Note: Descriptions are shown in the official language in which they were submitted.
JBF/jbf 23-96246-05 12/04/18 30797-E CIP FILED VIA EFS ON JULY 10, 2018
EXTRACTING MAXIMAL FREQUENCY RESPONSE POTENTIAL IN
CONTROLLABLE LOADS
CROSS-REFERENCE TO RELATED APPLICATIONS
[001] This application is a continuation-in-part of U.S. Patent Application
No. 15/746,258,
entitled "FREQUENCY THRESHOLD DETERMINATION FOR FREQUENCY-
RESPONSIVE LOAD CONTROLLERS," filed January 19, 2018, which application is the
U.S.
National Stage of International Application No. PCT/U52016/028901, entitled
"FREQUENCY
THRESHOLD DETERMINATION FOR FREQUENCY-RESPONSIVE LOAD
CONTROLLERS," filed April 22, 2016, which application claims the benefit of
prior U.S.
Provisional Application No. 62/197,979, entitled "CONTROLLER DESIGN OF GRID
FRIENDLY APPLIANCES FOR PRIMARY FREQUENCY RESPONSE," filed July 28, 2015.
This application also claims the benefit of prior U.S. Provisional Application
No. 62/625,266,
entitled "EXTRACTING MAXIMAL FREQUENCY RESPONSE POTENTIAL IN
CONTROLLABLE LOADS," filed February 1, 2018. The full disclosure of U.S.
Patent
Application No. 15/746,258, International Application No. PCT/U52016/028901,
U.S.
Provisional Application No. 62/197,979, and U.S. Provisional Application No.
62/625,266 is
hereby incorporated herein by reference.
ACKNOWLEDGMENT OF GOVERNMENT SUPPORT
[002] This invention was made with Government support under Contract No. DE-
AC05-
76RL01830 awarded by the U.S. Department of Energy. The Government has certain
rights in
the invention.
BACKGROUND
[003] Due to growing environmental concerns and economic and political
requirements, the
integration of renewable energy into the power grid has become a growing
trend. Renewable
energy sources have the potential to lead to a significant reduction in fossil
fuel consumption and
carbon dioxide emissions. Renewable energy generation, however, is typically
non-dispatchable
because it is often operated at the maximum output due to the low marginal
cost of renewable
energy. In addition, the available output of renewable generation can be
variable and uncertain
due to the intermittency of renewable energy.
- 1 -
CA 3027776 2018-12-17
JBF/Jbf 23-96246-05 12/04/18 30797-E C IP FILED VIA EFS ON JULY 10, 2018
[004] Large-scale integration of renewable energy into the power grid
substantially increases
the need for operational reserves. At the same time, the total system inertia,
as well as
contingency reserve, is decreasing as conventional generation is gradually
displaced by non-
dispatchable renewable generation. Therefore, it becomes extremely difficult
for a system
operator to maintain the stability and reliability of the power grid. If
operational reserves are
required to be provided by conventional generation for stability reasons, it
diminishes the net
carbon benefit from renewables, reduces generation efficiency, and becomes
economically
untenable. Hence, renewable penetration is still limited due to the lack of
appropriate
technologies that are able to reliably and affordably manage the dynamic
variability introduced
by renewable generation.
[005] Demand-side approaches can help alleviate some of the instability
resulting from
renewable generation sources. Conventionally, demand-side loads are treated as
passive and
non-dispatchable, but demand-side approaches such as management of flexible
loads have begun
to be introduced. Such approaches, however, typically do not produce a
frequency response
curve that closely matches the desired curve, which can cause additional
instability. Further,
conventional demand-side approaches can over- or undercompensate by managing
too many or
too few loads.
SUMMARY
[006] In today's power systems operations, traditional frequency control
resources (e.g. speed
governors, spinning reserves) are deployed to ensure resilient grid operations
under
contingencies, by restoring system frequency close to its nominal values. The
importance of
adequate (and cost-effective) frequency response mechanisms is expected to
grow even further
as the grid turns "greener" and "smarter." Electrical loads, if coordinated
smartly, have the
potential to provide a much faster, cleaner and less expensive alternative to
the traditional
frequency responsive resources. Potential of controllable loads to provide
frequency response
services has been explored both in academia and in industry.
[007] In order to scalably integrate millions of controllable devices (loads)
into the grid
operational paradigm, a hierarchical distributed control architecture is
conceptualized in which a
supervisor (e.g. a load aggregator) is tasked with dispersing the response of
the loads across the
ensemble so that some desirable collective behavior is attained. Dispersion of
load response in
frequency (by assigning to each load specific frequency thresholds to respond
to) allows a
- 2 -
CA 3027776 2018-12-17
JBF/ibf 23-96246-05 12/04/18 30797-E CIP FILED VIA EFS ON JULY 10, 2018
power-frequency droop-like response enabling easier integration of such
frequency-responsive
resources in the grid operational framework. However, the availability of the
end-use load to
respond to ancillary service requests strongly depends on the local dynamics
and constraints,
thereby adversely affecting the reliability of decentralized frequency control
algorithms.
[008] Examples described herein relate to frequency-responsive load
controllers that control
associated grid-connected electrical devices and determine frequency
thresholds at which such
controllers manage the associated grid-connected electrical devices. A
frequency-responsive
load controller can provide a demand-side contribution to stabilizing the
power grid by turning a
grid-connected electrical device on or off in order to bring the grid
frequency closer to a target
value (e.g., 50 or 60 Hz).
[009] In some examples, we consider a hierarchical control framework for
coordinating
ensembles of switching loads (e.g., electric water-heaters and residential air-
conditioners) to
provide frequency response services to the grid operator. Each device receives
a frequency
threshold which it uses to activate (turn "on" or "off') autonomously (e.g.,
without further user
intervention) when a frequency event happens. In some examples, at least some
of the devices
can activate at more than one level, thereby consuming varying levels of
power. In some
examples, at least some of the devices only activate or deactivate. In some
examples, at least
some of the devices are modeled as only activating or deactivating, but may
actually consume
varying levels of power. A metric is proposed to evaluate the "fitness" of
each device in
providing frequency response, while also using this metric to assign frequency
thresholds in a
way that can extract the maximal response potential of an ensemble.
[010] In some examples, a frequency range extending from a target grid
frequency to an end
frequency can be determined. A first portion of the frequency range can be
identified as a
deadband within which a grid-connected electrical device is not turned on or
off in response to
grid frequency deviations. The first portion extends from the target grid
frequency to a deadband
bound frequency. A second portion of the frequency range extends from the
deadband bound
frequency to the end frequency. A frequency, from the frequency range, can be
selected for use
as the frequency threshold. The frequency threshold is the grid frequency at
which the grid-
connected electrical device is automatically turned off or turned on by an
associated frequency-
responsive load controller. If the frequency selected for use as the frequency
threshold is within
the deadband, the frequency threshold is set to a frequency within the second
portion of the
- 3 -
CA 3027776 2018-12-17
JBF/jbf 23-96246-05 12/04/18 30797-E CIP FILED VIA EFS ON JULY 10,2018
frequency range. For example, the frequency threshold can be set to a first
available frequency
outside the deadband.
[011] In some examples, the frequency range is determined by receiving
instructions from a
supervisory coordinator configured to establish the frequency range based on
aggregated
characteristics of a number of grid-connected electrical devices being managed
by corresponding
frequency-responsive load controllers. For example, individual frequency-
responsive load
controllers can provide power (and state) information to the supervisory
coordinator, and the
coordinator can aggregate the power information and determine frequency
range(s) from which
frequency thresholds can be selected based on the aggregated power information
and a target
power-frequency curve. Power information can be re-aggregated periodically
(and the frequency
range recalculated) to accurately reflect the current load on the grid. In
such situations, the
frequency thresholds can be re-selected using the recalculated frequency range
to provide the
desired power-frequency curve.
[012] This summary is provided to introduce a selection of concepts in a
simplified form that
are further described below in the Detailed Description. This Summary is not
intended to
identify key features or essential features of the claimed subject matter, nor
is it intended to be
used to limit the scope of the claimed subject matter. The foregoing and other
objects, features,
and advantages of the disclosed subject matter will become more apparent from
the following
Detailed Description, which proceeds with reference to the accompanying
figures.
BRIEF DESCRIPTION OF THE DRAWINGS
[013] FIG. 1 is a diagram illustrating an example method of managing frequency
response
using a grid-connected electrical device.
[014] FIG. 2A is a scatter plot illustrating the curtailing frequency
threshold and power of a
plurality of example grid-connected electrical devices where the curtailing
frequency of the
devices is set to be at a first available frequency outside of the deadband if
initially randomly
selected to be inside the deadband.
[015] FIG. 2B is a graph illustrating a droop-like power-frequency curve
resulting from the
curtailing frequency thresholds illustrated in FIG. 2A.
[016] FIG. 3A is a graph illustrating a droop-like power-frequency curve in an
over-frequency
example.
- 4 -
CA 3027776 2018-12-17
JBF/jbf 23-96246-05 12/04/18 30797-E CIP FILED VIA EFS ON JULY 10, 2018
[017] FIG. 3B is a graph illustrating droop-like power-frequency curves for an
example in
which controllers can be used in both over- and under-frequency situations.
[018] FIG. 4 is a flow chart illustrating an example method of managing a grid-
connected
electrical device using a selected curtailing frequency threshold.
[019] FIG. 5 is a flow chart illustrating an example method of managing a grid-
connected
electrical device using a selected curtailing frequency threshold and a
selected rising frequency
threshold.
[020] FIG. 6 is a block diagram of an example frequency-responsive load
controller.
[021] FIG. 7 is a block diagram of an example frequency-responsive load
controller
implemented using a field programmable gate array (FPGA).
[022] FIG. 8 is a block diagram of an example hierarchical power grid
management system in
which a supervisory controller communicates with individual frequency-
responsive load
controllers.
[023] FIG. 9 is a block diagram of an example target power-frequency curve.
[024] FIG. 10 is a diagram illustrating an example method of managing
frequency response in
an electrical power distribution system using grid-connected electrical
devices.
[025] FIG. 11 is a block diagram of an example system for assigning frequency
thresholds to
grid-connected devices.
[026] FIG. 12 is a block diagram of an example resource controller of FIG. 11.
[027] FIG. 13 is a block diagram of an example load aggregator of FIG. 11.
[028] FIG. 14 illustrates an example power-frequency response curve.
[029] FIG. 15 illustrates an example error curve due to finite non-zero
sampling time.
[030] FIG. 16 shows sample under-frequency and over-frequency events.
[031] FIGS. 17A-17B illustrate example target and achieved frequency response
curves.
[032] FIGS. 18A-18B illustrate example performance under a cascading
contingency.
[033] FIG. 19 illustrates error statistics at varied commitment level as a
percentage of the
maximal guaranteed capacity.
[034] FIG. 20 illustrates performance results for simulated examples.
[035] FIG. 21 is a flowchart depicting an example method of assigning
frequency thresholds as
can be performed in certain examples of the disclosed technology.
[036] FIG. 22 is a flowchart depicting another example method of assigning
frequency
thresholds as can be performed in certain examples of the disclosed
technology.
- 5 -
CA 3027776 2018-12-17
JBF/pf 23-96246-05 12/04/18 30797-E CIP FILED VIA EFS ON JULY 10, 2018
[037] FIG. 23 is a flowchart depicting another example method of operating the
example
resource controller of FIG. 12 as can be performed in certain examples of the
disclosed
technology.
[038] FIG. 24 is an example computing environment that can be used in
conjunction with the
technologies described herein.
DETAILED DESCRIPTION
General Considerations
[039] For purposes of this description, certain aspects, advantages, and novel
features of the
embodiments of this disclosure are described herein. The disclosed methods,
apparatus, and
systems should not be construed as being limiting in any way. Instead, the
present disclosure is
directed toward all novel and nonobvious features and aspects of the various
disclosed
embodiments, alone and in various combinations and sub-combinations with one
another. The
methods, apparatus, and systems are not limited to any specific aspect or
feature or combination
thereof, nor do the disclosed embodiments require that any one or more
specific advantages be
present or problems be solved.
[040] Although the operations of some of the disclosed embodiments are
described in a
particular, sequential order for convenient presentation, it should be
understood that this manner
of description encompasses rearrangement, unless a particular ordering is
required by specific
language set forth below. For example, operations described sequentially may
in some cases be
rearranged or performed concurrently. Moreover, for the sake of simplicity,
the attached figures
may not show the various ways in which the disclosed methods can be used in
conjunction with
other methods. Additionally, the description sometimes uses terms like
"provide" or "achieve"
to describe the disclosed methods. These terms are high-level descriptions of
the actual
operations that are performed. The actual operations that correspond to these
terms may vary
depending on the particular implementation and are readily discernible by one
of ordinary skill in
the art having the benefit of the present disclosure.
[041] As used in this application and in the claims, the singular forms "a,"
"an," and "the"
include the plural forms unless the context clearly dictates otherwise.
Additionally, the term
"includes" means "comprises." Further, the terms "coupled" and "associated"
generally mean
electrically, electromagnetically, and/or physically (e.g., mechanically or
chemically) coupled or
linked and does not exclude the presence of intermediate elements between the
coupled or
associated items absent specific contrary language.
- 6 -
CA 3027776 2018-12-17
JBF/jbf 23-96246-05 12/04/18 30797-E CIP FILED VIA EFS ON JULY 10, 2018
[042] In some examples, values, procedures, or apparatus may be referred to as
"lowest,"
"best," "minimum," or the like. It will be appreciated that such descriptions
are intended to
indicate that a selection among many alternatives can be made, and such
selections need not be
better, smaller, or otherwise preferable to other selections.
[043] In the following description, certain terms may be used such as "up,"
"down," "upper,"
"lower," "horizontal," "vertical," "left," "right," and the like. These terms
are used, where
applicable, to provide some clarity of description when dealing with relative
relationships. But,
these terms are not intended to imply absolute relationships, positions,
and/or orientations. For
example, with respect to an object, an "upper" surface can become a "lower"
surface simply by
turning the object over. Nevertheless, it is still the same object.
[044] Using the systems, methods, and computer-readable media described
herein, frequency
thresholds can be determined at which grid-connected electrical devices can be
turned on or off
by associated frequency-responsive load controllers to provide "primary
frequency response" for
a power grid. As used herein, "primary frequency response" refers to adjusting
system
generation or system load of a power grid to balance the amount of generation
with the amount
of load (also referred to as demand), thereby maintaining a grid frequency
(frequency of the
voltage or current supplied by the grid) near to a target frequency (e.g., 50
or 60 Hz). A grid
frequency that begins to drop below the target frequency indicates excess
demand relative to
generation, and a grid frequency that begins to rise above the target
frequency indicates excess
generation relative to demand. Unlike previous approaches to selection of
frequency thresholds,
the described technologies maintain a desired "droop-like" power-to-frequency
curve that
indicates grid stability. "Droop" refers to a control scheme for generators in
the power grid. A
device performing droop control is automatically adjusting its power output in
accordance to
frequency deviations. Droop can be defined as the percentage change in
frequency at which the
device delivers all of its frequency regulating capability. "Droop-like"
refers to a scheme where
a device is automatically adjusting its power output in accordance to
frequency deviations,
regulating frequency at a defined percentage relative to frequency deviation
until the resource is
exhausted. The described technologies also allow determination of frequency
thresholds in both
autonomous and supervised arrangements.
[045] In an example autonomous arrangement, individual grid-connected
appliances (e.g.,
electric water heaters) are separately and autonomously controlled by
corresponding individual
frequency-responsive load controllers. For a particular appliance, the
frequency-responsive load
- 7 -
CA 3027776 2018-12-17
JBF/jbf 23-96246-05 12/04/18 30797-E CIP FILED VIA EFS ON JULY 10, 2018
controller randomly (or otherwise) selects a frequency threshold from
available frequencies in a
frequency range. If the selected frequency falls within a deadband, then the
controller sets the
frequency threshold to a frequency outside of the deadband instead. As a
specific example, the
controller can set the frequency threshold to a first available frequency (or
a frequency within a
narrow frequency band) outside of the deadband.
[046] The deadband is a frequency range near the target frequency and within
which deviations
from the target frequency are considered to be small enough to ignore for
demand-side primary
frequency response purposes. In conventional approaches, because the
frequencies within the
deadband are not available to be set as the frequency threshold, the resulting
distribution of
frequency thresholds over all controllers is not uniform over the entire
frequency range, and the
power-to-frequency relationship of the grid is not droop-like. In the
described technologies,
however, the controller selects the frequency threshold from a frequency range
that includes
frequencies in the deadband, but instead of actually using the frequency
within the deadband as
the threshold if selected, the controller uses the closest available frequency
outside of the
deadband. As used herein, "available" means available for use as a frequency
threshold.
Frequencies within the deadband, which cannot be used as the frequency
threshold, are
unavailable. "Available" does not refer to a state of being "taken" or in use
by another load
controller. That is, if, for multiple load controllers, a frequency in the
deadband is selected, more
than one (or all) of the load controllers can set the frequency threshold to
the first frequency
outside of the deadband. When viewed on a system-wide level, this approach
effectively
produces a weighting scheme that approximates what a uniform distribution of
frequency
thresholds over the entire frequency range, including the deadband, would be.
This weighted
distribution achieves the proper power-to-frequency relationship for grid
stability while still
allowing frequency thresholds to be excluded from the deadband.
[047] In an example supervised arrangement, a supervisory coordinator can
aggregate power
information (e.g., load and on/off status) for many grid-connected electrical
devices. Based on
the aggregate power available for being turned on or being turned off, a
frequency range
available for frequency thresholds can be determined based on a desired power-
frequency curve.
By considering the overall power of the loads available in the system,
situations in which too
much or too little load power is turned on or off (which creates instability
in the grid) can be
avoided. Individual frequency-responsive controllers can select frequency
thresholds, for
example as described above in the autonomous arrangement, once a frequency
range has been
- 8 -
CA 3027776 2018-12-17
JBF/jbf 23-96246-05 12/04/18 30797-E CIP FILED VIA EFS ON JULY 10, 2018
communicated to the controllers. In some examples, frequency threshold
selection for individual
controllers can be performed by the supervisory coordinator, and the
thresholds can be
communicated to the individual controllers.
[048] The described technologies produce a significant improvement to the
power grid
management technology and "smart" device technology areas. The demand-side
approaches
described herein reduce the need to rely on power generators to manage primary
frequency
response and allow for a greater integration of renewable energy sources into
the grid. Further,
by determining a range of frequency thresholds that result in a stable, droop-
like power-to-
frequency curve, the frequency-responsive controllers will be triggered less
often by not having
to correct the instability caused by the controllers' own response and will
thus consume fewer
controller computing resources. Additional examples are described below.
Frequency Threshold Selection Examples and Examples of Autonomous Arrangements
[049] Demand-side control presents a novel and viable way to supplement the
conventional
generation-side control for a power grid having an increased percentage of
renewable power
sources. An autonomous arrangement in which frequency-responsive controllers
associated with
corresponding grid-connected electrical devices respond individually to
frequency deviations
provides a fast response time for grid stabilization. In some approaches,
autonomous response
occurs for under-frequency load shedding, in which loads are turned off at
larger frequency
deviations from a target grid frequency in order to prevent, for example, a
grid or substation
failure. Such approaches, however, do not provide the proper droop-like
frequency response
necessary for demand-side primary frequency response.
[050] The frequency-responsive load controllers described herein can be, for
example, small
electronic devices that reside within grid-connected electrical devices (also
referred to simply as
"devices") such as appliances. The frequency-responsive load controllers (also
referred to
simply as "controllers") can be configured to monitor, for example, the AC
voltage (or current)
signal available to the devices at their wall outlets. When an under-frequency
(or in some
examples, an over-frequency) event is detected, the controller will alter the
operating mode of a
corresponding device to help the power grid, provided the device's current
operating mode can
be changed. In the example of an under-frequency event, the controller is
configured to request
that the electrical load be shed by its corresponding device whenever the grid
frequency falls
below a particular curtailing frequency threshold. The curtailing frequency
threshold can be, for
example, randomly chosen. In an over-frequency example, the controller is
configured to
- 9 -
CA 3027776 2018-12-17
JBF/Jbf 23-96246-05 12/04/18 30797-E CIP FILED VIA EFS ON JULY 10, 2018
request that an electrical device be turned on whenever the grid frequency
exceeds a particular
rising frequency threshold, which can also be randomly chosen.
[051] In recent years, appliance and equipment manufacturers have moved
rapidly toward mass
production of devices with smart grid capabilities that can be used with the
described
technologies. For implementation of frequency-responsive load controllers, the
response time
(e.g., the time constant of a low-pass filter for frequency measurement), can
directly affect the
frequency response of the bulk power system. In general, the shorter the
response time, the
better the system response. Shorter response time, however, can lead to false
inputs and noise.
In practice, selection of an appropriate response time can be done by
analyzing the frequency
characteristics of historic frequency events.
[052] The geographical distribution of controller-controlled devices within a
system can also
influence the impact of the demand-side management on the grid. Although there
are indications
that it may be more effective to have all the controllers deployed in the
proximity of the location
where the under- or over-frequency events have been caused, it is typically
not possible in
practice to know beforehand the location of such events. An even distribution
throughout a
system can be used instead. Such an even distribution can be implemented
through coordination
among various system operators from different areas.
[053] Another factor that can influence the effect of controllers on frequency
response in the
grid is the penetration level of controllers and associated devices (how many
devices having an
associated controller that are currently on and are thus available to be
turned off or how many
devices having an associated controller that are currently off and are thus
available to be turned
on). Transient signals tend to increase as the penetration level of
controllers increases, which
can potentially drive the system to instability. One approach to limiting
transients is to limit how
many controllers should actually respond to under-frequency events. For an
autonomous
arrangement, all available controllers will typically respond, regardless of
possible negative
consequences of the aggregated effect. The autonomous response of controllers
from different
geographical locations can instead, for example, be coordinated so that
negative consequences
are mitigated.
[054] Previous demand-side approaches to grid frequency management have been
used for
under-frequency load shedding and have not been used for primary frequency
response due to,
among other things, the lack of a droop-like frequency response curve. In some
situations, such
- 10 -
CA 3027776 2018-12-17
JBF/Jbf 23-96246-05 12/04/18 30797-E CIP FILED VIA EFS ON JULY 10, 2018
approaches can result in excessive power reduction, which can impact the
system stability
negatively.
[055] FIG. 1 illustrates a method 100 of managing frequency response using a
grid-connected
electrical device. Method 100 can be performed by or using, for example, a
frequency-
responsive load controller connected to or installed in the grid-connected
electrical device.
Example frequency-responsive load controllers are discussed with respect to
FIGS. 6 and 7. The
discussion of method 100 also references the examples shown in FIGS. 2A, 2B,
3A, and 3B for
clarity.
[056] In process block 102, a frequency range extending from a target grid
frequency to an end
frequency is determined. An example frequency range and target grid frequency
are shown in
FIGS. 2A and 2B. FIGS 2A and 2B show plots 200 and 220, respectively, that
illustrate an
under-frequency case in which devices are turned off when the grid frequency
falls below the
target grid frequency. In FIGS. 2A and 2B, the target grid frequency is 60 Hz,
and the frequency
range is frequency range 202 that extends from the target grid frequency of 60
Hz to the end
frequency of 59.95 Hz.
[057] The target grid frequency can depend upon the electrical grid. For
example, the target
grid frequency can be 60 Hz, as is typically used in North America, or 50 Hz,
as is typically used
in much of Europe and the rest of the world. The end frequency can be either
be below the target
grid frequency, as illustrated in FIGS. 2A and 2B, or above the target grid
frequency as
illustrated in the over-frequency example shown in FIG. 3. The end frequency
can be:
predetermined or dynamically calculated based on historic under- or over-
frequency events
and/or historic or current total system load of controlled devices; based on
empirically
determined or calculated frequencies at which the grid becomes unstable or
reaches a
performance threshold; or based on other factors.
[058] In process block 104, a first portion of the frequency range is
identified as a deadband.
The deadband extends from the target grid frequency to a deadband bound
frequency. The
deadband is a frequency range within which the grid-connected electrical
device is not turned on
or off by the frequency-responsive load controller. That is, frequency
deviations within the
deadband are tolerated, and demand-side management is not used to address the
deviations. In
the under-frequency example of FIGS. 2A and 2B, a deadband 204 is shown,
extending from the
target grid frequency of 60 Hz to a deadband bound frequency 206 (of 59.986
Hz). The extent of
the deadband can be: predetermined or dynamically calculated based on historic
under- or over-
- 11 -
CA 3027776 2018-12-17
JBF/jbf 23-96246-05 12/04/18 30797-E CIP FILED VIA EFS ON JULY 10, 2018
frequency events and/or historic or current total system load of controlled
devices; based on
controller response time; based on historic, empirically determined, or
calculated frequencies at
which primary frequency response is determined to be desirable; or based on
other factors. In
some examples, the size of deadband 204 is comparable to generation-side
deadbands used in
generation-side frequency response.
[059] A second portion of the frequency range extending from the deadband
bound frequency
to the end frequency is identified in process block 106. With reference again
to FIGS. 2A and
2B, a second portion 208 of frequency range 202 extends from a first available
frequency
(59.985) below deadband bound frequency 206 to the end frequency (59.95 Hz).
[060] In process block 108, a frequency, from the frequency range (e.g., from
frequency range
202 of FIG. 2A), is selected for use as a frequency threshold. The frequency
threshold is a grid
frequency at which the grid-connected electrical device is automatically
turned off or turned on
by an associated frequency-responsive load controller. In under-frequency
examples, such as the
example illustrated in FIGS. 2A and 2B, the deadband bound frequency is lower
than the target
grid frequency and the end frequency is lower than both the deadband bound
frequency and the
target grid frequency. In such examples, the frequency threshold is a
curtailing frequency
threshold, and the curtailing frequency threshold is the grid frequency at
which the grid-
connected electrical device is turned off by the associated frequency-
responsive load controller.
Frequency deviations below the target grid frequency indicate a greater load
than can be
supported by the current generation capacity.
[061] In over-frequency examples, such as the example illustrated in FIG. 3A,
the deadband
bound frequency is higher than the target grid frequency and the end frequency
is higher than
both the deadband bound frequency and the target grid frequency. In such
examples, the
frequency threshold is a rising frequency threshold, and the rising frequency
threshold is the grid
frequency at which the grid-connected electrical device is turned on by the
associated frequency-
responsive load controller. Frequency deviations above the target grid
frequency indicate greater
generation than can be used by the current grid load.
[062] In some examples, both a rising frequency threshold and a curtailing
frequency threshold
are established (along with two corresponding frequency ranges, end
frequencies, and
deadbands) for a controller and corresponding device, allowing the device to
be used for over-
frequency or under-frequency response. When both a rising frequency threshold
and a curtailing
- 12 -
CA 3027776 2018-12-17
JBF/jbf 23-96246-05 12/04/18 30797-E CIP FILED VIA EFS ON JULY 10, 2018
frequency threshold are used, the frequency ranges, deadbands, etc. can be
mirrored around the
target grid frequency or determined separately (as shown, for example, in FIG.
3B).
[063] The frequency selected for use as the frequency threshold in process
block 108 can be
selected, for example, using a probabilistic approach, such as random
selection, to select the
frequency from a group of available frequencies in the frequency range. For
example, a
frequency responsive load controller can randomly select a number between the
end frequency
and the target grid frequency. Random selection, over a large sample size,
results in a uniform
distribution of selected frequencies over the frequency range. An example of a
large number of
controllers each having a randomly selected frequency threshold is illustrated
in FIG. 2A and
discussed below.
[064] Upon determining, that the frequency selected for use as the frequency
threshold is within
the deadband, the frequency threshold is set to a frequency within the second
portion of the
frequency range in process block 110. In some examples, when the selected
frequency is within
the deadband, the frequency threshold is set to an available frequency that is
closest to the
deadband bound frequency. This is illustrated in plot 200 of FIG. 2A, where
many points (each
representing an individual controller) are located at frequency 210. Frequency
210 is a first
available frequency outside of deadband 204. For selected frequencies that are
inside deadband
204, the frequency threshold is set to frequency 210 to provide a weighting to
create a desired
droop-like response, illustrated by power-frequency curve 222 of FIG. 2B,
while still
maintaining deadband 204.
[065] As used herein, "available" means available for selection. The
frequencies that are
available are outside of the deadband and account for the granularity with
which frequency can
be specified. Frequency can be selected in increments of .0001 Hz, .001 Hz,
.005, .01 Hz, or
other increments. As an example, if frequency is specified/selectable in .005
Hz increments,
even though a frequency that is .00000001 Hz outside of the deadband bound is
closer to the
deadband bound than a second frequency .005 Hz outside the deadband bound, the
second
frequency is the closest available frequency because of the .005 Hz frequency
increments being
used. In an under-frequency example, for a deadband bound frequency indicating
the end of the
deadband is 59.986, 59.990, etc., if the selected frequency is within the
deadband, the frequency
threshold can be set to 59.985, 59.980, or other value below but near the end
of the deadband.
[066] In some examples, the second portion of the frequency range comprises a
third portion
extending from the deadband bound to less than halfway from the deadband bound
to the end
- 13 -
CA 3027776 2018-12-17
JBF/jbf 23-96246-05 12/04/18 30797-E CIP FILED VIA EFS ON JULY 10, 2018
frequency, and the frequency within the second portion of the frequency range
to which the
frequency threshold is set is within the third portion. Plot 220 of FIG. 2B
illustrates a third
portion 224. Third portion 224 is less than half of the size of second portion
208 and extends
from just below the deadband bound frequency 206 to approximately 59.97 Hz.
(In this
particular example, third portion 224 is approximately a same size as deadband
204.) The
frequency within the third portion used as the frequency threshold can be
selected, for example,
by randomly selecting one of the available frequencies within the third
portion. The third portion
provides a relatively narrow band (as compared to the second portion) of
frequencies that can be
used to adjust the frequency response curve to a more droop-like shape. In
contrast to FIG. 2A
in which the first available frequency is used as the threshold for the
controllers for which the
selected frequency for use as the threshold is within the deadband, setting
the threshold to a
value within third portion 224 of FIG. 2B provides a more gradual initial
response to under-
frequency events while still providing a droop-like response as illustrated by
power-frequency
curve 222.
[067] Method 100 can further comprise upon determining that the grid frequency
meets the
frequency threshold, turning off (for under-frequency events) or turning on
(for over-frequency
events) the electrical device. In some examples, frequency of the grid voltage
is measured, and
the measurement is compared to the threshold. Grid current frequency can also
be measured.
Frequency measurement, as used herein, also includes measuring the period of a
signal (which is
the inverse of frequency). Measurements/comparisons can be performed
periodically.
[068] In some examples, the frequency range is determined by receiving
instructions from a
supervisory coordinator configured to establish the frequency range based on
aggregated
characteristics of a plurality of grid-connected electrical devices being
managed by
corresponding frequency-responsive load controllers. The aggregated
characteristics can include
power consumption or peak power consumption as well as an "on" or "off'
status. In some
examples, method 100 is performed by the supervisory coordinator, and the
frequency
threshold(s) are communicated to individual controllers. Supervisory
coordinators are discussed
further below.
[069] FIG. 2A illustrates a plot 200 of an example distribution of
approximately 1,000 devices
having associated controllers. The power rating of the devices is distributed
uniformly between
4 and 6 kW. Each point in plot 200 represents a device having a curtailing
frequency threshold
and a power rating. The frequency thresholds are uniformly distributed over
second portion 208
- 14 -
CA 3027776 2018-12-17
JBF/jbf 23-96246-05 12/04/18 30797-E CIP FILED VIA EFS ON JULY 10, 2018
of frequency range 202, with the exception of the many points located at
frequency 210, which is
the first available frequency below deadband 204. The points at frequency 210
represent
controllers for which the frequency selected for use as the frequency
threshold fell within
deadband 204, and because deadband frequencies are not available for use as a
frequency
threshold, the frequency threshold for these controllers was instead set to
first available
frequency 210. This approach provides a weighting to create the desired droop-
like response
while still keeping deadband 204 unavailable for frequency thresholds.
[070] Plot 220 of FIG. 2B illustrates droop-like power-frequency curve 222
that corresponds to
the distribution shown in FIG. 2A. The x-axis of plot 220 represents
frequency, and the y-axis
represents a percentage of the aggregate controller-managed power that is
turned off by the
controllers to provide primary frequency response. As is illustrated in plot
220, due to the
random distribution of frequency thresholds illustrated in FIG. 2A, the number
of controllers
turning off a corresponding device increases as the grid frequency drops
until, at the end of
second portion 208 of frequency range 202, all of the available controllers
have turned their
corresponding device off.
[071] As discussed above, deadband 204 represents a frequency band in which
frequency
deviations are tolerated and primary frequency response is not initiated. The
deadband acts to
ignore noise and prevent overreactions and serves other purposes as well. In a
theoretical
simplification without a deadband, in which the practical reasons for using a
deadband would not
apply, a droop-like response in a system without a deadband would include
dashed line 224, such
that the droop-like response both is linear over all of frequency range 202
and reaches the 0%
power, 60 Hz point on plot 220. Using the described approaches, the
"weighting" provided by
the many controllers for which frequency thresholds are set at first available
frequency 210 (or in
third portion 224) provides a step- or impulse-type response that quickly
brings the power
percentage to the theoretical level (meeting dotted line 224) for a frequency
deviation just below
deadband 204. The uniform distribution of the remaining frequency thresholds
maintains the
droop-like response over the remainder of frequency range 202. Thus, power-
frequency curve
222 has the desired characteristic of being droop-like over frequency range
202 while also
dropping to zero because of the practically desirable use of the deadband.
[072] In contrast to the described technology, in a conventional approach, use
of the deadband
(e.g., deadband 204), results in a power-frequency curve 226. In power-
frequency curve 226,
rather than reaching 0% power at 60 Hz, 0% power is reached at deadband bound
frequency 206.
- 15 -
CA 3027776 2018-12-17
JBF/Jbf 23-96246-05 12/04/18 30797-E CIP FILED VIA EFS ON JULY 10, 2018
While power-frequency curve 226 is linear, the slope of power-frequency curve
226 differs from
power-frequency curve 222 because of the different 0% power frequency, and
power-frequency
curve 226 is therefore not droop-like. The non-droop-like response in previous
approaches is
most noticeable for frequency deviations just slightly below the deadband
because few
controllers will be triggered as compared to the approaches shown in FIGS. 2A
and 2B.
[073] FIGS. 2A and 2B illustrate an under-frequency example. FIG. 3A
illustrates an over-
frequency example, and FIG. 3B illustrates an example in which primary
frequency response can
be provided for both under- and over-frequency situations. FIG. 3A illustrates
a plot 300 similar
to plot 202 of FIG. 2B, except that the frequency range along the x-axis
increases from left to
right to represent an over-frequency example. A frequency range extends from a
target grid
frequency of 60 Hz to an end frequency of 60.050 Hz. A deadband 302 extends
from 60 Hz to a
deadband bound frequency 304. A second portion 306 of the frequency range
extends from just
above the deadband bound frequency 304 to the end frequency (60.050 Hz).
[074] Rising frequency thresholds are selected from the entire frequency range
(from 60 Hz to
60.050 Hz), and for controllers for which a selected frequency falls within
deadband 302, the
rising frequency threshold is set to a frequency within second portion 306
(e.g., a closest
available frequency above deadband 302 or a frequency within a narrow
frequency band
extending from deadband bound frequency 304). Similar to plot 220 of FIG. 2B,
no controllers
activate devices for frequency deviations within deadband 302, and the number
of controllers
turning on a corresponding device increases as the grid frequency increases
until, at the end of
second portion 306, all of the available controllers have turned their
corresponding device on.
[075] Also similar to plot 220 of FIG. 2B, the "weighting" provided by the
many controllers for
which rising frequency thresholds are set at a first available frequency above
deadband 302 (or in
a narrow frequency band above deadband 302) provides a step- or impulse-type
response that
quickly brings the power percentage to the theoretical level (meeting dotted
line 308) for a
frequency deviation just above deadband 302. The uniform distribution of the
remaining
frequency thresholds maintains a droop-like response over the remainder of
frequency range 306,
as shown by power-frequency curve 310. Thus, power-frequency curve 310 has the
desired
characteristic of being droop-like over frequency range 306 while also
dropping to zero over
deadband 302 because of the practically desirable use of deadband 302.
[076] FIG. 3B shows a plot 320 of power-frequency curves 322 and 324. Power-
frequency
curve 322 is an under-frequency example as shown in FIG. 2B (with the slope of
power-
- 16 -
CA 3027776 2018-12-17
JBF/pf 23-96246-05 12/04/18 30797-E C1P FILED VIA EFS ON JULY 10, 2018
frequency curve 322 going negative to account for the x-axis values of
frequency increasing to
the right, in contrast to FIG. 2B). Power-frequency curve 324 is an over-
frequency example as
shown in FIG. 3A. In plot 320, there is an upper (or rising) deadband 326 and
an upper second
portion 328 (similar to deadband 302 and second portion 306 of FIG. 3A). Upper
deadband 326
and upper second portion 324 form an upper frequency range. Similarly, plot
320 includes a
lower (or curtailing) deadband 330 and a lower second portion 332 (similar to
deadband 204 and
second portion 208 of FIG. 2B) that together form a lower frequency range. The
upper
frequency range is used for over-frequency primary frequency response, and the
lower frequency
range is used for under-frequency primary frequency response, similar to the
discussion with
respect to FIGS. 2A-3A. In some examples, the upper frequency range and lower
frequency
range are a same size and rising deadband 326 and curtailing deadband 330 are
a same size. In
other examples, they are determined separately, and rising deadband 326 does
not necessarily
correspond to curtailing deadband 330, etc.
[077] The technology described herein was tested for an under-frequency
example using the
IEEE 16-machine 68-bus test system. This test system approximates the
interconnection
between the New England test system (NETS) and the New York power system
(NYPS). There
are five areas in total. Area 4 represents NETS with generators G1 to G9, and
area 5 represents
NYPS with generators G10 to G13. Generators G14 to G16 are equivalent
aggregated
generators that model the three neighboring areas connected to NYPS. The
system parameters
are taken from the data files that come with the Power System Toolbox (PST)
distribution. The
total load in the system is 18,333.90 MW with 5,039.00 MW in the NETS (area 4)
and 7,800.95
MW in the NYPS (area 5). The total load of online GFAs is 800 MW, which are
evenly
distributed among areas 4 and 5. The controllers in these studies are selected
to be electric water
heaters. The curtailment time delay td is selected to be 0.4 seconds for the
hardware
implementation. The activation time delay td a is randomly chosen between 2
and 3 minutes.
[078] Two scenarios were considered. In the first scenario, the system
responses in four
situations are compared when the system is subject to small disturbances. The
under-frequency
event considered here is the tripping of generator Gl. Since the power output
of generator G1 is
small, the resulting frequency deviation is so small that the lowest frequency
is within the range
of 59.95 Hz and 59.985 Hz. In the second scenario, the comparison between the
system
responses in four different situations is performed again when the system is
subject to a large
- 17 -
CA 3027776 2018-12-17
JBF/jbf 23-96246-05 12/04/18 30797-E CIP FILED VIA EFS ON JULY 10,2018
disturbance. The under-frequency event in this case study is the tripping of
generator G12,
which has large power output before the tripping occurs. In both scenarios,
primary frequency
response using the described technology was very close to the desired droop-
like situation.
Example Controllers and Controller Operation
[079] FIG. 4 shows an example operational flow 400 for a controller
implemented in an under-
frequency example. In process block 402, upon determining that a frequency
selected for use as
a curtailing frequency threshold is within the deadband (e.g., as in process
block 108 of FIG. 1),
the curtailing frequency threshold is set to a frequency outside the deadband
(e.g., a first
available frequency). In process block 404, grid frequency is monitored and
operation of a grid-
connected electrical device is managed. In some examples, individual
controllers have four
different operating modes including active 406, triggered 408, curtailed 410,
and released 412.
In the active operating mode 406, the individual controller evolves based on
its internal
dynamics, turning ON or OFF according to its predefined control logic. Once
the controller
detects that the grid frequency falls below a predetermined curtailing
frequency threshold fih,
the controller changes its operating mode from active 406 to triggered 408.
The controller
remains in this mode as long as the grid frequency does not return abovefih. A
time tb_a is the
time the device has been in the released mode, and a time tb_, is the time the
device has been in
the triggered mode.
[080] If the under-frequency event persists longer than the response time td
(curtailment time
delay) of the controller, the device shuts down and switches from triggered
408 to curtailed 410.
The time period of td is defined by the response time of a low-pass digital
filter in charge of
smoothing the frequency measurements in order to avoid reactions to
unrealistic data and noise.
Once the grid frequency rises above a predetermined restoring frequency
threshold frih,
where fr_th > ff_th , the controller switches from curtailed 410 to released
412 and remains in this
mode provided the grid frequency stays above frih . If it has been released
for a period of time
longer than td a, the controller switches from released 412 to active 406, and
follows its nominal
internal dynamics. The activation time delay td a is designed in order to
minimize or reduce the
rebound effect when all the controllers would turn on at the same time.
- 18 -
CA 3027776 2018-12-17
JBF/jbf 23-96246-05 12/04/18 30797-E CIP FILED VIA EFS ON JULY 10, 2018
[081] FIG. 5 includes flow chart 500 that illustrates an example operation of
a controller
capable of providing primary frequency response for both over- and under-
frequency events. In
process block 502, if a selected frequency is within a lower deadband
(curtailing deadband), then
the curtailing frequency threshold is set below the lower deadband, and if a
selected frequency is
within an upper deadband (rising deadband), then the rising frequency
threshold is set above the
upper deadband. Frequency monitoring begins in process block 504.
[082] Functionally, each individual controller has two different operating
modes ¨ under-
frequency ( f 5_ 60 Hz) and over-frequency ( f > 60 Hz) modes (where 60 Hz is
the nominal
(target) frequencyfno.). In the under-frequency mode, the controller reacts to
the under-
frequency events. In the over-frequency mode, it reacts to the over-frequency
events. In some
examples, at any given time instant, the controller can only be operated in
one mode, which is
determined and changed according to the local frequency measurement.
Furthermore, two
operating modes can be further divided into seven different states including
free 506, triggered
off 508, triggered on 510, forced off 512, forced on 514, released off 516,
and released on 518.
In the state of free 506, the controller evolves based on their internal
dynamics, turning ON or
OFF according to their predefined internal control.
[083] In process block 520, time is set to zero, and in process block 522, the
initial state of the
controller is set to free 506. The grid frequency is measured in process block
524 and provided
to a low-pass filter in process block 526, and if the result indicates a
frequency deviation, an
operating mode (over- or under-frequency) is determined in process block 528.
If the measured
frequency is less than a target frequency, then a current state is set through
process block 530 by
way of process blocks 532, 534, 536, and/or 538. In process block 532, if the
grid frequency
falls below a predetermined curtailing frequency threshold f7, the controller
changes its
operating state from free 506 to trigger off 508. If, in process block 534,
the time of the
frequency event tbu , persists longer than the response time Tbuõ the
controller shuts down the
device and switches it from triggered off 508 to force off 512. The time
period of Tb", is defined
by a low-pass filter (e.g., a digital low-pass filter, applied in process
blocks 526, 544, and/or 560)
in charge of smoothing the frequency measurements to avoid reactions to
unrealistic data and
noise.
- 19 -
CA 3027776 2018-12-17
JBF/Jbf 23-96246-05 12/04/18 30797-E CIP FILED VIA EFS ON JULY 10, 2018
[084] Once the grid frequency rises above a predetermined restoring frequency
threshold fu in
process block 536, where fru > j, the controller switches from forced off 512
to released off
516. The controller remains in this state, given that the frequency stays
above f,. If the
controller has been in the state of released off 516 for a longer time tbu
than the release time
delay Tb " as determined in process block 538, the controller switches its
state back to free 506
and follows its nominal internal dynamics. The release time delay T, "r is
designed for the
purpose of preventing the rebound effect that occurs when all the controllers
try to return to their
normal operations at the same time. Frequency is determined in process block
540, time is
incremented in process block 542, and a low-pass filter is applied in process
block 544 to prepare
the most recent frequency measurement obtained in process block 540 for
another iteration
through process blocks 530-538.
[085] If the measured frequency is greater than a target frequency (over-
frequency event), then
a current state is set through process block 546 by way of process blocks 548,
550, 552, and/or
554. In process block 548, if the grid frequency rises above a predetermined
rising frequency
threshold f, the controller changes its operating state from free 506 to
trigger on 510. If, in
process block 550, the time of the frequency event t;), , persists longer than
the response
time Tb õ the controller turns on the device and switches it from triggered on
510 to forced on
514. The time period of Tb , is defined by a low-pass filter in charge of
smoothing the frequency
measurements to avoid reactions to unrealistic data and noise.
[086] Once the grid frequency rises above a predetermined restoring frequency
threshold f: in
process block 552, where f,. < ft , the controller switches from forced on
514 to released on
518. The controller remains in this state, given that the frequency stays
below fr . If the
controller has been in the state of released on 518 for a longer time tb ,
than the release time
delay Tb , as determined in process block 554, the controller switches its
state back to free 506
and follows its nominal internal dynamics. The release time delay Tb , is
designed for the
purpose of preventing the rebound effect that occurs when all the controllers
try to return to their
- 20 -
CA 3027776 2018-12-17
JBF/jbf 23-96246-05 12/04/18 30797-E CEP FILED VIA EFS ON JULY 10, 2018
normal operations at the same time. Frequency is determined in process block
556, time is
incremented in process block 558, and a low-pass filter is applied in process
block 560 to prepare
the most recent frequency measurement obtained in process block 556 for
another iteration
through process blocks 548-554. In some examples, the low-pass filter applied
in process blocks
526, 544 and 560 are the same filter. From free state 506, time is incremented
in process block
562, frequency is measured in process block 564, a low-pass filter is applied
in process block
526, and a decision is again made in process block 528 as to whether to enter
an under- or over-
frequency mode.
[087] Two under-frequency examples follow (similar examples can be constructed
for the case
of over-frequency events). A controller starts out in the state of free when
the frequency starts to
dip. When the frequency drops below the curtailing frequency threshold fu, the
controller
changes its state to triggered off. Then, the frequency is restored above the
restoring frequency
threshold j: within the response time Tbuõ so the controller changes its state
back to free
resuming the normal operation.
[088] In a second example, the controller also starts in the state of free.
When the frequency
drops below the frequency threshold fiu , the controller changes its state to
triggered off. In this
case, the frequency is not restored above the frequency threshold fru within
the response
time Tbuõ so the controller changes its state to forced off. The controller
stays in the state of
forced off until the frequency is restored above the frequency threshold fru,
and then changes its
state to released off However, the frequency does not stay above f,' for
enough time, so the
controller changes its state back to forced off After some time, the frequency
returns above fru
again and the controller changes its state to released off Finally, the
frequency stays above the
j: for a longer time than the release time Tbur, , so the controller changes
its state to free resuming
the normal operation.
[089] FIG. 6 illustrates a frequency-responsive load controller 600.
Controller 600 includes a
curtailing frequency threshold selector 602 implemented by computing hardware.
The
computing hardware can include a programmable logic device such as a field
programmable gate
array (FPGA), an application-specific integrated circuit (ASIC), and/or one or
more processors
- 21 -
CA 3027776 2018-12-17
JBF/jbf 23-96246-05 12/04/18 30797-E CIP FILED VIA EFS ON JULY 10, 2018
and memory. Curtailing frequency threshold selector 602 is configured or
programmed to select
a frequency from a frequency range for use as a curtailing frequency
threshold. The frequency
range can be stored in the computing hardware (e.g., stored in memory). The
curtailing
frequency threshold is a grid frequency at or below which a grid-connected
electrical device 604
associated with frequency-responsive load controller 600 is turned off.
[090] Curtailing frequency threshold selector 602 is further configured or
programmed to, upon
determining that the frequency selected for use as the curtailing frequency
threshold is within an
under-frequency deadband of the frequency range, set the curtailing frequency
threshold to a
frequency lower than the under-frequency deadband but within the frequency
range. The under-
frequency deadband (also referred to as the lower deadband or curtailing
deadband) is a
frequency range over which the grid-connected electrical device is not turned
off (and remains
on if already on) by the frequency-responsive load controller. Curtailing
frequency threshold
selector 602 can be configured or programmed to perform any of the frequency
threshold
selection approaches described herein, including those discussed with respect
to FIGS. 1-5.
[091] Frequency-responsive load controller 600 also includes a power
controller 606
implemented by the computing hardware. Power controller 606 is configured or
programmed to
monitor the grid frequency at grid-connected electrical device 604, and, upon
determining that
the grid frequency meets or falls below the curtailing frequency threshold,
initiate a powering off
of grid-connected electrical device 604. Power controller 606 can include a
voltmeter, ammeter,
or other measurement device. Power controller 606 can interface directly with
a power supply
circuit (e.g., a switch) of grid-connected electrical device 604 or can
transmit a power control
signal to a different circuit or component of grid-connected electrical device
604.
[092] In some examples, the frequency lower than the under-frequency deadband
but within the
frequency range that is set as the curtailing frequency threshold is a first
available frequency
lower than the under-frequency deadband. In other examples, a second, third,
or other available
frequency lower than the under-frequency deadband is used. In still other
examples, the
frequency set as the curtailing frequency threshold is selected from a narrow
frequency band
lower than the deadband (e.g., less than half of the range from the end of the
under-frequency
deadband to the end of the frequency range).
[093] Controller 600 can also comprise a rising frequency threshold selector
608 implemented
by the computing hardware. Rising frequency threshold selector 608 is
configured or
programmed to select a second frequency from a second frequency range for use
as a rising
- 22 -
CA 3027776 2018-12-17
JBF/Jbf 23-96246-05 12/04/18 30797-E CIP FILED VIA EFS ON JULY 10, 2018
frequency threshold. The rising frequency threshold is a grid frequency at or
above which grid-
connected electrical device 604 is turned on. Rising frequency threshold
selector 608 is further
configured or programmed to, upon determining that the second frequency is
within an over-
frequency deadband of the second frequency range, set the rising frequency
threshold to a
frequency higher than the over-frequency deadband but within the second
frequency range. The
over-frequency deadband (also referred to as the upper deadband or rising
deadband) is a
frequency range over which grid-connected electrical device 604 is not turned
on by frequency-
responsive load controller 600. In examples in which rising frequency
threshold selector 608 is
present, power controller 606 is further configured or programmed to, upon
determining that the
grid frequency meets or rises above the rising frequency threshold, initiate a
powering on of grid-
connected electrical device 604.
[094] In some examples, the frequency higher than the over-frequency deadband
but within the
frequency range that is set as the rising frequency threshold is a first
available frequency higher
than the over-frequency deadband. In other examples, the frequency set as the
rising frequency
threshold is selected from a narrow frequency band higher than the deadband
(e.g., less than half
of the range from the end of the over-frequency deadband to the end of the
frequency range).
Frequency-responsive load controller 600 can include curtailing frequency
threshold selector 602
and not rising frequency threshold selector 608, rising frequency threshold
selector 608 and not
curtailing frequency threshold selector 602, or both curtailing frequency
threshold selector 602
and rising frequency threshold selector 608.
Example Hardware Configurations
[095] In an example computing hardware configuration of an under-frequency
frequency-
responsive load controller, a 5-cm x 7.5-cm (2-in. x 3-in.) digital electronic
controller board is
used. The digital intelligence is based on an Altera FPGA. Inputs to the
controller board include
V DC, which is used to power the board, and a 24 V AC voltage-sensing input
from a voltage
transformer that is used to sense grid frequency of a grid-connected
electrical device's 120 or
240 V AC electric service. The AC signal is conditioned by a series of
comparators that convert
the AC sinusoid into a square wave signal having fast rise and fall times. The
period of the
resulting 60 Hz square wave is measured using the pulse count from a 7.2 MHz
crystal oscillator
reference. Outputs of the controller board consist of several digital outputs,
the characteristics
and meanings of which can be assigned by firmware. In this example, only the
"relay control"
signal is passed along to the controlled electrical device. This signal is
pulled to its low logic
- 23 -
CA 3027776 2018-12-17
JBF/jbf 23-96246-05 12/04/18 30797-E CIP FILED VIA EFS ON JULY 10, 2018
state while a curtailment response was being requested from the controlled
electrical device.
Remaining output pins are assigned to facilitate testing and troubleshooting,
but these additional
signals are not used for device control in this example.
[096] In this example, the output of the controller is a binary signal. Grid-
connected electrical
device load current does not flow through any part of the controller board. In
examples in which
the electrical device is an electric water heater, the binary output signals
can be used to control
relay switches in the control modules for water-heater loads. In examples in
which the electrical
device is a clothes dryer, optically isolated versions of the controllers'
output signals can be sent
to the dryer's communication processors, where they can be translated into the
dryer's
proprietary serial protocol and sent to and understood by the dryer's
microcontrollers.
[097] Portions of an example controller 700 are illustrated in FIG. 7. FPGA
702 can be or can
be similar to an Altera EPM7128BTC100-10 FPGA. This FPGA embodiment is by way
of
example only, as other circuits or processing devices can be used, such as
application specific
integrated circuits (ASICs) or microprocessors executing suitable instructions
for performing the
disclosed functions. In the example of FIG. 7, a hardware gate design approach
is used to
achieve an efficient implementation using the limited number of macro cells of
FPGA 702. In
some examples, controller 700 determines frequency by measuring the period of
an input signal
704. Input signal 704 is stepped-down to 24 V AC from an, e.g., 120 or 240 V,
AC voltage. The
period of the signal is the reciprocal of the signal's frequency. A signal
conditioning stage 706
can include, for example, a series of comparators. The conditioned 60 or 50 Hz
square wave
from the power grid is an input to a phase locked loop (PLL) 708 that is
implemented using
FPGA 702. PLL 708 removes jitter from the period measurement and prevents
logic confusions
that can occur when multiple zero crossings occur in noisy device electrical
environments. The
period of the output of PLL 708 is measured at counter 709 using a pulse count
from an (e.g., 7.2
MHz) crystal oscillator 711 reference.
[098] A difference is taken in summation stage 710 between the period measured
using PLL
708 and counter 709 and the present reported period of controller 700 (the
negative of the period
count is summed with the measured period, resulting in a difference). This
difference is an error
signal. The error signal is then divided by an integer in stage 712 to create
a low-pass filtered
tracking of the actual frequency. In some examples, the divisor 16 is used,
but any other divisor
can be used and is within the scope of the disclosed technology. This divisor
removes the
responses to high-frequency noise, but it also slows the response to
legitimate changes, as is
- 24 -
CA 3027776 2018-12-17
JBF/jbf 23-96246-05 12/04/18 30797-E CIP FILED VIA EFS ON JULY 10,2018
typical for low-pass filtering. The result of this division (an attenuated
error signal) in stage 712
is then added to the reported period in summation stage 714. The reported
period is then
digitally compared against thresholds by power controller 716, which can be
similar to power
controller 608 of FIG. 6, to determine the state of an output-control signal.
FPGA 702 is also
used to implement at least one of a curtailing threshold frequency selector
(not shown) or rising
threshold frequency selector (not shown) that can be similar to the
corresponding components in
FIG. 6.
Frequency Range Determination Examples and Examples of Supervised Arrangements
[099] The frequency threshold selection technologies described herein can also
be used in a
hierarchical decentralized control strategy for engaging the end-use loads to
provide primary
frequency response. In some examples, two decision-making layers including
supervisory and
device layers, are used. Additional decision-making layers can also be used.
Frequency-
responsive load controllers at the device layer can still be operated in an
autonomous fashion to
provide a quick response while a coordinator at the supervisory layer
coordinates the
autonomous responses to overcome the stability issue associated with high
penetration of
controllers. These approaches provide an aggregated response that is droop-
like without over-
responding to frequency deviations due to high controller penetration.
Simulation results
illustrate the effectiveness of such a hierarchical decentralized control
strategy in providing
primary frequency response using controllers associated with grid-connected
electrical devices.
[0100] FIG. 8 illustrates a hierarchical decentralized arrangement 800 that
includes two decision-
making layers ¨ a supervisory layer 802 and a device layer 804. In supervisory
layer 802, a
supervisory coordinator 806 is responsible for ensuring that an aggregated
response from
engaged controllers is droop-like during frequency events and preventing the
aggregated
response from being excessive under high penetration of controllers.
Supervisory coordinator
806 can be, for example, implemented on one or more server computers in the
cloud or on a
particular computing device or devices accessible over a network such as the
Internet. In some
examples, additional intermediate decision-making layers are present.
[0101] Supervisory coordinator 806 communicates with controllers 808, 810, and
812.
Controllers 808, 810, and 812 are associated with grid-connected electrical
devices 814, 816, and
818, respectively. Communication between supervisory coordinator 806 and
controllers 808,
810, and 812 can occur, for example, once every control period (e.g., once
every 5, 10, 15, 30, or
60 min, etc.) and/or after a request has been sent by or received by
supervisory coordinator 806
- 25 -
CA 3027776 2018-12-17
JBF/jbf 23-96246-05 12/04/18 30797-E C IP FILED VIA EFS ON JULY 10, 2018
= =
based on non-time-based criteria (e.g., total system load, total available
generation, historical
frequency deviation information, etc.). Communication can occur, for example,
over the Internet
or other computer network, over a cellular network, through power line
communication (PLC),
or through other approaches.
[0102] In examples in which periodic communication is used, the length of the
control period
can be selected based on the characteristics of controllers 808, 810, and 812
and/or based on
historical frequency deviation information, characteristics of the grid, or
other factors.
Controllers 808, 810, and 812 submit power information, including power rating
(in kW) and
power mode (ON or OFF), to supervisory coordinator 806 at the beginning of
each control
period or upon request. After collecting the power information, supervisory
coordinator 806
divides controllers 808, 810, and 812 (as well as other available controllers)
into two groups.
The ON group consists of those controllers that are currently ON and will
provide under-
frequency response. The OFF group consists of those controllers that are OFF
and will provide
over-frequency response. Supervisory coordinator 806 then calculates the total
aggregated
power of each group, Pm and selects the desired droop value R for each group
based on the
corresponding magnitude ofp. This is illustrated in FIG. 9.
[0103] FIG. 9 shows a graph 900 of power vs. frequency. Desired droop R is
calculated as the
change in frequency divided by change in power. As an example, for an
aggregated amount of
power 902 ( p max), a horizontal line is determined to a point 904 on the
desired droop curve. A
vertical line is then determined down to identify the corresponding boundary
frequency 906 (j2)
that indicates the end of the frequency range available for use as frequency
thresholds. A
deadband bound frequency 908 ( ) is also shown. In some examples, deadband
bound
frequency 908 is a fixed value, and in other examples, deadband bound
frequency 908 is adjusted
periodically (and in some examples every control period) based on historical
frequency events,
grid performance, or other factors. For different values of p mwõ the desired
droop curve can
similarly be used to identify a boundary frequency.
[0104] Returning now to FIG. 8, supervisory coordinator 806 communicates
information to
individual controllers 808, 810, and 812 based on the aggregated power
information. In some
examples, supervisory coordinator 806 determines the frequency range(s) from
which frequency
thresholds can be selected and communicates the range(s) to controllers 808,
810, and 812.
Controllers 808, 810, and 812 then select frequency thresholds from the ranges
and monitor the
- 26 -
CA 3027776 2018-12-17
JBF/Jbf 23-96246-05 12/04/18 30797-E CIP FILED VIA EFS ON JULY 10, 2018
grid locally. The boundary frequency (e.g., f2 from FIG. 9) can be
communicated, and in some
examples, the deadband bound frequency is also communicated. In a periodic
update example,
supervisory coordinator 806 receives current power information, determines new
frequency
ranges (e.g., as illustrated in FIG. 9), and communicates the new ranges back
to controllers 808,
810, and 812. Controllers 808, 810, and 812 continue to operate autonomously,
but each control
period the controllers receive an updated frequency range and select a new
frequency threshold
from the updated range.
[0105] In other examples, supervisory coordinator 806 both determines the
frequency range(s)
and (e.g., randomly) selects frequency thresholds from the range(s) and
communicates the
selected thresholds to individual controllers. Supervisory coordinator 806 can
account for the
power of the loads associated with the controllers. For example, frequency
thresholds can be
assigned to particular controllers based on the associated power of the load
to help maintain a
linear response.
[0106] In decentralized hierarchical arrangement 800, by determining f2
indirectly through the
selection of R (e.g., as shown in FIG. 9), the maximum frequency deviation
responded to
becomes dependent on the penetration level of controllers, which effectively
overcomes the issue
of excessive response under high controller penetration. In some examples,
multiple supervisory
coordinators are used, each coordinator supervising a feeder, substation, or
other grid unit. In
other examples, a single supervisory coordinator is used for the entire grid.
[0107] Decentralized hierarchical arrangements were tested using the IEEE 16-
machine 68-bus
test system. The system parameters were taken from the data files that come
with the Power
System Toolbox (PST) distribution. The total load in the system was 18,333.90
MW with
5,039.00 MW in area 4 and 7,800.95 MW in area 5. The controllers are selected
to be electric
water heaters, which are evenly distributed among area 4 and 5. The response
time delay Thu and
Tb were selected to be 0.4 seconds, while the release time delay T: and T,
were randomly
chosen between two and three minutes.
[0108] Two example scenarios were investigated. In the first scenario, load
bus 7 was tripped to
create an over-frequency event. Two different penetration levels of
controllers ( 400 MW and
2700 MW) were simulated. A plot of rotor speed responses indicates that the
decentralized
control strategy (without a supervisory coordinator) greatly improves the
primary frequency
response when the penetration level of controllers is low. However, as the
penetration level
- 27 -
CA 3027776 2018-12-17
= JBF/jbf 23-96246-05
12/04/18 30797-E CIP FILED VIA EFS ON JULY 10, 2018
increases, excessive response from controllers negatively impacts the system
response when the
penetration level is high. By taking a hierarchical decentralized control
approach to controllers
under high penetration, the excessive response was effectively avoided through
the coordination
of the supervisory coordinator.
[0109] In the second scenario, generator G1 was tripped to create an under-
frequency event and
repeat the same simulation scenarios as the first scenario. Simulation results
indicate a similar
advantage (as in the first scenario) of hierarchical decentralized control
over a decentralized
control strategy without supervision.
[0110] FIG. 10 illustrates an example method 1000 of managing frequency
response in an
electrical power distribution system. Method 1000 can be performed, for
example, by a
supervisory coordinator such as supervisory coordinator 806 of FIG. 8. In
process block 1002,
power information is received for a plurality of grid-connected electrical
devices. The power
information can include a power load rating (e.g., in kWh) and can also
include an on-or-off
status. Power information can be reported by individual controllers in
response to a request from
a supervisory coordinator or reporting can be initiated by the individual
controllers (e.g.,
periodically). The received power information is aggregated in process block
1004.
[0111] Based on the aggregated power information and a target power-frequency
curve, one or
more frequency ranges from which frequency thresholds can be selected for the
respective grid-
connected electrical devices are determined in process block 1006. For a
respective grid-
connected electrical device, the frequency threshold is a grid frequency at
which the grid-
connected electrical device is automatically turned off or turned on by an
associated frequency-
responsive load controller. The target power-frequency curve can be a desired
droop or droop-
like response as illustrated in FIG. 9. In some examples, process block 1006
further comprises
determining an under-frequency range from which curtailing frequency
thresholds can be
selected and determining an over-frequency range from which rising frequency
thresholds can be
selected.
[0112] In process block 1008, at least one of (i) the one or more frequency
ranges or (ii) one or
more selected frequencies within the one or more frequency ranges are
transmitted to the
respective frequency-responsive load controllers associated with the
respective grid-connected
electrical devices. In some examples, the receiving, aggregating, and
transmitting are performed
periodically (e.g., every 5, 10, 15, 30, or 60 mm, etc.). The frequency ranges
or selected
frequencies transmitted in process block 1008 can be transmitted over a
computer network, such
- 28 -
CA 3027776 2018-12-17
JBF/jbf 23-96246-05 12/04/18 30797-E ClP FILED VIA EFS ON JULY 10, 2018
as the Internet, over a cellular network, using PLC, or through other
approaches from a
supervisory coordinator to the individual frequency-responsive load
controllers associated with
the grid-connected electrical devices.
[0113] In some examples in which multiple supervisory coordinators are used,
after collecting
power ratings of controllers at the beginning of each control period,
supervisors located at
different feeders can use information discovery approaches to determine the
total power of
online controllers in the system. For example, the supervisors can run
consensus algorithms by
exchanging the current power of online controllers under their supervision
with neighboring
supervisors. Once the total power of online controllers is known, each
supervisor can determine
a new range accordingly and then broadcast the range to the supervised
controllers, which can
randomly pick a frequency threshold from the new range.
Additional Examples
[0114] Various market mechanisms can be used to further penetration of
frequency-responsive
load controllers into the grid. In such examples, a supervisory coordinator
can collect additional
information from the controllers, including device states other than on/off
and/or a "willingness"
or priority factor. The willingness factor can be based on an expressed user
preference (e.g., an
amount or relative amount of device management the user is willing to
tolerate) or it can be
based on device states. For example, if a water heater is nearly finished
returning to a set
temperature, which indicates that a person using the water heater may not be
inconvenienced
much by the water heater being turned off to manage grid frequency, a higher
willingness factor
can be sent to the supervisory coordinator. Conversely, if a water heater has
just started bringing
the temperature of the water up from a low value toward a target, a lower
willingness factor can
be sent. Controllers with a high willingness factor can be used before other
controllers to
manage frequency response. The willingness factor can be, for example, a
number between 1
and 10, 1 and 100, 0 and 1, a letter between "a" and "z," etc.
[0115] Rewards can be provided to users based on the willingness factor. In
examples in which
the willingness factor is based on a device state, a lower reward can be
provided to a user with a
high device-based willingness factor. Continuing the water heater example, if
the water heater
were about to shut off anyway, allowing the controller to shut the device off
is not highly
rewarded, whereas if the water heater were just beginning to heat, shutting
off the water heater
may be a large inconvenience to a user, and allowing the controller to shut
the device off is
rewarded. The willingness factor reflects these device states and is used to
adjust how much
- 29 -
CA 3027776 2018-12-17
= JBF/jbf 23-96246-05
12/04/18 30797-E CIP FILED VIA EFS ON JULY 10, 2018
reward a user receives. As another example, if a user specifies a high
willingness to have the
controller shut off the user's device regardless of state, then the user's
device can be shut off
before others, and if the current device state is one that would not normally
be rewarded highly,
the user can still receive a larger reward for effectively volunteering via
the user's expressed
preference. Rewards can be, for example, usage or bill credits or lower kWh
rates.
[0116] The described market mechanisms can be implemented as a central
clearing mechanism
using two independent double-auction markets of, for example, five or ten
minutes (ON-to-OFF
and OFF-to-ON).
Additional Examples of the Disclosed Technology
[0117] In another embodiment, each grid-connected appliance can be assigned a
frequency
threshold based on a fitness metric. The fitness metric can be based on a
particular appliance's
ability to provide a frequency response (e.g., turning off in an under-
frequency event or turning
on in an over-frequency event). Then, each grid-connected appliance can be
ordered or assigned
a priority based on their assigned fitness metrics and frequency thresholds
can be assigned based
on this ordering. That is, appliances that can most readily provide a
particular frequency
response can be assigned frequency thresholds closest to a target frequency
value and appliances
that are less readily able to provide a frequency response can be assigned
frequency thresholds
further from the target frequency. Thus, if an over-frequency or under-
frequency event occurs,
the appliances that can most readily provide an appropriate frequency response
will do so before
other appliances that cannot as readily provide a frequency response. As such,
the overall
performance of the power grid can be improved.
[0118] FIG. 11 shows a block diagram of a hierarchical system 1100 for
implementing a power
grid in which frequency thresholds are assigned based on fitness metrics, in
accordance with
disclosed technology as described herein. The system 1100 comprises a grid
operator 1110, a
plurality of load aggregators 1120, a plurality of resource controllers 1130,
and a plurality of
sensors 1140, local device controllers 1150, and loads 1160. The grid operator
1110 can provide
power to the system and communicates with the plurality of load aggregators
1120 as disclosed
herein. Each load aggregator 1120 can communicate with the grid operator 1110
and with a
plurality of resource controllers 1130 as disclosed herein. In the illustrated
example, each load
aggregator 1120 can communicate with a number of resource controllers 1130
within one
distribution sphere (about 1,000 houses). In other examples, each load
aggregator 1120 can
communicate with any number of resource controllers 1130. Each resource
controller 1130 can
- 30 -
CA 3027776 2018-12-17
JBF/jbf 23-96246-05 12/04/18 30797-E CIP FILED VIA EFS ON JULY 10, 2018
communicate with a local device controller 1150, a load 1160 (e.g., a grid-
connected appliance),
and one or more sensors 1140 as disclosed herein. Each local device controller
1150 can receive
sensor data and can control one load 1160.
[0119] Each load 1160 can be a grid-connected electrical appliance such as an
air conditioner or
a water heater. Each load 1160 can be controlled by a local device controller
1150 using known
techniques. Each local device controller 1150 can receive measurement data
from one or more
sensors 1140 (e.g., temperature readings) to control the load 1160. In an
example where the load
is an air conditioner, a user can set a temperature setpoint. The local device
controller 1150 can
then read temperature data from the sensors 1140 and turn the load 1160 on
when the measured
temperature rises above the setpoint and turn the load off when the measured
temperature falls
below the setpoint. In addition, the local device controller 1150 can follow
supervisory control
from the resource controller 1130. The local device controller 1150 can
transmit information to
the resource controller 1130 including whether the load 1160 is in an on or
off state at a
particular time.
[0120] FIG. 12 shows a block diagram of an example resource controller 1130.
In the illustrated
example, the resource controller 1130 can comprise sensor data receiver 1200,
a load state
receiver 1210, a profile transmitter 1220, a frequency threshold receiver
1230, a grid frequency
monitor 1240, and a load controller 1250. As explained above, each resource
controller 1130
can receive data from one or more sensors 1140 associated with a particular
load 1160 and can
communicate with the local device controller 1150 associated with the load to
control the
operation of the load. In the illustrated example of FIG. 12, the sensor data
receiver 1200 can
receive data from the sensor 1140. In the illustrated example, the load state
receiver 1210 can
receive information from the local device controller 1150 as to the
operational state of the load
1160 at a particular time (e.g., whether the load is on or off). In some
examples, the load state
receiver 1210 can receive load state information directly from the load 1160
rather than from the
local device controller 1150. In the illustrated example, profile transmitter
1220 can transmit the
data received by the sensor data receiver 1200 and the load state receiver
1210 to the load
aggregator 1120 associated with the resource controller 1130. This data
constitutes a use profile
(sometimes referred to herein as a load profile) of the load 1160 that the
load aggregator 1120
can use to determine a fitness metric and assign a frequency threshold for the
load 1160, as
discussed in further detail below. The frequency threshold receiver 1230 can
receive a frequency
threshold for the load 1150 from the load aggregator 1120. The grid frequency
monitor 1240 can
- 31 -
CA 3027776 2018-12-17
JBF/jbf 23-96246-05 12/04/18 30797-E CIP FILED VIA EFS ON JULY
10, 2018
= monitor the grid frequency and determine if the grid frequency is above
or below the frequency
threshold received from the load aggregator 1120. The load controller 1250 can
communicate
with the local device controller 1150 to control the operation of the load
1160. Specifically, the
load controller 1250 can send a signal to the local device controller 1150 to
cause the load 1160
to turn off or deactivate if the detected grid frequency is below the assigned
frequency threshold
(in an under-frequency response) or the load controller 1250 can send a signal
to the local device
controller 1150 to cause the load 1160 to turn on if the detected grid
frequency is above the
assigned frequency threshold (in an over-frequency response).
[0121] FIG. 13 shows a block diagram of an example load aggregator 1120. The
load
aggregator 1120 is responsible for aggregating the data regarding the
operation of each load 1160
within its purview (e.g., within one distribution sphere) and assigning an
appropriate frequency
threshold for each such load. In the illustrated example, the load aggregator
1120 can comprise a
load profile receiver 1300, a fitness metric calculator 1310, a frequency
threshold assigner 1320,
a frequency threshold transmitter 1330, a power requirement transmitter 1340,
and a power
allocation receiver 1350. In the illustrated example, the load profile
receiver 1300 receives data
from each resource controller 1130 that the load aggregator 1120 is
responsible for. This can
include all or any subset of the data received by the resource controller 1130
from one or more
sensors 1140, a local device controller 1150, and the associated load 1160.
The fitness metric
calculator 1310 calculates a fitness metric for a resource controller 1130 and
an associated load
1160 using the methods disclosed herein. The frequency threshold assigner 1320
assigns a
frequency threshold for a resource controller 1130 based on the calculated
fitness metric. The
frequency threshold transmitter 1330 transmits the assigned frequency to the
appropriate
resource controller 1130. The power requirement transmitter 1340 determines
the total power
required to operate each of the loads 1160 associated with the load aggregator
1120 based on the
data received by the load profile receiver 1300 and transmits this power
requirement to the grid
operator 1110. The power allocation receiver 1350 receives from the grid
operator 1110 an
allocated power value that the load aggregator 1120 can operate at.
[0122] In the illustrated example, the grid operator 1110 can analyze the
available flexibility
across the network, along with the current network status (e.g., generation
and load forecast,
measurements from power management units, topology, etc.) to optimally
allocate control
capacities from the responsive load ensembles. The grid operator 1110 then
transmits an
allocated capacity to each of the load aggregators 1120.
- 32 -
CA 3027776 2018-12-17
JBF/jbf 23-96246-05 12/04/18 30797-E CIP FILED VIA EFS ON JULY 10, 2018
[0123] FIG. 14 shows a frequency response profile 1400 for a power grid system
such as system
1100. As the grid frequency drops from a target value, the power consumption
should drop
linearly as shown in the solid line. However, in an actual system, the
response will more closely
resemble the dashed line. In the example of FIG. 14, each grid-connected
device is assigned a
frequency threshold and each device shuts off when the grid frequency drops
below its assigned
frequency threshold. This can be seen in the dashed line of FIG. 14 where
power consumption
drops each time a device shuts off at grid frequencies of (..4, (.43,2, 64,
etc. However, not all
devices are able to readily shut off in response to the grid frequency hitting
the device's assigned
frequency threshold. For example, if the device is not in an on state when the
frequency
threshold is hit, the device cannot turn off Furthermore, different devices
may have different
time delays in responding to a frequency threshold being reached. Accordingly,
assigning
frequency thresholds to grid-connected devices based on each device's ability
to respond to a
frequency request, using the disclosed technology, can help the actual
frequency response curve
to more closely resemble the target response curve of FIG. 14, thereby
improving system
performance.
[0124] In order to assign appropriate frequency thresholds to each grid-
connected load 1160,
each load aggregator 1120 can determine the ability of each load 1160 to
respond to a frequency
request (e.g., turn off in an over-frequency event or turn on in an under-
frequency event). One
approach to accomplish this task would be for the load aggregators 1120 to
continuously monitor
the operating state of each device 1160. Although this approach can help
achieve this goal, such
continuous monitoring can have high telemetry requirements and can have
potential privacy
concerns for the device owners. Instead, a more viable option is to
periodically acquire and
update the state of each device at the start of fixed control time windows.
This information can
then be used to estimate the availability of the device to respond to a
frequency event during the
control window.
[0125] In the illustrated example, the load aggregators 1120 can determine a
fitness metric for
each load or device 1160. This fitness metric is a measure of the device's
ability to response to a
frequency event (e.g., turn off in an under-frequency event or turn on in an
over-frequency
event). The devices 1160 can then be ordered based on their fitness metrics
and assigned
frequency thresholds based on the fitness metrics (e.g., the higher fitness
metric a device has, the
closer its frequency threshold will be to the target grid frequency). The
fitness metric for a load
1160 can be determined based on information received by the resource
controller 1130
- 33 -
CA 3027776 2018-12-17
JBF/jbf 23-96246-05 12/04/18 30797-E CIP FILED
VIA EFS ON JULY 10, 2018
associated with the device, as discussed above, as well as based on previous
performance of a
particular device 1160 in response to a frequency request. The determination
of fitness metrics is
discussed in further detail below.
[0126] As disclosed herein, fitness is a qualitative measure of the ability of
a controllable load to
successfully respond to a certain ancillary service request (e.g., a frequency
response).
Specifically, the fitness of a device i to respond to a request k can be
denoted by a scalar 71
which can have a value between 0 and 1 and quantifies how likely the device i
is to successfully
complete the request k over some time window. This metric of fitness can
depend on a variety of
factors such as device dynamics, response delays, rate of failure to respond
to the request, and
the type of service request. In a simplified form, the fitness can be composed
of two component
metrics, availability for response and quality of response.
[0127] The availability metric of a device i for response to a service request
k can be denoted by
avati,t
Trk . This metric can have a value between 0 and 1 and can represent the
probability that the
device is available to respond to the particular service request over some
time (e.g., the
probability that the device is on or active when a request is made to turn the
device off). The
quality metric of a device i for response to service request k can be denoted
by rrrt . This
metric can have a value between 0 and 1 and can represent the probability that
the device, when
available, completes the service request successfully. The overall fitness
metric can be a product
1,z quaLs
of the availability metric and the quality metric as follows: 71-/!, = Trk
[0128] The quality metric can depend on a variety of different factors
including sensor and
actuation time-delays, as well as sensor and actuators failures. In a
simplified form, the
performance degradation due to time-delays can be modeled into the quality
metric as
qua1,1
it k
exp(¨/3t) , where t is an appropriate scaling factor and tl,k is an estimated
time-
delay of the device in responding to the particular service request. In some
examples, the
estimated time-delay can be based on the time delay in responding to previous
such requests. A
total failure of the device to respond to the request would be captured by the
limiting case
,k -4 +Up while tk = 0 would refer to a success rate of 1. In some examples,
the quality
metric is assumed equal to 1 for all devices. In other examples, the quality
metric of a device for
- 34 -
CA 3027776 2018-12-17
= JBF/jbf 23-96246-05
12/04/18 30797-E CIP FILED VIA EFS ON JULY 10, 2018
, .
. a particular service is estimated by monitoring the performance of
the device in response to
similar requests over time.
[0129] The availability metric for a device can be determined based on how
likely a device is to
be available for a particular service. In the illustrated example, the
availability metric of a device
is the probability that the device is able to respond to a frequency request.
That is, for an under-
frequency event, the availability metric is equal probability that the device
is turned on when the
event happens, and thus is available to be turned off.
[0130] For an over-frequency response, the availability metric is equal to the
probability that the
device is turned off when the event happens, and thus is available to be
turned on. Assuming
that the probability of an under-frequency event happening at any time t is
uniformly distributed
within an interval [to, tf], the availability metric of device for under-
frequency response
(denoted by the subscript "resp-") can be obtained as:
iravall'' .Pr{device-i is 'on' when under-frequency happens}
resp-
t F
--,-- Pr{device-i is 'on' at time r} = fresp(r) dr
it'
o
tf si (
=7) Von
_____________________________________ d'r= ____________________ (9)
fr) tf ¨ to tf ¨ to
where, s' 0 E 10,11 represents the operational state of the device, taking
value 0 in the "off'
state and 1 in the "on" state; to' is the length of time the device spends in
the "on" state during
the control window [to. tf]; and &..p_ 0 is the uniform probability density
function at the time
of occurrence of the under-frequency event. With the knowledge of the internal
states of each
the devices 1150, and some forecast of the external conditions based on sensor
data, it is possible
to estimate Trrag;L: for each device at the start of each control period.
Using similar arguments,
the availability factor for an over-frequency response (denoted by the
subscript "resp+") over an
control window [to, tf] could be calculated as:
t'
avail,i of f = (10)
irresp+
t f ¨ to
where to, tf 1 is the length of time the device spends in the "off' state
during the control window
{to, tf}. Discussed below are some examples of how these availability factors
can be computed
- 35 -
CA 3027776 2018-12-17
JBF/jbf 23-96246-05 12/04/18 30797-E CIP FILED VIA EFS ON JULY
10, 2018
. , .
based on information on the current states, device parameters, and forecasts
of end-usage and
external conditions.
[0131] In one example, the devices 1150 can be an ensemble of N air-
conditioning (AC) loads.
Each device dynamics can be represented by,
t(t) _ (T(t)¨ To(t)) II p(t)
(11a)
C 1? C .
{ 0, if T(t) < i],et ¨ 8T/2
p(t) = P, if T(t) > Lot + OT/2 , (1 1 b)
p(t), otherwise
where T(t) is the room temperature; p(t) E {0,P} represent the power draw of
the AC; Tn(f)
denotes the outside air temperature; and C, R, it are the device parameters
representing the room
thermal resistance, thermal capacitance and the load efficiency, respectively.
T is the
temperature set-point and ST represents the width of the temperature
hysteresis deadband. Let us
assume that, at the start of an control window [to, rib the room temperature
T(to) and the
operational state of the AC (in the form of power consumed p(to) are known to
the resource
controller. If the outside air temperature is constant throughout the control
window, the
dynamics can be solved to compute the time t:õf f an initially "on" device
spends before turning
"off," and the time tUf an initially "off" device spends before turning "on"
as:
tg f = CR log alto) ¨ 70(t)) + iiPR -
(12a)
T(to) ¨ T(t)
toff= C I? log (12b)
_Tsft + 6172 ¨ Ta(t) =
The time a device spends in the 'on' and off state during the control window
is given by:
min (t 1 ¨to , egif) , 'on' at 7'0
ton ¨ (13a)
ma.x (o. tf ¨to ¨to7f) . 'off' at to
toff = if ¨ to ¨ toõ . (13b)
[0132] In another example, the devices 1160 can be an ensemble of N electric
water-heating
(EWH) loads. The water temperature dynamics of an EWH can be modeled using a
"one-mass"
thermal model which assumes that the temperature inside the water-tank is
spatially uniform
(valid when the tank is nearly full or nearly empty):
- 36 -
CA 3027776 2018-12-17
. JBF/jbf 23-96246-05 12/04/18 30797-E CIP FILED VIA EFS ON JULY
10, 2018
' =
. i(t) = ¨a(t) T(t) + b(s(t), t) , (14)
1
where, a(t) := ¨ (th(t) Cr + W) ,
Sr- b(s(t),t) := .,..1 (s(t) P + ih(t)C,Tin(t) + W Ta(t)) =
7', denotes the temperature of the water in the tank, and s(t) denotes a
switching variable which
determines whether the EWH is drawing power (s(t) = 1 or "on") or not (s(t) =
0 or "off'). The
state of the EWH ("on" or "off') is determined by the switching condition:
0. if Tiv(t) > Tõt 5172
se). 1, if T(t) < Tset ¨ 6772 , (15)
{
s(t) , otherwise
where 7'.. is the temperature set-point of the EWH with a deadband width of
ST. Let us assume
that, at the start of an control window [to, tid, the room temperature,
Tw(to), and the operational
state of the EWH, s(to), are known to the resource controller. If the
exogenous parameters are
unchanged throughout the control window, then the dynamics can be solved to
compute the time
t:fr, f an initially "on" device spends before turning "off," and the time t
f; 1 an initially "off"
device spends before turning "on" as:
1
= ¨a(t) Ty, (to) + b(1,t) -
tad f ¨ log
' a(t) [ --a(t) (Tsa + 6772) h(), t)_ ' (16a)
1 ¨a (t) Ti, (to) + b(0,t)
t" = log __________________ 16
"f f a(t) [¨a(t) (T, et ¨ oT 12) + b(0 ( b) ,
t) _ =
The time the device spends in the "on" and "off' state during the control
window as:
min (t1 ¨to. tgi ) , 'on' at to
ton =---- (17a)
max (a. t f ¨ 40 ¨ ff)1} f) , 'off' at to
toff = tf ¨ to ¨ to,n, . (17b)
[0133] Using the above discussed techniques, at the start of the control
window (t = to), the
fitness values of each device 1150 in the population are computed for any
particular service k
(e.g., a frequency response). Based on the computed fitness values, TtViE fl,
2, ...,N}, all the
devices 1150 are prioritized in an order fdl, d7, d3, ... , d N} for
consideration of commitment to
service k, such that
d3 d NT
Tr ki > IT k- > 7 k . = = > 7rk' = (18)
-37 -
CA 3027776 2018-12-17
.03F/jbf 23-96246-05 12/04/18 30797-E CIP FILED VIA EFS ON JULY 10, 2018
Then, using this ordering, frequency thresholds (for primary frequency
response) are assigned,
such that devices with frequency thresholds closer to the nominal frequency
are assigned to
higher priority (e.g., 'fitter') devices. After assigning the frequency
thresholds, a subset of the
devices 1160 can be selected, based on the priority order, such that their
aggregate power rating
equals (within some tolerable error, Ep) the target response capacity Apr'',
e.g. choose the
smallest m E {1,2, such that:
rn
Apmax E fp (19)
Furthermore, the probability that all the devices responding to the service
request is given by,
771
Pr{ 'success' } = H (20)
Consequently, we can also compute the maximal response capacity that the
aggregation of
devices can commit to with a probability of success 1, which is defined as
follows. The maximal
capacity that an aggregation can successfully (e.g. with probability=1) commit
for any service-k
is denoted by {
]cap k and is given by
[Aprak := pdi pd2 (22)
such that
= WI E {12, ...,n} and ITcia+1. < 1
[0134] Control performance can be evaluated against a metric termed as the
reserve margin
variability target (RMVT) which is expressed as the following,
RMVT :=
total response provided on request
1
total response requested
There are several sources of uncertainties that may affect the control
performance (and
contribute to the RMVT), such as forecast errors, modeling uncertainties and
faults in sensors.
Of particular interest to this work are the uncertainties due to control
parameters, such as the
discrete allocation of frequency thresholds and sampling time delays.
[0135] As can be seen from Fig. 14, due to the discrete power consumption of
the devices and
due to finite number of devices committing to provide the frequency response,
at any frequency
- 38 -
CA 3027776 2018-12-17
JBF/jbf 23-96246-05 12/04/18 30797-E CIE FILED VIA EFS ON JULY 10, 2018
value, the maximal deviation is given by the power rating of the largest
device that has
committed to the service. Using the threshold assignment logic disclosed
above, the relative
error in response (relative to the response capacity) due to discrete loads
can be given by,
,n,
(23)
Apmax pd,
This suggests that in order for the relative error in response to be less than
certain pre-specified
performance metric E, the committed aggregate capacity for response has to be
larger than
certain critical value, e.g.
max, Pt
RAIVT < c ¨> Ap"' > _________________________________ (24)
[0136] In general, the delay between a sensor measurement or service request
and the control
execution (or, actuation) can have multiple components, e.g. actuator delays
(td), and delays due
to finite sampling rate (At). The effective delay in response, therefore will
be given by max
(td, At). For simplicity, in the examples disclosed herein, the actuator delay
is assumed to be
negligible (td = 0), in order to consider only on the delay due to finite
sampling rate. FIG. 15
shows a first chart 1500 showing the change in response capacity air as a
function of frequency
and a second chart 1550 showing the change in frequency co(t) over time t. The
local sensor of
a device can detect that frequency co(t) at time t is lower than its assigned
frequency threshold
and therefore, according to the control logic above, turns "off' at the next
time instant t + At,
where At refers to the non-zero discrete sampling time. If the frequency
deviates further during
this time delay, there is a non-zero deviation, 8p, from the target frequency
response curve. For
small At, this error can be estimated as,
(w) DLe
6p ¨ = At (25a)
Ot
w(t)
6p At 3,3)
(25b)
______________________ Aprizaz (we, _ Ot
e.g. the relative error in response due to finite sampling rate is
proportional to the sampling time,
as well as the rate of change of frequency.
- 39 -
CA 3027776 2018-12-17
JBF/jbf 23-96246-05 12/04/18 30797-E CIP FILED VIA EFS ON JULY 10, 2018
SIMULATION RESULTS
[0137] In order to test the prioritized decentralized frequency response
algorithm, a random
collection of 1000 ACs and 1000 EWHs was generated. The limits for the
frequency response
were chosen as:
= 59.7 Hz and 59.995 Hz for under-frequency response, and
= 60.005 Hz and 60.3 Hz for over-frequency response.
Several frequency events were created in an IEEE 39-bus network, by injecting
disruptions via
changing the loads. FIG. 16 illustrates two such events, an over-frequency
response 1600 and an
under-frequency response 1650. Performance of the frequency response control
algorithm was
tested against these various frequency events (shifted in time as
appropriate).
[0138] FIGS. 17A and 17B illustrate how the target and achieved frequency
response curves
typically look like, simulated using 1000 EWHs in chart 1700 and 1000 ACs in
chart 1750. The
results are obtained for a 5 mm control window, with a sampling time of At = 1
s, while the
response capacity is set at 60% of the maximal capacity as defined above. It
is noted that, with
either type of the devices, the achieved response is fairly close to the
target response, with some
errors being observed for lower frequency deviations. This key observation can
be explained by
looking at the frequency events in FIG. 16. The rate at which the frequency
changes is high
when the frequency deviation is low (e.g. closer to the nominal value of 60
Hz) and gradually
decreases (due to damping effect by the generators) as the frequency deviates
further. This
suggests that the sampling time should be chosen sufficiently small for faster
frequency events.
[0139] FIG. 18A shows the response of the group of 1000 ACs (chart 1800) and
1000 EWHs
(chart 1820) in response to a cascading contingency where an initial
contingency (created by
load drop) leads to two subsequent under-frequency events. In the example of
FIGS. 18A and
18B, control was chosen as 5 mm. The net response magnitude achieved is 3.097
MW, which is
less than 0.2% of the target 3.103 MW, e.g. RMVT< 0.2%. It is noted that, the
achieved
response is able to track the target response curve always within 1 s delay.
[0140] Discrete allocation of frequency thresholds introduce certain error in
the response curve.
FIG. 19 is a chart 1900 that shows the error statistics (in the form of mean
RMVT) as the
committed capacity is varied between 1% and 120% of the maximal guaranteed
capacity, e.g. the
ratio of Ap' [Ap]a-P is plotted on the x-axis. Clearly below 20 % commitment (-
1 MW), the
error is high due to discrete allocation of resources, which steadies to <0.3%
(coming from
- 40 -
CA 3027776 2018-12-17
= JBF/jbf 23-96246-05
12/04/18 30797-E CIP FILED VIA EFS ON JULY 10, 2018
= sampling time) from over 20% up to 100%. Beyond 100% commitment, the
error increases
again due to unavailability of sufficient number of "fit" devices.
[0141] Finally Monte-Carlo simulations were run to test the algorithm under
various different
scenarios. With a fixed (but randomly generated) population of 1000 EWHs and
1000 ACs,
different scenarios were created by changing the initial operating condition,
the length of the
control window as well as the time when the frequency event happens. The RMT
level was
chosen to be 60% of the estimated maximal guaranteed capacity. In Table 2000
of FIG. 20, the
mean RMVT values for 6 different scenarios are presented. Across all these
scenarios, the
priority-based algorithm performs uniformly well with mean RMVT < 0.3%.
However, when
not using the priority-based algorithm, as shown in Table 2050 of FIG. 20, the
RIVIVT increases
and is sensitive to the length of the control window and when the time of
occurrence of the
event.
[0142] FIG. 21 is a flowchart 2100 depicting an example method of assigning
frequency
thresholds to grid-connected appliances. For example, the hardware discussed
above regarding
FIGS. 11 and 12 can be used to implement the illustrated method.
[0143] At process block 2102, the sensor data receiver 1200 of a resource
controller 1130
receives data from the sensor 1140 associated with the resource controller. In
the illustrated
example, the received sensor data is a temperature of the environment of the
load 1160. In other
examples, the sensor 1140 can provide other types of data regarding the
environment or
operation of the load 1160.
[0144] At process block 2104, the load state receiver 1210 of the resource
controller 1130
receives from the local device controller 1150 associated with the load 1160
the current state of
the load. In the illustrated example, the current state of the load can be
either on or off. In some
examples, the resource controller 1130 can receive time series power
consumption data from the
local device controller 1150 associated with the load 1160. In other examples,
the load state
receiver 1210 can receive other information regarding the state of the load
1160. In the
illustrated example, each resource controller 1130 of the system 1100 receives
sensor data and
load state data at the beginning of each control time window. In other
examples, this data can be
received at other intervals.
[0145] At process block 2106, the profile transmitter 1220 transmits the data
received by the
sensor data receiver 1200 to the load aggregator 1120. This data represents a
profile of the load
1160 that the load aggregator 1120 can use to determine a fitness metric.
After this data is sent,
- 41 -
CA 3027776 2018-12-17
= JBF/Jbf 23-96246-05
12/04/18 30797-E CIP FILED VIA EFS ON JULY 10, 2018
=
=
the load profile receiver 1200 receives this data from the resource controller
1130 and each
resource controller under its control.
[0146] At process block 2108, the fitness metric calculator 1310 of the load
aggregator 1120
calculates a fitness metric for each load 1160 under its control based on the
profile data received
from the profile transmitter 1220 of each resource controller 1130. The
fitness metric calculator
1310 can calculate a fitness metric using the techniques described above. The
calculated fitness
metric for a particular load 1160 can represent the probability that the load
will be available to
respond to a frequency request during the control time window.
[0147] At process block 2110, the frequency threshold assigner 1320 can assign
frequency
thresholds for each load 1160 under its control. This can be accomplished by
ordering the loads
based on the fitness metric calculated by the fitness metric calculator 1310
for each load and
assigning a frequency threshold accordingly. As discussed above, the loads
1160 with higher
fitness metrics can be assigned frequency thresholds closer to the target grid
frequency and loads
with lower fitness metrics can be assigned frequency thresholds further from
the target grid
frequency.
[0148] At process block 2112, the frequency threshold transmitter 1330 can
transmit an assigned
frequency threshold to each resource controller 1130.
[0149] FIG. 22 is a flowchart 2200 depicting another example method of
assigning frequency
thresholds to grid-connected appliances. At process block 2202, the fitness
metric calculator
1210 of the load aggregator 1120 determines a fitness metric for a grid-
connected electrical
device using the methods described above and assigns the determined fitness
metric to the
device. At process block 2204, the frequency threshold assigner 1220 assigns a
frequency
threshold to the device using the techniques described above. At process block
2206, the
frequency threshold transmitter 1230 sends the assigned frequency to the
device.
[0150] FIG. 23 is a flowchart 2300 depicting an example method of operating
the example
resource controller 1130. At process block 2302, the sensor data receiver 1300
and/or the load
state receiver 1310 of the resource controller 1130 receive information from a
grid-connected
electrical device, such as data from one or more sensors connected to the
device or information
about the operational state of the device. At process block 2304, the profile
transmitter 1320
sends a use profile based on the information received by the sensor data
receiver 1300 and the
load state receiver 1310 to the load aggregator 1120.
- 42 -
CA 3027776 2018-12-17
JBF/jbf 23-96246-05 12/04/18 30797-E CIP FILED VIA EFS ON JULY 10, 2018
[0151] At process block 2306, the frequency threshold receiver 1330 receives a
frequency
threshold from the load aggregator 1120. At process block 2308, the grid
frequency monitor
1340 monitors the frequency of the electrical grid that the device is
connected to in order to
determine a current grid frequency. At process block 2310, the load controller
1350 can update
the operational state of the device based on the frequency threshold and the
grid frequency. For
example, in an under-frequency event, the load controller 1350 can deactivate
the device if the
grid frequency is below the frequency threshold. Or, in an over-frequency
event, the load
controller 1350 can activate the device if the grid frequency is above the
frequency threshold.
Example Computing Environments
[0152] FIG. 24 depicts a generalized example of a suitable computing system
2400 in which the
described innovations may be implemented. The computing system 2400 is not
intended to
suggest any limitation as to scope of use or functionality, as the innovations
may be implemented
in diverse general-purpose or special-purpose computing systems.
[0153] With reference to FIG. 24, the computing system 2400 includes one or
more processing
units 2410, 2415 and memory 2420, 2425. In FIG. 24, this basic configuration
2430 is included
within a dashed line. The processing units 2410, 2415 execute computer-
executable instructions.
A processing unit can be a general-purpose central processing unit (CPU),
processor in an
application-specific integrated circuit (ASIC), or any other type of
processor. In a multi-
processing system, multiple processing units execute computer-executable
instructions to
increase processing power. For example, FIG. 24 shows a central processing
unit 2410 as well
as a graphics processing unit or co-processing unit 2415. The tangible memory
2420, 2425 may
be volatile memory (e.g., registers, cache, RAM), non-volatile memory (e.g.,
ROM, EEPROM,
flash memory, etc.), or some combination of the two, accessible by the
processing unit(s). The
memory 2420, 2425 stores software 2480 implementing one or more innovations
described
herein, such as curtailing frequency threshold selector 602 and rising
frequency threshold
selector 608 of FIG. 6, in the form of computer-executable instructions
suitable for execution by
processing units 2410 and/or 2415. A programmable logic device (PLD), such as
an FPGA, can
execute programmable-logic-device-executable instructions. An example of
programmable-
logic-device-executable instructions is the configuration bits for programming
the PLD (such as
a ".bit" file for a Xilinx0 FPGA).
[0154] A computing system may have additional features. For example, the
computing system
2400 includes storage 2440, one or more input devices 2450, one or more output
devices 2460,
- 43 -
CA 3027776 2018-12-17
JBF/jbf 23-96246-05 12/04/18 30797-E CIP FILED VIA EFS ON JULY 10, 2018
and one or more communication connections 2470. An interconnection mechanism
(not shown)
such as a bus, controller, or network interconnects the components of the
computing system
2400. Typically, operating system software (not shown) provides an operating
environment for
other software executing in the computing system 2400, and coordinates
activities of the
components of the computing system 2400.
[0155] The tangible storage 2440 may be removable or non-removable, and
includes magnetic
disks, magnetic tapes or cassettes, CD-ROMs, DVDs, or any other medium which
can be used to
store information and which can be accessed within the computing system 2400.
The storage
2440 stores instructions for the software 2480 implementing one or more
innovations described
herein.
[0156] The input device(s) 2450 may be a touch input device such as a
keyboard, mouse, pen, or
trackball, a voice input device, a scanning device, or another device that
provides input to the
computing system 2400. For video encoding, the input device(s) 2450 may be a
camera, video
card, TV tuner card, or similar device that accepts video input in analog or
digital form, or a CD-
ROM or CD-RW that reads video samples into the computing system 2400. The
output
device(s) 2460 may be a display, printer, speaker, CD-writer, or another
device that provides
output from the computing system 2400.
[0157] The communication connection(s) 2470 enable communication over a
communication
medium to another computing entity. The communication medium conveys
information such as
computer-executable instructions, audio or video input or output, or other
data in a modulated
data signal. A modulated data signal is a signal that has one or more of its
characteristics set or
changed in such a manner as to encode information in the signal. By way of
example, and not
limitation, communication media can use an electrical, optical, RF, or other
carrier.
[0158] The innovations can be described in the general context of computer-
executable
instructions, such as those included in program modules, being executed in a
computing system
on a target real or virtual processor. Generally, program modules include
routines, programs,
libraries, objects, classes, components, data structures, etc. that perform
particular tasks or
implement particular abstract data types. The functionality of the program
modules may be
combined or split between program modules as desired in various embodiments.
Computer-
executable instructions for program modules may be executed within a local or
distributed
computing system.
- 44 -
CA 3027776 2018-12-17
JBF/jbf 23-96246-05 12/04/18 30797-E CIP FILED VIA EFS ON JULY 10, 2018
[0159] The terms "system" and "device" are used interchangeably herein. Unless
the context
clearly indicates otherwise, neither term implies any limitation on a type of
computing system or
computing device. In general, a computing system or computing device can be
local or
distributed, and can include any combination of special-purpose hardware
and/or general-
purpose hardware with software implementing the functionality described
herein.
[0160] For the sake of presentation, the detailed description uses terms like
"determine" and
"use" to describe computer operations in a computing system. These terms are
high-level
abstractions for operations performed by a computer, and should not be
confused with acts
performed by a human being. The actual computer operations corresponding to
these terms vary
depending on implementation.
[0161] Although the operations of some of the disclosed methods are described
in a particular,
sequential order for convenient presentation, it should be understood that
this manner of
description encompasses rearrangement, unless a particular ordering is
required by specific
language set forth below. For example, operations described sequentially may
in some cases be
rearranged or performed concurrently. Moreover, for the sake of simplicity,
the attached figures
may not show the various ways in which the disclosed methods can be used in
conjunction with
other methods. Additionally, the description sometimes uses terms like
"provide" or "achieve"
to describe the disclosed methods. These terms are high-level descriptions of
the actual
operations that are performed. The actual operations that correspond to these
terms may vary
depending on the particular implementation and are readily discernible by one
of ordinary skill in
the art having the benefit of the present disclosure.
[0162] Any of the disclosed methods can be implemented as computer-executable
instructions or
a computer program product stored on one or more computer-readable storage
media and
executed on a computing device (e.g., any available computing device,
including smart phones
or other mobile devices that include computing hardware). Computer-readable
storage media are
any available tangible media that can be accessed within a computing
environment (e.g., one or
more optical media discs such as DVD or CD, volatile memory components (such
as DRAM or
SRAM), or nonvolatile memory components (such as flash memory or hard
drives)). By way of
example and with reference to FIG. 24, computer-readable storage media include
memory 2420
and 2425, and storage 2440. The term computer-readable storage media does not
include signals
and carrier waves. In addition, the term computer-readable storage media does
not include
communication connections (e.g., 2470).
- 45 -
CA 3027776 2018-12-17
JBF/jbf 23-96246-05 12/04/18 30797-E CIP FILED VIA EFS ON JULY 10, 2018
[0163] Any of the computer-executable instructions for implementing the
disclosed techniques
as well as any data created and used during implementation of the disclosed
embodiments can be
stored on one or more computer-readable storage media. The computer-executable
instructions
can be part of, for example, a dedicated software application or a software
application that is
accessed or downloaded via a web browser or other software application (such
as a remote
computing application). Such software can be executed, for example, on a
single local computer
(e.g., any suitable commercially available computer) or in a network
environment (e.g., via the
Internet, a wide-area network, a local-area network, a client-server network
(such as a cloud
computing network), or other such network) using one or more network
computers.
[0164] For clarity, only certain selected aspects of the software-based
implementations are
described. Other details that are well known in the art are omitted. For
example, it should be
understood that the disclosed technology is not limited to any specific
computer language or
program. For instance, the disclosed technology can be implemented by software
written in
C++, Java, Pert, JavaScript, Adobe Flash, or any other suitable programming
language.
Likewise, the disclosed technology is not limited to any particular computer
or type of hardware.
Certain details of suitable computers and hardware are well known and need not
be set forth in
detail in this disclosure.
[0165] Furthermore, any of the software-based embodiments (comprising, for
example,
computer-executable instructions for causing a computer to perform any of the
disclosed
methods) can be uploaded, downloaded, or remotely accessed through a suitable
communication
means. Such suitable communication means include, for example, the Internet,
the World Wide
Web, an intranet, software applications, cable (including fiber optic cable),
magnetic
communications, electromagnetic communications (including RF, microwave, and
infrared
communications), electronic communications, or other such communication means.
[0166] For purposes of this description, certain aspects, advantages, and
novel features of the
embodiments of this disclosure are described herein. The disclosed methods,
apparatus, and
systems should not be construed as limiting in any way. Instead, the present
disclosure is
directed toward all novel and nonobvious features and aspects of the various
disclosed
embodiments, alone and in various combinations and sub combinations with one
another. The
disclosed methods, apparatus, and systems are not limited to any specific
aspect or feature or
combination thereof, nor do the disclosed embodiments require that any one or
more specific
advantages be present or problems be solved.
- 46 -
CA 3027776 2018-12-17
JBF/jbf 23-96246-05 12/04/18 30797-E CIP FILED VIA EFS ON JULY 10, 2018
[0167] The technologies from any example can be combined with the technologies
described in
any one or more of the other examples. In view of the many possible
embodiments to which the
principles of the disclosed technology may be applied, it should be recognized
that the illustrated
embodiments are examples of the disclosed technology and should not be taken
as a limitation
on the scope of the disclosed technology.
[0168] As used in this application and in the claims, the singular forms "a,"
"an," and "the"
include the plural forms unless the context clearly dictates otherwise.
Additionally, the term
"includes" means "comprises." Further, the terms "coupled" and "associated"
generally mean
electrically, electromagnetically, and/or physically (e.g., mechanically or
chemically) coupled or
linked and does not exclude the presence of intermediate elements between the
coupled or
associated items absent specific contrary language.
[0169] In some examples, values, procedures, or apparatus may be referred to
as "lowest,"
"down," "upper," "lower," "horizontal," "vertical," "left," "right," and the
like. These terms are
used, where applicable, to provide some clarity of description when dealing
with relative
relationships. But, these terms are not intended to imply absolute
relationships, positions, and/or
orientations. For example, with respect to an object, an "upper" surface can
become a "lower"
surface simply by turning the object over. Nevertheless, it is still the same
object.
Additional Examples of the Disclosed Technology
[0170] Additional Examples of the disclosed subject matter are discussed
herein in accordance
with the examples discussed above.
[0171] According to one example of the disclosed technology, a method includes
assigning a
fitness metric to at least one electrical device coupled to a power grid, the
fitness metric being
based at least in part on an availability component and a quality component
associated with the at
least one electrical device, assigning a frequency threshold based on the
fitness metric to cause
the at least one electrical device to activate autonomously based on a
frequency of the power
grid, and transmitting the assigned frequency threshold to the at least one
electrical device.
[0172] In some examples of the method, the availability component is based on
a probability that
the at least one electrical device will be available to perform a requested
service.
[0173] In some examples of the method, the requested service is a request for
the at least one
electrical device to deactivate, and the availability component is based on a
probability that the at
least one electrical device will be active when the service is requested.
- 47 -
CA 3027776 2018-12-17
JBF/jbf 23-96246-05 12/04/18 30797-E CIP FILED VIA EFS ON JULY 10, 2018
[0174] In some examples of the method, the requested service is a request for
the at least one
electrical device to activate, and the availability component is based on a
probability that the at
least one electrical device will not be active when the service is requested.
[0175] In some examples of the method, the quality component is based on the
quality of
performance of the at least one electrical device when it performs a requested
service.
[0176] In some examples of the method, the quality component is based on a
probability that the
at least one electrical device will be able to successfully perform a
requested service when
requested.
[0177] In some examples of the method, the transmitting uses at least one of
an Internet
connection, an intranet connection, a powerline transceiver, or a wireless
connection.
[0178] In some examples of the method, the at least one electrical device is a
heater, an HVAC
system, or a water heater.
[0179] In some examples of the method, the method further includes receiving a
use profile
associated with the at least one electrical device, and calculating the
fitness metric based on the
received use profile.
[0180] In some examples of the method, the use profile includes an operational
state of the at
least one electrical device at a particular time.
[0181] In some examples of the method, the use profile includes data from at
least one sensor
associated with the at least one electrical device.
[0182] In some examples of the method, the at least one electrical device
comprises a first
electrical device, the fitness metric comprises a first fitness metric, the
frequency threshold
comprises a first frequency threshold, and the method further includes
assigning a second fitness
metric to a second electrical device coupled to the power grid, the second
fitness metric being
based at least in part on a second availability component and a second quality
component
associated with the second electrical device, assigning a priority to the
first and second electrical
devices based on the first and second fitness metrics, assigning the first
frequency threshold to
the first electrical device and a second frequency threshold to the second
electrical device based
on the assigned priority of the devices, and transmitting the assigned second
frequency threshold
to the second electrical device.
[0183] In some examples of the method, the method further includes determining
a first amount
of power required to operate the at least one electrical device during a
certain time period,
transmitting the first amount of power to a grid operator, and receiving from
the grid operator a
- 48 -
CA 3027776 2018-12-17
JBF/jbf 23-96246-05 12/04/18 30797-E OP FILED VIA EFS ON JULY 10, 2018
second amount of power that can be allocated to the at least one electrical
device during the time
period.
[0184] In some examples of the method, a non-transitory computer-readable
storage media
stores computer-executable instructions that when executed by a computer cause
the computer to
perform the method.
[0185] According to another example of the disclosed technology, a load
aggregator includes a
processor, a communication interface coupled to a power grid, and memory
storing computer-
readable instructions that when executed by the processor, cause the processor
to perform a
method, the instructions including instructions that cause the processor to
assign a fitness metric
to at least one electrical device coupled to the power grid, the fitness
metric being based at least
in part on an availability component and a quality component associated with
the at least one
electrical device, instructions that cause the processor to assign a frequency
threshold based on
the fitness metric to cause the at least one electrical device to activate
autonomously based on a
frequency of the power grid, and instructions that cause the processor to
transmit the assigned
frequency threshold to the at least one electrical device.
[0186] In some examples of the load aggregator, the availability component is
based on a
probability that the at least one electrical device will be available to
perform a requested service.
[0187] In some examples of the load aggregator, the quality component is based
on the quality of
performance of the at least one electrical device when it performs a requested
service.
[0188] In some examples of the load aggregator, the instructions further
include instructions that
cause the processor to receive a use profile associated with the at least one
electrical device and
instructions that cause the processor to calculate the fitness metric based on
the received use
profile.
[0189] In some examples of the load aggregator, the at least one electrical
device comprises a
first electrical device, the fitness metric comprises a first fitness metric,
the frequency threshold
comprises a first frequency threshold, and the instructions further include
instructions that cause
the processor to assign a second fitness metric to a second electrical device
coupled to the power
grid, the second fitness metric being based at least in part on a second
availability component
and a second quality component associated with the second electrical device,
instructions that
cause the processor to assign a priority to the first and second electrical
devices based on the first
and second fitness metrics, instructions that cause the processor to assign
the first frequency
threshold to the first electrical device and a second frequency threshold to
the second electrical
- 49 -
CA 3027776 2018-12-17
JBF/jbf 23-96246-05 12/04/18 30797-E CEP FILED VIA EFS ON JULY 10, 2018
device based on the assigned priority of the device, and instructions that
cause the processor to
transmit the assigned second frequency threshold to the second electrical
device.
[0190] In some examples of the load aggregator, the instructions further
include instructions that
cause the processor to determine a first amount of power required to operate
the at least one
electrical device during a certain time period, instructions that cause the
processor to transmit the
determined first amount of power to a grid operator, and instructions that
cause the processor to
receive from the grid operator a second amount of power that can be allocated
to the at least one
electrical device during the time period.
[0191] According to another example of the disclosed technology, a method
includes sending a
use profile associated with the electrical device, responsive to the sending
the use profile,
receiving a frequency threshold, monitoring a grid frequency of the power
grid, and activating or
deactivating the electrical device based on the received frequency threshold
and the monitored
power grid frequency.
[0192] In some examples of the method, the method further includes activating
the electrical
device when the grid frequency is above the frequency threshold.
[0193] In some examples of the method, the method further includes
deactivating the electrical
device when the grid frequency is below the frequency threshold.
[0194] In some examples of the method, the method further includes receiving
data from at least
one sensor coupled to the electrical device, wherein the use profile is based
at least in part on the
data received from the at least one sensor.
[0195] In some examples of the method, the data received from the at least one
sensor comprises
temperature data.
[0196] In some examples of the method, the method further includes receiving
data indicating an
operational state of the electrical device, wherein the use profile is based
at least in part on this
received data.
[0197] According to another example of the disclosed technology, a resource
controller includes
a receiver configured to receive sensor data and load state data provided by
an electrical device
coupled to a power grid, and a processor coupled to the receiver and
configured to perform a
method by executing computer-readable instructions, the instructions including
instructions that
cause the processor to send a use profile associated with the electrical
device based on the sensor
data and the load state data, instructions that cause the processor to detect
a grid frequency of the
- 50 -
CA 3027776 2018-12-17
JBF/Jbf 23-96246-05 12/04/18 30797-E CIP FILED VIA EFS ON JULY 10, 2018
power grid, and instructions that cause the processor to activate or
deactivate the electrical
device based on a frequency threshold and the detected grid frequency.
[0198] In some examples of the resource controller, the instructions cause the
processor to
activate the electrical device when the detected grid frequency is above the
frequency threshold.
[0199] In some examples of the resource controller, the instructions cause the
processor to
deactivate the device when the grid frequency is below the frequency
threshold.
[0200] In some examples of the resource controller, the use profile is based
at least in part on
data generated by at least one sensor coupled to the electrical device.
[0201] In some examples of the resource controller, the use profile is based
at least in part on
data indicating an operational state of the device.
[0202] According to another example of the disclosed technology, a system
includes a resource
controller and a load aggregator. In some examples of the system, the resource
controller
includes a receiver configured to receive sensor data and load state data
provided by an electrical
device coupled to a power grid, and a first processor coupled to the receiver
and configured to
perform a method by executing computer-readable instructions, the instructions
including
instructions that cause the first processor to send a user profile associated
with the electrical
device based on the sensor data and the load data, instructions that cause the
first processor to
detect a grid frequency of the power grid, and instructions that cause the
processor to activate or
deactivate the electrical device based on a frequency threshold and the
detected grid frequency.
In some examples of the system, the load aggregator comprises a second
processor, a
communication interface coupled to the power grid, and memory storing computer-
readable
instructions that when executed by the second processor, cause the second
processor to perfor a
method, the instructions including instructions that cause the second
processor to assign a fitness
metric to the electrical device, the fitness metric being based at least in
part on an availability
component and a quality component associated with the electrical device,
instructions that cause
the second processor to assign the frequency threshold based on the fitness
metric, and
instructions that cause the processor to transmit the assigned frequency
threshold to the electrical
device.
[0203] In view of the many possible embodiments to which the principles of the
disclosed
subject matter may be applied, it should be recognized that the illustrated
embodiments are only
preferred examples and should not be taken as limiting the scope of the claims
to those preferred
examples. Rather, the scope of the claimed subject matter is defined by the
following claims.
-51 -
CA 3027776 2018-12-17
JBF/jbf 23-96246-05 12/04/18 30797-E CIP FILED
VIA EFS ON JULY 10, 2018
We therefore claim as our invention all that comes within the scope of these
claims and their
equivalents.
- 52 -
CA 3027776 2018-12-17
