Note: Descriptions are shown in the official language in which they were submitted.
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ELECTRIC POWER SYSTEM CONTROL WITH PLANNING OF ENERGY
DEMAND AND ENERGY EFFICIENCY USING AMI-BASED DATA ANALYSIS
BACKGROUND
[0001] The present disclosure relates to a method, an apparatus, a system and
a
computer program for controlling an electric power system, including planning
the
distribution circuits with respect to optimizing voltage, conserving energy,
and
reducing demand. More particularly, the disclosure relates to an
implementation of
planning electrical demand and energy efficiency, using advanced metering
infrastructure ("AMI")-based data analysis. This method enables the direct
determination of the capability of a circuit to reduce energy usage and
electrical
demand based on an implementation of proposed configuration changes of an
electric
power system. The method may be used to accurately quantify a projection of
the
value of the energy efficiency and electrical demand reduction savings
resulting from
implementation of proposed modifications in an electric power system and
compare a
cost/benefit of each proposed modification. In addition, this method is
capable of
using the AMI-based measurements to identify specific problems with the
electric
power system, allowing the operation of the electric power system to be
appropriately
modified based on the identification of these problems.
[0002] Electricity is commonly generated at a power station by
electromechanical
generators, which are typically driven by heat engines fueled by chemical
combustion
or nuclear fission, or driven by kinetic energy flowing from water or wind.
The
electricity is generally supplied to end users through transmission grids as
an
alternating current signal. The transmission grids may include a network of
power
stations, transmission circuits, substations, and the like.
[0003] The generated electricity is typically stepped-up in voltage using, for
example,
generating step-up transformers, before supplying the electricity to a
transmission
system. Stepping up the voltage improves transmission efficiency by reducing
the
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electrical current flowing in the transmission system conductors, while
keeping the
power transmitted nearly equal to the power input. The stepped-up voltage
electricity
is then transmitted through the transmission system to a distribution system,
which
distributes the electricity to end users. The distribution system may include
a network
that carries electricity from the transmission system and delivering it to end
users.
Typically, the network may include medium-voltage (for example, less than
69kV)
power lines, electrical substations, transformers, low-voltage (for example,
less than
lkV) distribution wiring, electric meters, and the like.
[0004] The following, the entirety of each of which is herein incorporated by
reference, describe subject matter related to power generation or
distribution:
Engineering Optimization Methods and Applications, First Edition, G.V.
Reklaitis, A.
Ravindran, K.M. Ragsdell, John Wiley and Sons, 1983; Estimating Methodology
for a
Large Regional Application of Conservation Voltage Reduction, J.G. De Steese,
S.B.
Merrick, B.W. Kennedy, IEEE Transactions on Power Systems, 1990; Power
Distribution Planning Reference Book, Second Edition, H. Lee Willis, 2004;
Implementation of Conservation Voltage Reduction at Commonwealth Edison, IEEE
Transactions on Power Systems, D. Kirshner, 1990; Conservation Voltage
Reduction
at Northeast Utilities, D.M. Lauria, IEEE, 1987; Green Circuit Field
Demonstrations,
EPRI, Palo Alto, CA, 2009, Report 1016520; Evaluation of Conservation Voltage
Reduction (CVR) on a National Level, PNNL-19596, Prepared for the U.S.
Department of Energy under Contract DE-AC05-76RL01830, Pacific Northwest
National Lab, July 2010; Utility Distribution System Efficiency Initiative
(DEI) Phase
1, Final Market Progress Evaluation Report, No 3, E08-192 (7/2008) E08-192;
Simplified Voltage Optimization (VO) Measurement and Verification Protocol,
Simplified VO M&V Protocol Version 1.0, May 4, 2010; MINITAB Handbook,
Updated for Release 14, fifth edition, Barbara Ryan, Brian Joiner, Jonathan
Cryer,
Brooks/Cole-Thomson, 2005; Minitab Software, http://www.minitab.com/en-
US/products/minitab/ Statistical Software provided by Minitab Corporation.
[0005] Further, U.S. patent application 61/176,398, filed on May 7, 2009 and
US
publication 2013/0030591 entitled VOLTAGE CONSERVATION USING
ADVANCED METERING INFRASTRUCTURE AND SUBSTATION
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CENTRALIZED VOLTAGE CONTROL, the entirety of which is herein incorporated
by reference, describe a voltage control and energy conservation system for an
electric power transmission and distribution grid configured to supply
electric power
to a plurality of user locations.
SUMMARY
[0006] Various embodiments described herein provide a novel method, apparatus,
system and computer program for controlling an electric power system,
including
implementation of voltage planning for electrical energy delivery systems
(EEDS)
using secondary voltages measured by advanced metering infrastructure (AMI)
("AMI-based measurements"). The AMI-based measurements and voltage planning
may be used to optimize the energy efficiency and demand reduction capability
of the
EEDS, including that specifically obtained from implementing conservation
voltage
reduction (CVR) in the EEDS. The AMI-based measurements and voltage planning
may also be used to improve the reliability of the voltage performance for the
energy
usage system (EUS) and energy usage devices (EUD) attached to the electrical
energy
distribution connection system (EEDCS).
[0007] According to an aspect of the disclosure, the energy planning process
(EPP)
projects the voltage range capability of a given electrical energy delivery
system
(EEDS) (made up of an energy supply system (ES S) that connects electrically
via the
electrical energy distribution connection system (EEDCS) to one or more energy
usage systems (EUS)) at the customer secondary level (the EUS) by measuring
the
level of change in energy usage from voltage management for the EEDS. The EPP
can also determine potential impacts of proposed modifications to the
equipment
and/or equipment configuration of the EEDS and/or to an energy usage device
(EUD)
at some electrical point(s) on an electrical energy delivery system (EEDS)
made up of
many energy usage devices randomly using energy at any given time during the
measurement. The purpose of the energy validation process (EVP) is to measure
the
level of change in energy usage for the EEDS for a change in voltage level.
The
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specifics of an example EVP are covered in co-pending U.S. patent application
nos.
61/789085 and 14/193,980, entitled ELECTRIC POWER SYSTEM CONTROL
WITH MEASUREMENT OF ENERGY DEMAND AND ENERGY EFFICIENCY
USING T ¨ DISTRIBUTIONS.("the co-pending /P006 application"), the entirety of
which are incorporated herein, although other EVPs may also be used. One
purpose
of the EPP system of the disclosed embodiments is to estimate the capability
of the
EEDS to accommodate voltage change and predict the level of change available.
The
potential savings in energy provided by the proposed modification to the
system can
be calculated by multiplying the CVR factor (% change in energy/% change in
voltage) (as may be calculated by the EVP, an example of which is described in
the
co-pending /P006 application, although other methods of calculating a CVR
factor
may also be used) by the available change in voltage (as determined by the
EPP) to
determine the available energy and demand savings over the time interval being
studied. The electrical energy supply to the electrical energy delivery system
(EEDS)
is measured in watts, kilowatts (kw), or Megawatts (Mw) (a) at the supply
point of the
ESS and (b) at the energy user system (EUS) or meter point. This measurement
records the average usage of energy (AUE) at each of the supply and meter
points
over set time periods such as one hour.
[0008] The test for energy use improvement is divided into two basic time
periods:
The first is the time period when the improvement is not included, i.e., in
"OFF" state.
The second time period is when the improvement is included, i.e., in "ON"
state.
Two variables must be determined to estimate the savings capability for a
modification in the EEDS: The available change in voltage created by the
modification and the EEDS capacity for energy change with respect to voltage
change
(the CVR factor, an example calculation of which is described in the co-
pending
/P006 application, although other methods of calculating a CVR factor may also
be
used).
[0009] The calculation of the change in voltage capability is the novel
approach to
conservation voltage reduction planning using a novel characterization of the
EEDS
voltage relationships that does not require a detailed loadflow model to
implement.
The input levels to the EEDCS from the ESS are recorded at set intervals, such
as one
hour periods for the time being studied. The input levels to the EUS from the
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EEDCS, at the same intervals for the time being studied, are measured using
the AMI
system and recorded. The EEDS specific relationship between the ESS
measurements
and the EUS usage measurements is characterized using a linear regression
technique
over the study period. This calculation specifically relates the effects of
changes in
load at the ESS to change in voltage uniquely to each customer EUS using a
common
methodology.
[00010] Once these linear relationships have been calculated, a simple
linear
model is built to represent the complex behavior of voltage at various loading
levels
including the effects of switching unique EUS specific loads that are embedded
in the
AMI collected data (e.g., the data includes the "ON" and "OFF" nature of the
load
switching occurring at the EUS). Then, the specific planned modification is
related to
the linear model so the model can calculate the new voltage ranges available
from the
planned modification. Using this simple linear model is a novel method of
planning
and predicting the voltage behavior of an EEDS caused by modifications to the
EEDS.
[00011] The relationships between the modification (e.g., adding/removing
capacitor banks, adding/removing regulators, reducing impedance, or adding
distributed generation) are developed first by using a simple system of one
ESS and a
simple single phase line and a single EUS with a base load and two repeating
switched loads. By comparing a traditional loadflow model of the simplified
EEDS to
the linear statistical representation of the voltage characteristics, the
linear model
changes can be obtained to relate the modifications to specific changes in the
linear
model. Once this is done, proposed modifications are easily checked to predict
the
voltage range effects and the corresponding EEDS energy savings and demand
savings using the CVR factor.
[00012] Once the linear model is built then the model can be used to apply
simple linear optimization to determine the best method of improving the EEDS
to
meet the desired energy modification. In addition this method can optimize the
cost/benefit of modifications allowing the user to select the best choice of
modifications for the EEDS.
[00013] According to a further aspect of the disclosure, the energy
planning
process (EPP) can be used to take the AMI data from multiple AMI EUS points
and
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build a linear model of the voltage using the linearization technique. These
multiple
point models can be used to predict voltage behavior for a larger radial
system (e.g., a
group of contiguous transmission elements that emanate from a single point of
connection) by relating the larger system linear characteristics to the system
modification of capacitor installation, regulator installation, and impedance
modifications to allow the building of a simple linear model of the voltage
characteristics with multiple modifications made. With the new model
representing
the modifications the optimization can optimize the cost/benefit of various
modifications, thus allowing the user to select the best choice of
modifications for the
EEDS.
[00014] According to a further aspect of the disclosure, the energy
planning
process (EPP) can be used to take the AMI data from multiple AMI EUS points
and
multiple ESS points and build a linear model of the voltage using the
linearization
technique. These multiple ESS and EUS point models can be used to predict
voltage
behavior for a larger radial system by relating the larger system linear
characteristics
to the system modification of capacitor installation, regulator installation,
and
impedance modifications to allow the building of a simple linear model of the
voltage
characteristics with multiple modifications made. With the new model
representing
the modifications the optimization can optimize the cost/benefit of various
modifications, thus allowing the user to select the best choice of
modifications for the
EEDS.
[00015] According to a further aspect of the disclosure, the energy
planning
process (EPP) can be used to take the AMI data from multiple AMI EUS points
and
multiple ESS points and build a linear model of the voltage using the
linearization
technique. The linear model that exists for normal operation can be determined
based
on the characteristics of the linearization. Using this normal operation model
as a
"fingerprint", the other EUS points on the EEDS can be filtered to determine
the ones,
if any, that are displaying abnormal behavior characteristics and the abnormal
EUS
points can be compared against a list of expected characteristics denoting
specific
abnormal behavior that represents the potential of low reliability
performance. As an
example, the characteristics of a poorly connected meter base has been
characterized
to have certain linear characteristics in the model. The observed linear
characteristics
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that represent this abnormal condition can be used to identify any of the EUS
meters
that exhibit this behavior, using the voltage data from AMI. This allows
resolution of
the abnormality before customer equipment failure occurs and significantly
improves
the reliability of the EEDS.
[00016] According to a further aspect of the disclosure, the energy
planning
process (EPP) can be used to take the AMI data from multiple AMI EUS points
and
multiple ESS points and build a linear model of the voltage using the
linearization
technique. Using this model and the measured AMI data the EPP can be used to
project the initial group of meters that can be used in the voltage management
system
to control the minimum level of voltage across the EEDS for implementation of
CVR.
[00017] According to a further aspect of the disclosure, the energy
planning
process (EPP) can be used to take the AMI data from multiple AMI EUS points
and
multiple ESS points and build a linear model of the voltage using the
linearization
technique. The voltage data can be used to provide location information about
the
meter connection points on the circuit using voltage correlation analysis.
This method
matches the voltages by magnitude and by phase using a technique that uses the
voltage data for each meter to provide the statistical analysis. Common phase
voltage
movement is correlated and common voltage movement by circuit is identified
using
linear regression techniques. This information when combined with the latitude
and
longitude information on the meter can provide specific connectivity checks
for
primary based applications such as outage management and DMS real-time models.
[0019] Additional features, advantages, and embodiments of the disclosure may
be set
forth or apparent from consideration of the detailed description and drawings.
Moreover, it is to be understood that both the foregoing summary of the
disclosure
and the following detailed description are exemplary and intended to provide
further
explanation without limiting the scope of the disclosure as claimed.
BRIEF DESCRIPTION OF THE DRAWINGS
[0020] The accompanying drawings, which are included to provide a further
understanding of the disclosure, are incorporated in and constitute a part of
this
specification, illustrate embodiments of the disclosure and together with the
detailed
description serve to explain the principles of the disclosure. No attempt is
made to
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show structural details of the disclosure in more detail than may be necessary
for a
fundamental understanding of the disclosure and the various ways in which it
may be
practiced. In the drawings:
[0021] FIG. 1 shows an example of an EEDS made up of an electricity
generation
and distribution system connected to customer loads, according to principles
of the
disclosure;
[0022] FIG. 2 shows an example of a voltage control and conservation (VCC)
system being measured at the ESS meter point, the EUS made up of Advanced
Metering Infrastructure (AMI) measuring voltage and energy, and the control
system
VCC and an EPP according to the principles of the disclosure;
[0023] FIG. 3 shows an example of an EEDS made up of an EES, an EEDCS
and multiple EUS, and outlines the methods of determining losses in the EEDCS
and
the EUS associated with voltage conservation control (VCC), according to
principles
of the disclosure;
[0024] FIG. 4 shows an example of an Energy Planning Process (EPP) system
with metering points (AMI) used in analysis, including the systems that affect
voltage
control as well as the devices or equipment that can be modified to change the
EEDS
performance according to principles of the disclosure;
[0025] FIG. 5 shows a distribution system example of how the ESS data is
correlated with the EUS data using linear regression to build the simple
linear model
of the voltage behavior of a EEDCS and customer loads, according to principles
of
the disclosure;
[0026] FIG. 6 shows a distribution system example of how the primary
system
is modeled to determine the change in linear system characteristics that are
developed
for specific modifications to the connection equipment and voltage control
equipment,
according to principles of the disclosure;
[0027] FIG. 7 shows an example of voltage data for an EEDCS for one set
of
ESS voltages (Volt) and one set of VAMI voltages (at an EUS) taken hourly over
a 24
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hour period for statistical comparison from a prototype system, according to
principles of the disclosure;
[0028] FIG. 8 shows an example of the results of the linear regression
analysis
of the example data from FIG. 7, according to the principles of the
disclosure.
[0029] FIG. 9 shows an example of the results of the linear regression
analysis
histograms of the example data from FIG. 7, according to the principles of the
disclosure.
[0030] FIG. 10 shows an example of the results of the linear regression
analysis histograms of the example data from FIG. 7, according to the
principles of
the disclosure
[0031] FIG. 11 shows an example of an Energy Planning Process (EPP) map
of the planning process for controlling voltage, according to the principles
of the
disclosure;
[0032] FIG. 12 shows an example of a histogram of the EUS AMI voltage
data used to identify the voltage outliers for developing modification plans
for the
EEDS, according to principles of the disclosure;
[0033] FIG. 13 shows a distribution circuit example of an application
that
maps the EUS AMI data to a circuit one line diagram for use by the planners to
develop circuit modifications with their existing circuit planning software,
according
to principles of the disclosure;
[0034] FIG. 14 shows a distribution circuit example of a mapping of the
AMI
voltage points to specific zones and blocks to match up with specific control
devices
on the EEDS, according to principles of the disclosure; and
[0035] FIG. 15 shows an example of a summary chart for the example circuit
shown in FIG. 14 that has been processed through the EPP to produce the
selection of
the initial meters for each block, according to principles of the disclosure.
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[0036] The present disclosure is further described in the detailed
description that
follows.
DETAILED DESCRIPTION OF THE DISCLOSURE
[0037] The disclosure and the various features and advantageous details
thereof
are explained more fully with reference to the non-limiting embodiments and
examples that are described and/or illustrated in the accompanying drawings
and
detailed in the following description. It should be noted that the features
illustrated in
the drawings are not necessarily drawn to scale, and features of one
embodiment may
be employed with other embodiments as the skilled artisan would recognize,
even if
not explicitly stated herein. Descriptions of well-known components and
processing
techniques may be omitted so as to not unnecessarily obscure the embodiments
of the
disclosure. The examples used herein are intended merely to facilitate an
understanding of ways in which the disclosure may be practiced and to further
enable
those of skill in the art to practice the embodiments of the disclosure.
Accordingly,
the examples and embodiments herein should not be construed as limiting the
scope
of the disclosure. Moreover, it is noted that like reference numerals
represent similar
parts throughout the several views of the drawings.
[0038] A "computer", as used in this disclosure, means any machine, device,
circuit, component, or module, or any system of machines, devices, circuits,
components, modules, or the like, which are capable of manipulating data
according
to one or more instructions, such as, for example, without limitation, a
processor, a
microprocessor, a central processing unit, a general purpose computer, a super
computer, a personal computer, a laptop computer, a palmtop computer, a
notebook
computer, a desktop computer, a workstation computer, a server, or the like,
or an
array of processors, microprocessors, central processing units, general
purpose
computers, super computers, personal computers, laptop computers, palmtop
computers, notebook computers, desktop computers, workstation computers,
servers,
or the like.
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[0039] A "server", as used in this disclosure, means any combination of
software
and/or hardware, including at least one application and/or at least one
computer to
perform services for connected clients as part of a client-server
architecture. The at
least one server application may include, but is not limited to, for example,
an
application program that can accept connections to service requests from
clients by
sending back responses to the clients. The server may be configured to run the
at
least one application, often under heavy workloads, unattended, for extended
periods
of time with minimal human direction. The server may include a plurality of
computers configured, with the at least one application being divided among
the
computers depending upon the workload. For example, under light loading, the
at
least one application can run on a single computer. However, under heavy
loading,
multiple computers may be required to run the at least one application. The
server, or
any if its computers, may also be used as a workstation.
[00401 A "database", as used in this disclosure, means any combination of
software and/or hardware, including at least one application and/or at least
one
computer. The database may include a structured collection of records or data
organized according to a database model, such as, for example, but not limited
to at
least one of a relational model, a hierarchical model, a network model or the
like. The
database may include a database management system application (DBMS) as is
known in the art. At least one application may include, but is not limited to,
for
example, an application program that can accept connections to service
requests from
clients by sending back responses to the clients. The database may be
configured to
run the at least one application, often under heavy workloads, unattended, for
extended periods of time with minimal human direction.
[00411 A "communication link", as used in this disclosure, means a wired
and/or
wireless medium that conveys data or information between at least two points.
The
wired or wireless medium may include, for example, a metallic conductor link,
a radio
frequency (RF) communication link, an Infrared (IR) communication link, an
optical
communication link, or the like, without limitation. The RF communication link
may
include, for example, WiFi, WiMAX, IEEE 802.11, DECT, OG, 1G, 2G, 3G or 4G
cellular standards, Bluetooth, and the like.
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[0042] The terms "including", "comprising" and variations thereof, as used
in this
disclosure, mean "including, but not limited to", unless expressly specified
otherwise.
[0043] The terms "a", "an", and "the", as used in this disclosure, means
"one or
more", unless expressly specified otherwise.
[0044] Devices that are in communication with each other need not be in
continuous communication with each other, unless expressly specified
otherwise. In
addition, devices that are in communication with each other may communicate
directly or indirectly through one or more intermediaries.
[0045] Although process steps, method steps, algorithms, or the like, may
be
described in a sequential order, such processes, methods and algorithms may be
configured to work in alternate orders. In other words, any sequence or order
of steps
that may be described does not necessarily indicate a requirement that the
steps be
performed in that order. The steps of the processes, methods or algorithms
described
herein may be performed in any order practical. Further, some steps may be
performed simultaneously.
[0046] When a single device or article is described herein, it will be
readily
apparent that more than one device or article may be used in place of a single
device
or article. Similarly, where more than one device or article is described
herein, it will
be readily apparent that a single device or article may be used in place of
the more
than one device or article. The functionality or the features of a device may
be
alternatively embodied by one or more other devices which are not explicitly
described as having such functionality or features.
[0047] A "computer-readable medium", as used in this disclosure, means any
medium that participates in providing data (for example, instructions) which
may be
read by a computer. Such a medium may take many forms, including non-volatile
media, volatile media, and transmission media. Non-volatile media may include,
for
example, optical or magnetic disks and other persistent memory. Volatile media
may
include dynamic random access memory (DRAM). Transmission media may include
coaxial cables, copper wire and fiber optics, including the wires that
comprise a
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system bus coupled to the processor. Transmission media may include or convey
acoustic waves, light waves and electromagnetic emissions, such as those
generated
during radio frequency (RF) and infrared (IR) data communications. Common
forms
of computer-readable media include, for example, a floppy disk, a flexible
disk, hard
disk, magnetic tape, any other magnetic medium, a CD-ROM, DVD, any other
optical
medium, punch cards, paper tape, any other physical medium with patterns of
holes, a
RAM, a PROM, an EPROM, a FLASH-EEPROM, any other memory chip or
cartridge, a carrier wave as described hereinafter, or any other medium from
which a
computer can read.
[0048] Various forms of computer readable media may be involved in carrying
sequences of instructions to a computer. For example, sequences of instruction
(i)
may be delivered from a RAM to a processor, (ii) may be carried over a
wireless
transmission medium, and/or (iii) may be formatted according to numerous
formats,
standards or protocols, including, for example, WiFi, WiMAX, IEEE 802.11,
DECT,
OG, 1G, 2G, 3G or 4G cellular standards, Bluetooth, or the like.
[0049] According to one non-limiting example of the disclosure, an energy
planning process (EPP) system 1700 (shown in FIG. 2) is provided. The EPP
system
1700 performs the planning functions of the disclosed embodiments, and is
described
in more detail below. A voltage control and conservation (VCC) system 200 may
also be provided, which includes three subsystems, including an energy
delivery (ED)
system 300, an energy control (EC) system 400 and an energy regulation (ER)
system
500. The VCC system 200 is configured to monitor energy usage at the ED system
300 and determine one or more energy delivery parameters at the EC system (or
voltage controller) 400. The EC system 400 may then provide the one or more
energy
delivery parameters CED to the ER system 500 to adjust the energy delivered to
a
plurality of users for maximum energy conservation. Also shown in FIG. 2 is an
energy validation system (EVP) 600. The EVP system 600 is used to monitor the
change in EEDS energy from the VCC system 200. The EVP system 600 monitors
through communications link 610 all metered energy flow and determines the
change
in energy resulting from a change in voltage control at the ER system 500. The
EVP
system 600 also reads weather data information through a communication link
620
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from an appropriate weather station 640 to execute the EVP process 630. An
example
EVP system 600 is more fully described in the co-pending /P006 application,
although other EVPs can also be used.
[0050] The EPP system 1700 reads the historical databases 470 via
communication link 1740 for the AMI data. The EPP system 1700 can process this
historical data along with measured AMI data to identify problems, if any, on
the
EEDS system 700. The EPP system 1700 is also able to identify any outlier
points in
the analysis caused by proposed system modifications and to identify the
initial
meters to be used for monitoring by VCC system 200 until the adaptive process
(discussed in the 2013/0030591 publication) is initiated by the control
system.
[0051] The VCC system 200 is also configured to monitor via communication
link 610 energy change data from EVP system 600 and determine one or more
energy
delivery parameters at the EC system (or voltage controller) 400. The EC
system 400
may then provide the one or more energy delivery parameters CED to the ER
system
500 to adjust the energy delivered to a plurality of users for maximum energy
conservation. Similarly, the EC system 400 may use the energy change data to
control the EEDS 700 in other ways. For example, components of the EEDS 700
may
be modified, adjusted, added or deleted, including the addition of capacitor
banks,
modification of voltage regulators, changes to end-user equipment to modify
customer efficiency, and other control actions.
[0052] The VCC system 200 may be integrated into, for example, an existing
load
curtailment plan of an electrical power supply system. The electrical power
supply
system may include an emergency voltage reduction plan, which may be activated
when one or more predetermined events are triggered. The predetermined events
may
include, for example, an emergency, an overheating of electrical conductors,
when the
electrical power output from the transformer exceeds, for example, 80% of its
power
rating, or the like. The VCC system 200 is configured to yield to the load
curtailment
plan when the one or more predetermined events are triggered, allowing the
load
curtailment plan to be executed to reduce the voltage of the electrical power
supplied
to the plurality of users.
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[0053] FIG. 1 is similar to FIG. 1 of US publication 2013/0030591, with
overlays
that show an example of an EEDS 700 system, including an ESS system 800, an
EUS
system 900 and an EEDCS system 1000 based on the electricity generation and
distribution system 100, according to principles of the disclosure. The
electricity
generation and distribution system 100 includes an electrical power generating
station
110, a generating step-up transformer 120, a substation 130, a plurality of
step-down
transformers 140, 165, 167, and users 150, 160. The electrical power
generating
station 110 generates electrical power that is supplied to the step-up
transformer 120.
The step-up transformer steps-up the voltage of the electrical power and
supplies the
stepped-up electrical power to an electrical transmission media 125. The ESS
800
includes the station 110, the step-up transformer 120, the substation 130, the
step-
down transformers 140, 165, 167, the ER 500 as described herein, and the
electrical
transmission media, including media 125, for transmitting the power from the
station
110 to users 150, 160. The EUS 900 includes the ED 300 system as described
herein,
and a number of energy usage devices (EUD) 920 that may be consumers of power,
or
loads, including customer equipment and the like. The EEDCS system 1000
includes
transmission media, including media 135, connections and any other equipment
located between the ESS 800 and the EUS 900.
[0054] As seen in FIG. 1, the electrical transmission media may include
wire
conductors, which may be carried above ground by, for example, utility poles
127,
137 and/or underground by, for example, shielded conductors (not shown).
The
electrical power is supplied from the step-up transformer 120 to the
substation 130 as
electrical power Ein(t), where the electrical power Em in MegaWatts (MW) may
vary
as a function of time t. The substation 130 converts the received electrical
power
E1(t) to Esuppiy(t) and supplies the converted electrical power Esuppiy(t) to
the plurality
of users 150, 160. The substation 130 may adjustably transform the voltage
component Vin(t) of the received electrical power Ein(t) by, for example,
stepping-
down the voltage before supplying the electrical power Esuppiy(t) to the users
150, 160.
The electrical power Esuppiy(t) supplied from the substation 130 may be
received by
the step-down transformers 140, 165, 167 and supplied to the users 150, 160
through
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a transmission medium 142, 162, such as, for example, but not limited to,
underground electrical conductors (and/or above ground electrical conductors).
[0055] Each of the users 150, 160 may include an Advanced Meter
Infrastructure
(AMI) 330. The AMI 330 may be coupled to a Regional Operations Center (ROC)
180. The ROC 180 may be coupled to the AMI 330, by means of a plurality of
communication links 175, 184, 188, a network 170 and/or a wireless
communication
system 190. The wireless communication system 190 may include, but is not
limited
to, for example, an RF transceiver, a satellite transceiver, and/or the like.
[0056] The network 170 may include, for example, at least one of the
Internet, a
local area network (LAN), a wide area network (WAN), a metropolitan area
network
(MAN), a personal area network (PAN), a campus area network, a corporate area
network, the electrical transmission media 125, 135 and transformers 140, 165,
167, a
global area network (GAN), a broadband area network (BAN), or the like, any of
which may be configured to communicate data via a wireless and/or a wired
communication medium. The network 170 may be configured to include a network
topology such as, for example, a ring, a mesh, a line, a tree, a star, a bus,
a full
connection, or the like.
[0057] The AMI 330 may include any one or more of the following: A smart
meter; a network interface (for example, a WAN interface, or the like);
firmware;
software; hardware; and the like. The AMI may be configured to determine any
one
or more of the following: kilo-Watt-hours (kWh) delivered; kWh received; kWh
delivered plus kWh received; kWh delivered minus kWh received; interval data;
demand data; voltage; current; phase; and the like. If the AMI is a three
phase meter,
then the low phase voltage may be used in the average calculation, or the
values for
each phase may be used independently. If the meter is a single phase meter,
then the
single voltage component will be averaged.
[0058] The AMI 330 may further include one or more collectors 350 (shown in
FIG. 2) configured to collect AMI data from one or more AMIs 330 tasked with,
for
example, measuring and reporting electric power delivery and consumption at
one or
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more of the users 150, 160. Alternatively (or additionally), the one or more
collectors
may be located external to the users 150, 160, such as, for example, in a
housing
holding the step-down transformers 140, 165, 167. Each of the collectors may
be
configured to communicate with the ROC 180.
[0059] The VCC system 200 plugs into the DMS and AMI systems to execute the
voltage control function. In addition the EVP system 600 collects weather data
and
uses the AMI data from the ESS system 800 to calculate the energy savings
level
achieved by the VCC system 200. In addition the EPP system 1700 provides a
process to continually improve the performance of the EEDS by periodically
reviewing the historical AMI voltage data and providing identification of
problem
EUS voltage performance and the modifications needed to increase the
efficiency and
reliability of the EEDS system 700, using the VCC system 200.
VCC SYSTEM 200
[0060] FIG. 2 shows an example of the VCC system 200 with the EVP system
600 monitoring the change in energy resulting from the VCC controlling the
EEDS in
the more efficient lower 5% band of voltage, according to principles of the
disclosure.
The VCC system 200 includes the ED system 300, the EC system 400 and the ER
system 500, each of which is shown as a broken-line ellipse. The VCC system
200 is
configured to monitor energy usage at the ED system 300. The ED system 300
monitors energy usage at one or more users 150, 160 (shown in FIG. 1) and
sends
energy usage information to the EC system 400. The EC system 400 processes the
energy usage information and generates one or more energy delivery parameters
CED,
which it sends to the ER system 500 via communication link 430. The ER system
500 receives the one or more energy delivery parameters CED and adjusts the
electrical power Esuppiy(t) supplied to the users 150, 160 based on the
received energy
delivery parameters CED. The EVP system 600 receives the weather data and the
energy usage data and calculates the energy usage improvement from the VCC
200.
[0061] The VCC system 200 minimizes power system losses, reduces user
energy
consumption and provides precise user voltage control. The VCC system 200 may
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include a closed loop process control application that uses user voltage data
provided
by the ED system 300 to control, for example, a voltage set point Vsp on a
distribution
circuit (not shown) within the ER system 500. That is, the VCC system 200 may
control the voltages Vsappiy(t) of the electrical power Esappiy(t) supplied to
the users
150, 160, by adjusting the voltage set point Vsp of the distribution circuit
in the ER
system 500, which may include, for example, one or more load tap changing
(LTC)
transformers, one or more voltage regulators, or other voltage controlling
equipment
to maintain a tighter band of operation of the voltages V Delivered(0 of the
electric power
EDellvered(t) delivered to the users 150, 160, to lower power losses and
facilitate
efficient use of electrical power EDehvered(0 at the user locations 150 or
160.
[0062] The VCC system 200 controls or adjusts the voltage Vsappiy(t) of the
electrical power Esappiy(t) supplied from the EC system 500 based on AMI data,
which
includes measured voltage VMeter(t) data from the users 150, 160 in the ED
system
300, and based on validation data from the EVP system 600 and information
received
from the EPP system 1700. The VCC system 200 may adjust the voltage set point
Vsp at the substation or line regulator level in the ER system 500 by, for
example,
adjusting the LTC transformer (not shown), circuit regulators (not shown), or
the like,
to maintain the user voltages VMeter(t) in a target voltage band VBand_n,
which may
include a safe nominal operating range.
[0063] The VCC system 200 is configured to maintain the electrical power
EDelivered(t) delivered to the users 150, 160 within one or more voltage bands
VBand-n=
For example, the energy may be delivered in two or more voltage bands VBand-n
substantially simultaneously, where the two or more voltage bands may be
substantially the same or different. The value VBand_n may be determined by
the
following expression [1]:
[1] VBand-n =Vsp + AV
where VBand-n is a range of voltages, n is a positive integer greater than
zero
corresponding to the number of voltage bands VBand that may be handled at
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substantially the same time, Vsp is the voltage set point value and AV is a
voltage
deviation range.
[0064] For example, the VCC system 200 may maintain the electrical power
EDehvered(t) delivered to the users 150, 160 within a band VBand_r equal to,
for example,
111V to 129V for rural applications, where Vsp is set to 120V and AV is set to
a
deviation of seven-and-one-half percent (+/- 7.5%). Similarly, the VCC system
200
may maintain the electrical power EDehvered(t) delivered to the users 150, 160
within a
band V Band-2 equal to, for example, 114V to 126V for urban applications,
where Vsp is
set to 120V and AV is set to a deviation of five (+/- 5%).
[0065] The VCC system 200 may maintain the electrical power EDeuvered(t)
delivered to the users 150, 160 at any voltage band V Band-n usable by the
users 150,
160, by determining appropriate values for Vsp and AV. In this regard, the
values Vsp
and AV may be determined by the EC system 400 based on the energy usage
information for users 150, 160, received from the ED system 300.
[0066] The EC system 400 may send the Vsp and AV values to the ER system
500
as energy delivery parameters CED, which may also include the value VBand-n.
The ER
system 500 may then control and maintain the voltage VDehvered(0 of the
electrical
power EDelivered(t) delivered to the users 150, 160, within the voltage band
VBand-n. The
energy delivery parameters CED may further include, for example, load-tap-
changer
(LTC) control commands.
[0067] The EVP system 600 may further measure and validate energy savings
by
comparing energy usage by the users 150, 160 before a change in the voltage
set point
value Vsp (or voltage band VBand-n) to the energy usage by the users 150, 160
after a
change in the voltage set point value Vsp (or voltage band VBand-n), according
to
principles of the disclosure. These measurements and validations may be used
to
determine the effect in overall energy savings by, for example, lowering the
voltage
VDehvered(t) of the electrical power EDenvered(t) delivered to the users 150,
160, and to
determine optimal delivery voltage bands VBand-n for the energy power
EDehvered(t)
delivered to the users 150, 160.
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ER SYSTEM 500
[0068] The ER system 500 may communicate with the ED system 300 and/or EC
system 400 by means of the network 170. The ER system 500 is coupled to the
network 170 and the EC system 400 by means of communication links 510 and 430,
respectively. The EC system 500 is also coupled to the ED system 300 by means
of
the power lines 340, which may include communication links.
[0069] The ER system 500 includes a substation 530 which receives the
electrical
power supply Ein(t) from, for example, the power generating station 110 (shown
in
FIG. 1) on a line 520. The electrical power E1(t) includes a voltage Vin(t)
component
and a current I1(t) component. The substation 530 adjustably transforms the
received
electrical power Ein(t) to, for example, reduce (or step-down) the voltage
component
Vin(t) of the electrical power Ein(t) to a voltage value Vsuppiy(t) of the
electrical power
Esuppiy(t) supplied to the plurality of AMIs 330 on the power supply lines
340.
[0070] The substation 530 may include a transformer (not shown), such as,
for
example, a load tap change (LTC) transformer. In this regard, the substation
530 may
further include an automatic tap changer mechanism (not shown), which is
configured
to automatically change the taps on the LTC transformer. The tap changer
mechanism may change the taps on the LTC transformer either on-load (on-load
tap
changer, or OLTC) or off-load, or both. The tap changer mechanism may be motor
driven and computer controlled. The substation 530 may also include a
buck/boost
transformer to adjust and maximize the power factor of the electrical power
EDetivered(t) supplied to the users on power supply lines 340.
[0071] Additionally (or alternatively), the substation 530 may include one
or more
voltage regulators, or other voltage controlling equipment, as known by those
having
ordinary skill in the art, that may be controlled to maintain the output the
voltage
component Vsuppiy(t) of the electrical power Esuppiy(t) at a predetermined
voltage value
or within a predetermined range of voltage values.
[0072] The substation 530 receives the energy delivery parameters CED from
the
EC system 400 on the communication link 430. The energy delivery parameters
CED
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may include, for example, load tap coefficients when an LTC transformer is
used to
step-down the input voltage component Vin(t) of the electrical power E1(t) to
the
voltage component Vsuppiy(t) of the electrical power Esuppiy(t) supplied to
the ED
system 300. In this regard, the load tap coefficients may be used by the ER
system
500 to keep the voltage component Vsuppiy(t) on the low-voltage side of the
LTC
transformer at a predetermined voltage value or within a predetermined range
of
voltage values.
[0073] The LTC transformer may include, for example, seventeen or more
steps
(thirty-five or more available positions), each of which may be selected based
on the
received load tap coefficients. Each change in step may adjust the voltage
component
Vsuppiy(t) on the low voltage side of the LTC transformer by as little as, for
example,
about five-sixteenths (0.3%), or less.
[0074] Alternatively, the LTC transformer may include fewer than seventeen
steps. Similarly, each change in step of the LTC transformer may adjust the
voltage
component Vs/(t) on the low voltage side of the LTC transformer by more than,
for
example, about five-sixteenths (0.3%).
[0075] The voltage component Vsuppiy(t) may be measured and monitored on
the
low voltage side of the LTC transformer by, for example, sampling or
continuously
measuring the voltage component Vsuppiy(t) of the stepped-down electrical
power
Esuppiy(t) and storing the measured voltage component Vsuppiy(t) values as a
function of
time t in a storage (not shown), such as, for example, a computer readable
medium.
The voltage component Vsuppiy(t) may be monitored on, for example, a
substation
distribution bus, or the like. Further, the voltage component Vsuppiy(t) may
be
measured at any point where measurements could be made for the transmission or
distribution systems in the ER system 500.
[0076] Similarly, the voltage component Vin(t) of the electrical power
E1(t) input
to the high voltage side of the LTC transformer may be measured and monitored.
Further, the current component Is/(t) of the stepped-down electrical power
Esuppiy(t)
and the current component I1(t) of the electrical power E1(t) may also be
measured
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and monitored. In this regard, a phase difference Tin(t) between the voltage
Vin(t) and
current I1(t) components of the electrical power E1(t) may be determined and
monitored. Similarly, a phase difference (mu/4*(0 between the voltage
Vsuppiy(t) and
current Isuppiy(t) components of the electrical energy supply Esuppiy(t) may
be
determined and monitored.
[0077] The ER system 500 may provide electrical energy supply status
information to the EC system 400 on the communication links 430 or 510. The
electrical energy supply information may include the monitored voltage
component
Vsuppiy(t). The electrical energy supply information may further include the
voltage
component Vin(t), current components Iin(t), Isuppiy(t), and/or phase
difference values
(PIn(t), (PSupp1y(0, as a function of time t. The electrical energy supply
status
information may also include, for example, the load rating of the LTC
transformer.
[0078] The electrical energy supply status information may be provided to
the EC
system 400 at periodic intervals of time, such as, for example, every second,
5 sec., 10
sec., 30 sec., 60 sec., 120 sec., 600 sec., or any other value within the
scope and spirit
of the disclosure, as determined by one having ordinary skill in the art. The
periodic
intervals of time may be set by the EC system 400 or the ER system 500.
Alternatively, the electrical energy supply status information may be provided
to the
EC system 400 or ER system 500 intermittently.
[0079] Further, the electrical energy supply status information may be
forwarded
to the EC system 400 in response to a request by the EC system 400, or when a
predetermined event is detected. The predetermined event may include, for
example,
when the voltage component Vsuppiy(t) changes by an amount greater (or less)
than a
defined threshold value Vsupptyihreshozd (for example, 130V) over a
predetermined
interval of time, a temperature of one or more components in the ER system 500
exceeds a defined temperature threshold, or the like.
ED SYSTEM 300
[0080] The ED system 300 includes a plurality of AMIs 330. The ED system
300
may further include at least one collector 350, which is optional. The ED
system 300
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may be coupled to the network 170 by means of a communication link 310. The
collector 350 may be coupled to the plurality of AMIs 330 by means of a
communication link 320. The AMIs 330 may be coupled to the ER system 500 by
means of one or more power supply lines 340, which may also include
communication links.
[0081] Each AMI 330 is configured to measure, store and report energy usage
data by the associated users 150, 160 (shown in FIG. 1). Each AMI 330 is
further
configured to measure and determine energy usage at the users 150, 160,
including
the voltage component VAietõ(t) and current component tvietõ(t) of the
electrical power
Emeter(t) used by the users 150, 160, as a function of time. The AMIs 330 may
measure the voltage component Vmeter(t) and current component tvieter(t) of
the
electrical power Emeter(t) at discrete times 6, where s is a sampling period,
such as, for
example, s = 5 sec., 10 sec., 30 sec., 60 sec., 300 sec., 600 sec., or more.
For
example, the AMIs 330 may measure energy usage every, for example, minute (t60
sec), five minutes (600 sec), ten minutes (t600 sec), or more, or at time
intervals variably
set by the AMI 330 (for example, using a random number generator).
[0082] The AMIs 330 may average the measured voltage Vmeter(0 and/or
Imeter(t)
values over predetermined time intervals (for example, 5 min., 10 min., 30
min., or
more). The AMIs 330 may store the measured electrical power usage Emeter(t),
including the measured voltage component VAieter(t) and/or current component
tvieter(t)
as AMI data in a local (or remote) storage (not shown), such as, for example,
a
computer readable medium.
[0083] Each AMI 330 is also capable of operating in a "report-by-exception"
mode for any voltage Villeter(t) 5 current Imeter(t), or energy usage
Emeter(t) that falls
outside of a target component band. The target component band may include, a
target
voltage band, a target current band, or a target energy usage band. In the
"report-by-
exception" mode, the AMI 330 may sua sponte initiate communication and send
AMI
data to the EC system 400. The "report-by-exception" mode may be used to
reconfigure the AMIs 330 used to represent, for example, the lowest voltages
on the
circuit as required by changing system conditions.
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[0084] The AMI data may be periodically provided to the collector 350 by
means
of the communication links 320. Additionally, the AMIs 330 may provide the AMI
data in response to a AMI data request signal received from the collector 350
on the
communication links 320.
[0085] Alternatively (or additionally), the AMI data may be periodically
provided
directly to the EC system 400 (for example, the MAS 460) from the plurality of
AMIs, by means of, for example, communication links 320, 410 and network 170.
In
this regard, the collector 350 may be bypassed, or eliminated from the ED
system
300. Furthermore, the AMIs 330 may provide the AMI data directly to the EC
system
400 in response to a AMI data request signal received from the EC system 400.
In the
absence of the collector 350, the EC system (for example, the MAS 460) may
carry
out the functionality of the collector 350 described herein.
[0086] The request signal may include, for example, a query (or read)
signal and a
AMI identification signal that identifies the particular AMI 330 from which
AMI data
is sought. The AMI data may include the following information for each AMI
330,
including, for example, kilo-Watt-hours (kWh) delivered data, kWh received
data,
kWh delivered plus kWh received data, kWh delivered minus kWh received data,
voltage level data, current level data, phase angle between voltage and
current, kVar
data, time interval data, demand data, and the like.
[0087] Additionally, the AMIs 330 may send the AMI data to the meter
automation system server MAS 460. The AMI data may be sent to the MAS 460
periodically according to a predetermined schedule or upon request from the
MAS
460.
[0088] The collector 350 is configured to receive the AMI data from each of
the
plurality of AMIs 330 via the communication links 320. The collector 350
stores the
received AMI data in a local storage (not shown), such as, for example, a
computer
readable medium (e.g., a non-transitory computer readable medium). The
collector
350 compiles the received AMI data into a collector data. In this regard, the
received
AMI data may be aggregated into the collector data based on, for example, a
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geographic zone in which the AMIs 330 are located, a particular time band (or
range)
during which the AMI data was collected, a subset of AMIs 330 identified in a
collector control signal, and the like. In compiling the received AMI data,
the
collector 350 may average the voltage component VAietõ(t) values received in
the AMI
data from all (or a subset of all) of the AMIs 330.
[0089] The EC system 400 is able to select or alter a subset of all of the
AMIs 330
to be monitored for predetermined time intervals, which may include for
example 15
minute intervals. It is noted that the predetermined time intervals may be
shorter or
longer than 15 minutes. The subset of all of the AMIs 330 is selectable and
can be
altered by the EC system 400 as needed to maintain minimum level control of
the
voltage Vsuppiy(t) supplied to the AMIs 330.
[0090] The collector 350 may also average the electrical power Emeter(t)
values
received in the AMI data from all (or a subset of all) of the AMIs 330. The
compiled
collector data may be provided by the collector 350 to the EC system 400 by
means of
the communication link 310 and network 170. For example, the collector 350 may
send the compiled collector data to the MAS 460 (or ROC 490) in the EC system
400.
[0091] The collector 350 is configured to receive collector control signals
over the
network 170 and communication link 310 from the EC system 400. Based on the
received collector control signals, the collector 350 is further configured to
select
particular ones of the plurality of AMIs 330 and query the meters for AMI data
by
sending a AMI data request signal to the selected AMIs 330. The collector 350
may
then collect the AMI data that it receives from the selected AMIs 330 in
response to
the queries. The selectable AMIs 330 may include any one or more of the
plurality of
AMIs 330. The collector control signals may include, for example, an
identification
of the AMIs 330 to be queried (or read), time(s) at which the identified AMIs
330 are
to measure the Villeter(t) 5 bleter4 E Aleter(t) and/or Tilleter(t)
(TAleter(t) is the phase
difference between the voltage Vmeter(t) and current Imeter(t) components of
the
electrical power EMeter(t) measured at the identified AMI 330), energy usage
information since the last reading from the identified AMI 330, and the like.
The
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collector 350 may then compile and send the compiled collector data to the MAS
460
(and/or ROC 490) in the EC system 400.
EC SYSTEM 400
[0092] The EC system 400 may communicate with the ED system 300 and/or ER
system 500 by means of the network 170. The EC system 400 is coupled to the
network 170 by means of one or more communication links 410. The EC system 400
may also communicate directly with the ER system 500 by means of a
communication link 430.
[0093] The EC system 400 includes the MAS 460, a database (DB) 470, a
distribution management system (DMS) 480, and a regional operation center
(ROC)
490. The ROC 490 may include a computer (ROC computer) 495, a server (not
shown) and a database (not shown). The MAS 460 may be coupled to the DB 470
and DMS 480 by means of communication links 420 and 440, respectively. The
DMS 480 may be coupled to the ROC 490 and ER SYSTEM 500 by means of the
communication link 430. The database 470 may be located at the same location
as
(for example, proximate to, or within) the MAS 460, or at a remote location
that may
be accessible via, for example, the network 170.
[0094] The EC system 400 is configured to de-select, from the subset of
monitored AMIs 330, a AMI 330 that the EC system 400 previously selected to
monitor, and select the AMI 330 that is outside of the subset of monitored
AMIs 330,
but which is operating in the report-by-exception mode. The EC system 400 may
carry out this change after receiving the sua sponte AMI data from the non-
selected
AMI 330. In this regard, the EC system 400 may remove or terminate a
connection to
the de-selected AMI 330 and create a new connection to the newly selected AMI
330
operating in the report-by-exception mode. The EC system 400 is further
configured
to select any one or more of the plurality of AMIs 330 from which it receives
AMI
data comprising, for example, the lowest measured voltage component Vueter,-,
(1-15 and
m
generate an energy delivery parameter CED based on the AMI data received from
the
AMI(s) 330 that provide the lowest measured voltage component V
Aleter(t).
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[0095] The MAS 460 may include a computer (not shown) that is configured to
receive the collector data from the collector 350, which includes AMI data
collected
from a selected subset (or all) of the AMIs 330. The MAS 460 is further
configured
to retrieve and forward AMI data to the ROC 490 in response to queries
received
from the ROC 490. The MAS 460 may store the collector data, including AMI data
in a local storage and/or in the DB 470.
[0096] The DMS 480 may include a computer that is configured to receive the
electrical energy supply status information from the substation 530. The DMS
480 is
further configured to retrieve and forward measured voltage component Vu
meter,-,
values and electrical power EAkter(t) values in response to queries received
from the
ROC 490. The DMS 480 may be further configured to retrieve and forward
measured
current component tvieter(t) values in response to queries received from the
ROC 490.
The DMS 480 also may be further configured to retrieve all "report-by-
exception"
voltages Vmeter(t) from the AMIs 330 operating in the "report-by-exception"
mode and
designate the voltages Vu (1-1 as one of the control points to be continuously
read at
meter,-,
predetermined times (for example, every 15 minutes, or less (or more), or at
varying
times). The "report-by-exception voltages VMeter(t) may be used to control the
EC
500 set points.
[0097] The DB 470 may include a plurality of relational databases (not
shown).
The DB 470 includes a large number of records that include historical data for
each
AMI 330, each collector 350, each substation 530, and the geographic area(s)
(including latitude, longitude, and altitude) where the AMIs 330, collectors
350, and
substations 530 are located.
[0098] For instance, the DB 470 may include any one or more of the
following
information for each AMI 330, including: a geographic location (including
latitude,
longitude, and altitude); a AMI identification number; an account number; an
account
name; a billing address; a telephone number; a AMI type, including model and
serial
number; a date when the AMI was first placed into use; a time stamp of when
the
AMI was last read (or queried); the AMI data received at the time of the last
reading;
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a schedule of when the AMI is to be read (or queried), including the types of
information that are to be read; and the like.
[0099] The historical AMI data may include, for example, the electrical
power
EMeter(t) used by the particular AMI 330, as a function of time. Time t may be
measured in, for example, discrete intervals at which the electrical power
EMeter
magnitude (kWh) of the received electrical power EMeter(t) is measured or
determined
at the AMI 330. The historical AMI data includes a measured voltage component
V,vieter(t) of the electrical energy EMeter(t) received at the AMI 330. The
historical AMI
data may further include a measured current component Imeter(t) and/or phase
difference (Pivkter(0 of the electrical power EMeter(t) received at the AMI
330.
[00100] As noted earlier, the voltage component VMeter(t) may be measured at a
sampling period of, for example, every five seconds, ten seconds, thirty
seconds, one
minute, five minutes, ten minutes, fifteen minutes, or the like. The current
component
Imeter(t) and/or the received electrical power EMeter(t) values may also be
measured at
substantially the same times as the voltage component V
meter(t).
[00101] Given the low cost of memory, the DB 470 may include historical data
from the very beginning of when the AMI data was first collected from the AMIs
330
through to the most recent AMI data received from the AMI 330.
[00102] The DB 470 may include a time value associated with each measured
voltage component V
Meter(05 current component IMeter(t), phase component m
T Meter(t)
and/or electrical power Emeter(t), which may include a timestamp value
generated at
the AMI 330. The timestamp value may include, for example, a year, a month, a
day,
an hour, a minute, a second, and a fraction of a second. Alternatively, the
timestamp
may be a coded value which may be decoded to determine a year, a month, a day,
an
hour, a minute, a second, and a fraction of a second, using, for example, a
look up
table. The ROC 490 and/or AMIs 330 may be configured to receive, for example,
a
WWVB atomic clock signal transmitted by the U.S. National Institute of
Standards
and Technology (NIST), or the like and synchronize its internal clock (not
shown) to
the WWVB atomic clock signal.
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[00103] The historical data in the DB 470 may further include historical
collector
data associated with each collector 350. The historical collector data may
include any
one or more of the following information, including, for example: the
particular AMIs
330 associated with each collector 350; the geographic location (including
latitude,
longitude, and altitude) of each collector 350; a collector type, including
model and
serial number; a date when the collector 350 was first placed into use; a time
stamp of
when collector data was last received from the collector 350; the collector
data that
was received; a schedule of when the collector 350 is expected to send
collector data,
including the types of information that are to be sent; and the like.
[00104] The historical collector data may further include, for example, an
external
temperature value Tcottector(t) measured outside of each collector 350 at time
t. The
historical collector data may further include, for example, any one or more of
the
following for each collector 350: an atmospheric pressure value Pcouector(t)
measured
proximate the collector 350 at time t; a humidity value Hcouector(t) measured
proximate the collector 350 at time t; a wind vector value Wcollector(t)
measured
proximate the collector 350 at time t, including direction and magnitude of
the
measured wind; a solar irradiant value Lcollector(t) (kW/m2) measured
proximate the
collector 350 at time t; and the like.
[00105] The historical data in the DB 470 may further include historical
substation
data associated with each substation 530. The historical substation data may
include
any one or more of the following information, including, for example: the
identifications of the particular AMIs 330 supplied with electrical energy
Esuppiy(t) by
the substation 530; the geographic location (including latitude, longitude,
and altitude)
of the substation 530; the number of distribution circuits; the number of
transformers;
a transformer type of each transformer, including model, serial number and
maximum
Megavolt Ampere (MVA) rating; the number of voltage regulators; a voltage
regulator type of each voltage regulator, including model and serial number; a
time
stamp of when substation data was last received from the substation 530; the
substation data that was received; a schedule of when the substation 530 is
expected
to provide electrical energy supply status information, including the types of
information that are to be provided; and the like.
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[00106] The historical substation data may include, for example, the
electrical
power Esuppiy(t) supplied to each particular AMI 330, where Esuppiy(t) is
measured or
determined at the output of the substation 530. The historical substation data
includes
a measured voltage component Vsuppiy(t) of the supplied electrical power
Esuppiy(t),
which may be measured, for example, on the distribution bus (not shown) from
the
transformer. The historical substation data may further include a measured
current
component Isuppty(t) of the supplied electrical power Esuppiy(t). As noted
earlier, the
voltage component Vs/(t), the current component Is/(t), and/or the electrical
power Esuppiy(t) may be measured at a sampling period of, for example, every
five
seconds, ten seconds, thirty seconds, a minute, five minutes, ten minutes, or
the like.
The historical substation data may further include a phase difference value
Tsuppiy(t)
between the voltage Vs/(t) and current Isuppiy(t) signals of the electrical
power
Esuppiy(t), which may be used to determine the power factor of the electrical
power
Esuppiy(t) supplied to the AMIs 330.
[0107] The historical substation data may further include, for example,
the
electrical power Ein(t) received on the line 520 at the input of the
substation 530,
where the electrical power E1(t) is measured or determined at the input of the
substation 530. The historical substation data may include a measured voltage
component Vin(t) of the received electrical power Ein(t), which may be
measured, for
example, at the input of the transformer. The historical substation data may
further
include a measured current component I1(t) of the received electrical power
Ein(t).
As noted earlier, the voltage component Vin(t), the current component I/n(t),
and/or
the electrical power Ein(t) may be measured at a sampling period of, for
example,
every five seconds, ten seconds, thirty seconds, a minute, five minutes, ten
minutes,
or the like. The historical substation data may further include a phase
difference
Tin(t) between the voltage component Vin(t) and current component I1(t) of the
electrical power Ein(t). The power factor of the electrical power Ein(t) may
be
determined based on the phase difference Tin(t).
[0108] According to an aspect of the disclosure, the EC system 400 may save
aggregated kW data at the substation level, voltage data at the substation
level, and
weather data to compare to energy usage per AMI 330 to determine the energy
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savings from the VCC system 200, and using linear regression to remove the
effects
of weather, load growth, economic effects, and the like, from the calculation.
[0109] In the VCC system 200, control may be initiated from, for example, the
ROC computer 495. In this regard, a control screen 305 may be displayed on the
ROC computer 495, as shown, for example, in FIG. 3 of the US 2013/0030591
publication. The control screen 305 may correspond to data for a particular
substation 530 (for example, the TRABUE SUBSTATION) in the ER system 500.
The ROC computer 495 can control and override (if necessary), for example, the
substation 530 load tap changing transformer based on, for example, the AMI
data
received from the ED system 300 for the users 150, 160. The ED system 300 may
determine the voltages of the electrical power supplied to the user locations
150, 160,
at predetermined (or variable) intervals, such as, e.g., on average each 15
minutes,
while maintaining the voltages within required voltage limits.
[0110] For system security, the substation 530 may be controlled through
the
direct communication link 430 from the ROC 490 and/or DMS 480, including
transmission of data through communication link 430 to and from the ER 500,
EUS
300 and EVP 600.
[0111] Furthermore, an operator can initiate a voltage control program on
the
ROC computer 490, overriding the controls, if necessary, and monitoring a time
it
takes to read the user voltages Vueter,-, (1-1 being used for control of, for
example, the
m
substation LTC transformer (not shown) in the ER system 500.
EVP SYSTEM 600
[0112] FIG. 3 of the co-pending /P006 application shows an example energy
validation process 600 for determining the amount of conservation in energy
per
customer realized by operating the VCC system in FIGS. 1-2 of the present
application. The process is started 601 and the data the ON and OFF periods is
loaded 602 by the process manager. The next step is to collect 603 the hourly
voltage and power (MW) data from the metering data points on the VCC system
from the DMS 480 which may be part of a supervisory control and data
acquisition
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(SCADA) type of industrial control system. Next the corresponding weather data
is
collected 604 for the same hourly conditions. The data is processed 605, 606,
607,
608 to improve its quality using filters and analysis techniques to eliminate
outliers
that could incorrectly affect the results, as describe further below. If
hourly pairing
is to be done the hourly groups are determined 609 using the linear regression
techniques. The next major step is to determine 611, 612, 613, 614, 615, 616,
617
the optimal pairing of the samples, as described further below.
EPP SYSTEM 1700
[0113] FIG. 2 also shows an example of the EPP system 1700 applied to a
distribution circuit, that also may include the VCC system 200 and the EVP
system
600, as discussed previously. The EPP system 1700 collects the historic energy
and
voltage data from the AMI system from database 470 and/or the distribution
management systems (DMS) 480 and combines this with the CVR factor analysis
from the EVP system 600 (discussed in detail in the co-pending /P006
application) to
produce a robust planning process (EPP system 1700) for correcting problems
and
improving the capability of the VCC system 200 to increase the energy
efficiency
and demand reduction applications.
[0114] FIG. 3 shows the overview of the breakdown of the approach to the
EPP system 1700. The ESS 800 supplies energy and voltage from fixed points
tied
to the transmission and generation sources on the ESS 800. The EEDCS 1000
connects the ESS 800 to the EUS 900 with primary and secondary electrical
connections, typical to electric distribution systems. The AMI meters 330 of
AMI
system measure both the inputs from the ESS 800 in energy and voltage and the
inputs to the EUS 900 in energy and voltage. As show in FIG. 3, the energy
losses in
the EEDCS 1000 can be linearized based on the voltage drop from the ESS 800 to
the EUS 900, as represented by the equation: Vs ¨ VAMI = BEEDCS X PLossEEDCS,
where
Vs is the ESS voltage, VAm1 is the EUS voltage (as measured by AMI 330),
BEEDCS
represents the slope of the linear regression, and PLossEEDCS represents the
loss energy
losses in the EEDCS 1000. Similarly, the energy "loss" in an EUS 900 (e.g.,
the
difference in energy between when the load is in the ON and OFF states) can be
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linearized based on the voltage difference between a measurement in the load-
ON
state and a measurement in the load-OFF state, as represented by the equation:
VAmk. ¨ VAMIoff ¨ BEUS X PLossEUS, where VIon -S Am i the EUS voltage in the
ON state,
VAmioff is the EUS voltage in the OFF state, BEus represents the slope of the
linear
regression, and PLossEUS represents the difference in energy between the load-
ON and
load-OFF states. The percentage of energy loss in the EEDCS 1000 that can be
controlled is orders of magnitude lower that the percentage of energy loss on
the
EUS 900 that can be controlled. As an example. on the distribution system the
EEDCS 1000 losses are less than 5% of the total and the losses on the EUS 900
are
more than 95% of the total.
[0115] Using these principles, and the relationship in ESS 800 voltages and
EUS 900 voltages, a performance criteria definition can be derived to allow
full
optimization of the EEDCS 1000 design based on the independent variables.
Based
on the linearization of the power and voltage relationships, this enables
optimization
on a near radial EEDCS 1000 which can be formulated as a search of the
boundary
conditions of the linear optimization problem.
[0116] FIG. 4 describes the planning variables and measurement systems that
are used to build the EPP system 1700 and provide the input for the voltage
optimization design. The top boxes denote each of the systems within the EEDS
700, e.g., ESS 800, EEDCS 1000, EUS 900 and ED system 300. The list below each
of the boxes include examples of controllable planning elements that may be
optimized and provided for cost/benefit analysis using the EPP system 1700.
The
cost/benefit analysis can be included in the optimization or the list of
modifications
from the voltage optimization can be broken into a prioritized list of project
modifications to be evaluated in sequence by cost/benefit. The AMI meter
points
330 denote the locations at which measurements are taken that are used to
formulate
the model and the data needed for the optimization calculations.
[0117] The chart 1750 in FIG. 5 shows how the voltage data from the ESS
800 is related to the AMI-measured voltage data of each EUS 900. The
linearization
technique (described with respect to FIGs. 7-10) used to create the chart 1750
is an
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important aspect of the disclosed embodiments. The ability of the EPP system
1700
to use a simple linearization technique to relate the source (e.g., ESS)
voltage and
delivery (e.g., EUS) voltage, creates an efficient method to calculate the
voltage
ranges available based on variations of ESS and EUS load data forecast by the
EEDS
system 700 owners. This method also enables the application of a novel linear
optimization process that can quickly evaluate various changes to the EEDCS
1000
and document the resulting change in voltage range capability.
[0118] FIG. 6 shows a method used to model the system to relate the simple
linear model to the potential changes identified by the EPP system 1700. For
each
proposed system modification, the linear model is changed to represent the
effect of
the modification on the system. For example, if a proposed system modification
is to
add an additional capacitor to the transmission line at location As of the
system, this
could be modeled by changing the appropriate variables at location Am of the
model.
With this new representation, the system is evaluated by the EPP system 1700
to
determine if the proposed modification results in additional voltage range.
This
additional voltage range can be used with the determined CVR factor capacity
to
calculate the energy savings and the demand savings based on the forecasted
ESS
loads to determine a combined energy improvement effect of the proposed system
modification. The EPP system 1700 performs the evaluations over 24 hour
intervals
of one hour up to yearly intervals of 8760 hour intervals. This gives the
ability to
optimize the number and priority of the modification projects and search the
solutions for the optimum combination of the modifications to the EEDS 700.
[0119] FIGs. 7-10 show a linearization example for one ESS 800 and EUS
900 element in an actual system. As can be seen in FIG. 7 the ESSDATA is the
AMI
data from the ESS 800 and the EUSDATA is the AMI data from the EUS. This data
(ESSDATA and EUSDATA) is used to perform the evaluation. Specifically, ESSDATA
can be used, as is known to one of skill in the art, to determine the value of
ESS Current
and DeltaV is Vs ¨ VAMI. Using the equation shown in FIG. 5 (V = IR+B, where V
is DeltaV, I is ESScurrent), a linear regression calculation can solve for the
slope (R)
and the intercept (B) of the best line fit to the data (see, FIG. 10). In this
example,
the linear regression equation for the data is Vs ¨ VAmI = 12.9(ESScurrent) ¨
1.17.
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[0120] FIG. 8 shows that 88 to 89 % of the variation in voltage drop from
ESS
to EUS can be explained by the linear technique (e.g., the R2 value is 88.3%,
which
describe how well the regression line fits the set of data). In addition, the
remaining
residual represents the normalized variation at the EUS that is characteristic
of the
"ON" and "OFF" nature of the load switching occurring at the EUS. This
characterization of the EUS is critical to an efficient method of planning the
distribution secondary voltage performance and tracking its reliability. FIGs.
9 and
10 show the calculations for how well the model represents the 24 hour
performance
of the EUS. This is consistent to within one half volt and the residuals are
highly
normalized. This gives a great view into characterizing "normal" EUS behavior
as
well as measuring abnormal EUS behavior. The system is an excellent model to
be
implemented in the EPP system 1700.
[0121] FIG. 11 is a flow diagram showing the energy planning process 1500
(e.g., a voltage planning process) implemented by the EPP system 1700. The
process starts with reading three major blocks of data at step 1501: AMI data,
ESS
data, and CVR factor data. As indicated previously, the AMI data is measured
voltage data from EUS 900, the ESS data is measured voltage data from ESS 800
and the CVR factor is calculated by EVP 600. Then historical AMI data and
historical ESS data are input, for example, from database 470 at step 1502.
[0122] The linearization model, as discussed above with respect to FIGs. 7-
10,
is built at step 1503. At step 1504, the data read-in by the process and the
forecast of
energy use at the ESS are used to determine the range of voltage operation and
identify the normal outliers (e.g., voltages not within limits). If any
voltages are
outside of normal limits, these are resolved by the traditional planning
process (e.g.,
traditional field resolution methods) at step 1505.
[0123] The next step 1506 is to identify any patterns of voltages denoting
specific problems impacting voltage reliability, in accordance with this
disclosure.
Examples of problems which create recognizable patterns in the linearization
process
comparison include a poor connection between a meter and a meter base, an
overloaded secondary conductor, an overloaded secondary transformer, an
incorrect
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transformer tap setting, an incompatible type of meter connected in a meter
base, and
a bad neutral connection. These can be identified, for example, as a data
point lying
outside of the linear regression (see e.g., point X on chart 1750 of FIG. 5).
Once the
problems are identified, they are put into the project process to resolve
first at step
1507. Once resolved, the corrected linearization model is used to calculate
the new
range of performance using the CVR factor, at step 1508. If the determined
savings
is satisfactory for the next operating period (step 1509), the process moves
to the
next step 1510. If not the linearization model is run again with tighter
tolerances
(e.g. returns to step 1504) and the process is repeated until the targeted
energy
improvement is derived.
[0124] The final step 1510 is to choose a new set of initial meters for
monitoring and/or to configure the VCC 200 to operate with the new level of
system
performance forecasted by the EPP 1700. This information is then supplied to
the
VCC 200 and the EVP 600 to configure the controls over the next operating
period.
[0125] FIG. 12 shows an example of the display for the outlier
identification
(see, chart 1620) and some potential problems that may be identified from this
step
in the process. FIG. 13 shows the display screen that transfers the AMI data
analysis
to a geographic one line chart that can be used by the planner to determine
the best
combination of modifications at the secondary level or EUS level without
having to
do a detailed secondary model. The information can also be combined with
various
GIS representations to give the planning key information for selecting the
best group
of circuit modifications to optimize the performance of the voltage.
[0126] FIG. 14 illustrates the final step in the EPP process 1700, where
the
new meter information and the modifications are translated into the control
information used by the EPP system 1700 by identifying which meters are
associated with each block and zone of the control. Each "zone" refers to all
AMIs
330 downstream of a regulator and upstream of the next regulator (e.g., LTC,
regulator) and each "block" refers to areas within the sphere of influence of
features
of the distribution system (e.g., a specific capacitor). In the example shown
in FIG.
14, the LTC Zone includes all AMIs 330 downstream of the LTC and upstream of
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regulator 1402 (e.g., the AMIs 330 in B1 and B2), the Regulator Zone includes
all
AMIs 330 downstream of regulator 1402 (e.g., the AMIs 300 in B3), and Block 2
(B2) includes all AMIs 330 within the influence (upstream or downstream) of
capacitor 1403. This new meter and modification information, along with
detailed configuration information (zone/block information), is provided by
the EPP
system 1700 to the VCC 200 to allow clear implementation of the control with
the
new modifications in place.
[0127] FIG. 15 shows an example of the final file for configuring the
initial
set of meters for monitoring in CVR, using the EPP system 1700. The
recommended
set is given by the EPP system 1700. However, the user may be allowed to
change
this recommended set if additional considerations, such as critical customers
or other
criteria, override the automatic selection process inside the EPP system 1700.
This
final configuration is then transferred directly to the VCC configuration file
for
implementation.
[0128] While the disclosure has been described in terms of exemplary
embodiments, those skilled in the art will recognize that the disclosure can
be
practiced with modifications in the spirit and scope of the appended claims.
These
examples are merely illustrative and are not meant to be an exhaustive list of
all
possible designs, embodiments, applications or modifications of the
disclosure.
