Note: Descriptions are shown in the official language in which they were submitted.
CA 02689776 2010-01-07
CROSS REFERENCE TO RELATED APPLICATION: This application is a continuation
in part of US patent application serial no. 12/172,112 filed July 11, 2008,
the entirety of
which is incorporated herein by reference.
TITLE: System for Accurately Detecting Electricity Theft
FIELD OF THE INVENTION
The invention relates generally to methods for monitoring an electric
distribution
network and for detecting the theft of electricity.
BACKGROUND OF THE INVENTION
With rising energy prices, concerns about the environment, and an increased
emphasis on energy conservation, there has been an increased interest in the
detection
and prevention of electricity theft. Theft directly from a high voltage feeder
can be done
by the unauthorized installation of a non-utility owned distribution
transformer on the
feeder. The utility would not necessarily know about the existence of such a
transformer and thus a comparison between energy supplied by the utility owned
distribution transformers and the energy consumed by the end-users would not
detect
this kind of electricity theft. To detect this kind of theft, it is necessary
to measure
consumption at the feeder level. A feeder meter, according to the state of the
art,
measures energy supplied by the feeder. This requires multiplying voltage and
current
to determine power and integrating the power over a period of time to
determine
energy. Theft could be detected by comparing the energy supplied by the feeder
with
CA 02689776 2010-01-07
the energy supplied by the distribution transformers on that feeder. A major
disadvantage of this approach is that the feeder meter must be designed and
built for
high voltage operation. High voltage devices are expensive and depending on
the
design, can be hazardous to install. Furthermore, voltage drops occur in every
feeder
due to current flow and line resistance, and these voltage drops are a source
of
measurement error in the comparison. Increased measurement error means that
more
feeder meters are needed for a given number of distribution transformers in
order to be
able to distinguish between measurement error and theft.
Configuration information is an important input to the theft detection
equations.
It is necessary to know which end-users are connected to which distribution
transformers, and to know which distribution transformers are associated with
which
feeder meters and how. The traditional method of maintaining configuration
information
is to develop a series of maps showing the distribution system components and
how
they are interconnected. This is an expensive labour intensive process, and
often
these maps are not kept up-to-date.
SUMMARY OF THE INVENTION
In accordance with one aspect of the present invention, there is provided a
method of monitoring an electrical network of the type having a feeder line
connected to
a plurality of distribution transformers, each distribution transformer being
in turn
coupled to a load. The method includes the steps of recording an accumulated
in-
phase current at each of the distribution transformers over a time period and
recording
for the same time period an accumulated in-phase current at the feeder line.
The sum
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of the accumulated in-phase currents recorded at the distribution transformers
are then
compared to the accumulated in-phase current recorded at the feeder line.
In accordance with another aspect of the invention there is provided a method
of
monitoring an electrical network having a feeder line connected to a plurality
of
distribution transformers which are in turn connected to at least one customer
meter.
The method includes the steps of recording an accumulated in-phase current at
the
feeder line for a time period and, for the same time period, recording an
accumulated
in-phase current at each of the customer meters. The accumulated in-phase
current
recorded at the feeder line is then compared to a sum of the accumulated in-
phase
currents recorded at the customer meters.
In accordance with another aspect of the invention there is provided a method
of
monitoring an electrical network having a distribution transformer connected
to at least
one customer meter, the method including the steps of recording an accumulated
in-
phase current at the distribution transformer and at each of the customer
meters. The
method further includes the step of comparing the accumulated in-phase current
recorded at the distribution transformer with the sum of the accumulated in-
phase
currents recorded at the customer meters.
With the foregoing in view, and other advantages as will become apparent to
those skilled in the art to which this invention relates as this specification
proceeds, the
invention is herein described by reference to the accompanying drawings
forming a part
hereof, which includes a description of the preferred typical embodiment of
the
principles of the present invention.
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DESCRIPTION OF THE DRAWINGS
Figure 1 is a schematic view of an electricity network implementing the method
of the
present invention.
Figure 2 is a schematic view of an electricity network implementing the method
of the
present invention and showing the relationship of end users (EUs) to
distribution
transformers (DTs).
In the drawings like characters of reference indicate corresponding parts in
the
different figures.
DETAILED DESCRIPTION OF THE INVENTION
Energy accounting as a method of detecting electricity theft can be very
effective
at the distribution transformer level because of the small number of customers
involved.
Errors due to line losses may be 0.5% to 3% and the number of customers may be
no
more than ten. In this case the total amount of energy lost to the lines would
amount to
no more than a fraction of the amount used by a single customer, and an even
smaller
fraction of the amount likely to be involved in any theft.
At the feeder level, the situation is different because many more customers
are
involved. Here the energy lost in the lines is likely to be many times greater
than the
amount used by a single customer. Thus, the detection of theft is more
difficult, and the
sensitivity and reliability of the method is heavily dependent on the accuracy
of the
energy accounting process.
An improvement in the accuracy of the energy accounting process can be
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achieved by estimating the line losses and compensating for them, but there is
a
serious conceptual problem which limits the benefit that this can afford. The
problem is
that line losses are proportional to the square of the current level and
therefore vary
with load, and that's without even taking into account variable losses due to
line
resistance changing with temperature. This makes it very difficult to know
what these
losses are with sufficient accuracy.
For example, if we have a feeder which is supplying 100 Amps to a steady
unchanging load consisting of residential customers, the line losses might
amount to
1%. If, however, during one measurement interval, the load changes such that
half the
time the load is 200 Amps and the rest of the time the load is zero, the
result will be that
line losses during the measurement period are doubled. Instead of 1%, the line
losses
would be 2%. Since this change occurs within a measurement interval, it cannot
be
detected from the meter data.
For a feeder with 1000 customers, a change in line losses from 1% to 2%
represents a reduction of energy flow to customers, equivalent to ten times
the load of
an average customer.
There are a number of ways to cope with this. One can reduce the error by
reducing the measurement interval, but this increases the amount of data that
must be
transmitted and processed and doesn't totally solve the problem. One can
attempt to
depend on statistical averaging, but this only works most of the time. Thus
one is left
with a trade-off between sensitivity and the prevention of false alarms. If
the threshold
is set too low, there will be too many false alarms. If the threshold is set
too high,
actual theft will not be detected. In between these two levels will be a range
of
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threshold values which cause too many false alarms and fail to detect real
theft.
Thus, energy accounting as a method of theft detection has an inherent source
of error which is independent of accuracy of the instrumentation used. Even if
the
feeder meter(s), the distribution transformer meters, and the customer meters
were
totally error free, this method would still have a major source of error which
would limit
its sensitivity, and therefore its ability to detect electricity theft.
An alternative method which does not possess this source of error is to use
Accumulated In-Phase Current (AIPC). AIPC is simply the non-voltage component
of
energy, thus removing the voltage term from the equation. Since line losses
are
characterized by voltage losses rather than current losses, this method is
virtually
immune to the effect of line losses. This means that higher levels of overall
accuracy
can be achieved, which translates into greater sensitivity, and therefore a
greater ability
to detect theft, limited primarily by the metering accuracy. Thus, AIPC
provides a
measure for theft detection that is superior to the use of energy consumption
(kWh).
The term "feeder meter" is a general term for meters which measure electricity
at
the feeder level. A feeder current meter is a type of feeder meter which is
specifically
designed to measure feeder current. As such, it is ideally suited to the
measurement of
AIPC, and does not need to measure voltage, unlike other feeder meters.
In a system of feeder current meters (FCMs), distribution transformer meters
(DTMs) and customer meters (CMs), AIPC provides the best means for detecting
theft
as it is independent of varying line losses. One difficulty with this concept
is that CMs
generally do not provide AIPC data, and of course, AIPC cannot be compared
with
kWh. However, if DTMs are used, they can be programmed to provide both AIPC
and
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kWh. Then kWh can be used to reconcile between the DTMs and the CMs (where
small numbers of customers are involved) while AIPC is used to reconcile
between the
FCMs and the DTMs (where larger numbers of customers are involved).
In certain situations, such as rural areas where there is only one customer
per
transformer, it may be considered to be undesirable to deploy DTMs. In such a
case,
the customer meters could be supplied with the ability to transmit both the
energy
consumption reading, and the Accumulated In-Phase Current reading. The energy
consumption reading would be used for billing, while the AIPC reading would be
used
together with the feeder current meter reading to detect theft with greater
sensitivity and
reliability than would be possible using energy consumption data.
The most accurate approach, and the one which would be the most sensitive to
theft and least likely to generate false alarms, would be to add a true AIPC
capability to
the CMs. The problem with this is the amount of development required by the
meter
manufacturers to implement this capability. Nevertheless, by using the
existing
capability in the meter one could achieve a close approximation. The CMs in
addition
to transmitting the accumulated kWh for each one hour period would also
transmit the
maximum voltage and the minimum voltage. From this data one could determine
the
maximum possible AIPC and the minimum possible AIPC as follows:
Maximum AIPC = kWh / Minimum Voltage
Minimum AIPC = kWh / Maximum Voltage
To compare the AIPC at the feeder level with the AIPC at the transformer
secondary level,
it is necessary to account for the transformer transformation ratio which is
the primary side
voltage divided by the secondary side voltage. A simple way to do this is to
convert AIPC
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to normalized active energy or NAE by multiplying AIPC by the nominal voltage.
This is
done as follows:
NAE = normalized active energy = AIPC X nominal voltage
The theft alarm is triggered if the feeder current meter NAE minus the error
margin is greater than the sum of the NAE readings at the CMs. The sensitivity
of this
technique, in terms of the minimum theft load needed for detection, for each
one hour
period can be evaluated as follows:
Min Detectable Theft Load = Voltage X (Max AIPC - Min AIPC) + error margin
This technique will have the highest sensitivity during periods of constant
voltage, and yet during periods of changing voltage, false alarms will still
be minimized.
Since the targeted theft loads are base-load in nature, they should be readily
detectable during periods of high sensitivity. Furthermore, sensitivity can be
substantially enhanced during any one hour measurement period simply by
subdividing
the hour into five-minute measurement intervals. The sensitivity would then be
limited
by the amount of voltage change occurring during the five minutes. This is
likely to be
small in any normal situation, so that it should generally be possible to
maintain high
sensitivity at all times with this technique.
Since the sensitivity of any theft detection system varies inversely with the
number of customers, it is beneficial to use multiple FCMs on a feeder such
that each
FCM (feeder current meter) covers a different subset of the customers on that
feeder.
This will only work where the feeder branches into different sections. In this
case,
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different feeder meters can be installed on each branch. In cases where this
can be
done, there is still the problem that the line from the substation to the
first branch ~or
customer) would need to be protected, and yet on this line the number of
customers
cannot be subdivided. This section of line can be protected by two FCMs, one
at the
substation, and one just before the first customer, both of them measuring RMS
(root-
mean-squared) current. RMS current can be measured more accurately than kWh or
even AIPC because there is only one input into the measurement process.
Accuracy
can be further enhanced by calibrating two identical FCMs together, thus
giving this
section of line the best possible protection against theft.
The standard feeder current meter does not have a connection across high
voltage, but voltage information is needed to calculate kWh. A standard method
would
be to use a shielded resistive voltage divider or a potential transformer,
each method
having its own unique advantages and disadvantages. Both methods can provide
superior accuracy, but are expensive and inconvenient when accuracy is
required. An
alternative method is to measure the voltage on the secondary side of an
existing
distribution transformer and then multiply by the turns ratio.
This method could be implemented by a device which clamps onto the
distribution
transformer near the location of the feeder current meter (FCM). This device
would
measure voltage and current and combine them to produce voltage data for the
primary
side. This data would be continuously transmitted in real time, via short
range radio, to the
FCM which would use it to provide kWh data.
There are two main sources of error with this approach. The first is the
accuracy of
the turns ratio, and the second is the drop in voltage output as the
transformer is loaded.
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If the transformer meets the CSA specification, the turns ratio (rated high
voltage /
rated low voltage on nameplate) will be within +/- 0.5%. Also the transformer
impedance
(typically 1% to 3%) shown on the nameplate will be accurate to within +/- 5%.
Thus one
could measure the load current and use this data to compensate for the voltage
drop in the
transformer. If one assumes an instrumentation error of 0.15% for both the
voltage and
the current measurements, then the overall worst case high voltage measurement
error for
a transformer with 3% impedance would be:
3%X5%+0.15%+0.5%+0.15% = 1%.
This level of accuracy would only be suitable in situations where small
numbers
of customers are involved as would be true of any theft detection system which
is based
on kWh. The irony of this is that the extra expense and other drawbacks of
providing a
feeder current meter with a kWh capability, only results in enabling a system
of theft
detection which is mathematically inferior to one based on AIPC (Accumulated
In-
Phase Current). If AIPC is used instead, there will be a greater ability to
detect theft
and a greater ability to reduce false alarms, and the feeder current meter
will not need
any expensive voltage measurement instrumentation.
There are other advantages as well. Since there is no requirement for the
feeder
current meter to measure voltage, it can be a much smaller, lighter, and safer
device.
Since it does not need to be connected across any high voltage, no high
voltage fuses
are required. This reduces the size and weight of the device. Being
lightweight means
that it can clamp directly onto a feeder with no other means required to
support its
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weight. Thus deployment can be achieved much more quickly, and there is more
flexibility with regards to where the device can be installed. Finally, the
device is
inherently safe. Unlike devices which connect across the high voltage, this
device
completely eliminates the risk of internal arcing around a fuse enclosure and
thus
eliminates the danger of explosion during installation.
AIPC (Accumulated In-Phase Current)
AIPC is simply the non-voltage component of energy.
Energy = jPdt = jV*I dt = Accumulation (or integral) of voltage times real
current
AIPC = Jldt = Accumulation (or integral) of real current
where I = real current = non-reactive current = in-phase current
Energy is measured in kWh (kilo-Watt-hours) while AIPC is measured in Ah
(Amp -hours)
In practice, the magnitude of the in-phase current can be determined in a
number of
different ways. For example, the current signal could be multiplied by a
sinusoidal
waveform of fixed amplitude and having the same phase as the voltage. If such
a
waveform is not available, the voltage waveform could be used instead, but
then it
would be necessary to continuously divide by the voltage since the voltage
waveform is
one that continuously varies in amplitude. Even if the voltage waveform is
uncalibrated,
this would not matter because of the compensating effect of the division as
long as the
phase is accurate. In fact any sinusoidal waveform which remains proportional
to
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voltage, and has the correct phase and frequency would work, An alternative
method
would be to measure the amplitude of the current waveform and continuously
multipiy
this by the power factor. The power factor can be determined by taking the
cosine of
the phase angle between the voltage and the current, or by dividing the active
energy
by.the apparent energy. The active energy is what is normally measured by an
electricity meter and accumulated (or integrated over time) while the apparent
energy is
the RMS (root-mean-squared) of the voltage multiplied by the RMS of the
current and
accumulated.
If we have a 7.2 kV feeder (phase-to-ground) which is supplying 100 Amps to a
steady unchanging load, where the feeder line from the substation to the
customer has
0.72 Ohms, the voltage drop over this length of line would be 72 Volts. If the
voltage at
the substation is 7200 Volts then the voltage at the customer would be 7200 -
72 =
7128 Volts. The energy registered at the substation for a one hour period
would be 7.2
X 100 = 720 kWh. At the load, the metered energy would be 7.128 X 100 = 712.8
kWh.
In this case ((720 - 712.8) / 720) X 100% = 1% of the energy is lost due to
line losses.
In the next one hour interval the substation supplies 200 Amps during the
first 30
minutes and no current for the rest of the interval. During the first 30
minutes 200 X 7.2
X 30/60 = 720 kWh are registered at the substation and therefore also for the
entire
one hour period as well. At the load, however, the voltage drop is doubled as
it is
proportional to current and the customer voltage is 7200 - (200 X .72) = 7056
Volts for
the first 30 minutes and 7200 Volts for the following 30 minutes. The energy
metered at
the customer(s) is then 7056 X 200 X 30/60 = 705.6 kWh for the first 30
minutes and
therefore for the entire one hour interval as well. In this case, ((720 -
705.6) / 720) X
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100% = 2% of the energy is lost due to line losses.
Since the same amount of energy (720 kWh) is registered at the substation in
both cases, this measurement cannot be used to predict the amount of energy
lost to
the line. Volt-hours at the customer is also not useful for similar reasons.
In both of
these cases, there would be 7128 Volt-hours at the customer(s), for the one
hour
period, and yet in the second case there are 7.2 fewer kWh. Thus an attempt to
estimate AIPC by dividing Watt-hours, for a one hour period, by Volt-hours,
for the
same one hour period, will suffer from the same mathematical error caused by
load
induced line loss variations.
If true AIPC is used, then in both cases, 100 Ah would be registered at both
the
substation and at the customer(s) (unless there is theft). If AIPC is not
available, then
using maximum voltage and minimum voltage to calculate minimum AIPC and
maximum AIPC is the next best thing.
The system of the present invention is illustrated schematically in figure 1
as item
10 and consists of a plurality of distribution transformers 20 each coupled to
a
distribution transformer meter 22 which is capable of measuring and recording
AIPC.
The distribution transformer meter disclosed in co-pending United States
application no.
60/949,606 is suitable for use with the present invention. Distribution
transformers 20
are each coupled to a load 18 (for example several residential power
consumers) and
to a high voltage feeder line 12. High voltage feeder line 12 is in turn
coupled to a
substation transformer 17 in substation 14. Distribution transformer 34 is
also coupled
to feeder line 12 and data collector 16 is in turn coupled to distribution
transformer 34.
Each of the distribution transformer meters 22 records the AIPC used by its
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corresponding load 18 during a given time period and sends this information to
data
collector 16. Substation transformer 17 is coupled to feeder current meter 24,
which,
like distribution transformer meters 22, is configured to calculate and record
the AIPC
for a given time period. Feeder current meter 24 is further configured to send
the AIPC
measurements to data collector 16, preferably via power-line communications
signals.
Distribution transformer meters 22 are also configured to transmit their AIPC
measurements to data collector 16, also preferably via power-line
communications.
Data collector 16 then sends these AIPC measurements to central computer 32
which
does not need to be near data collector 16 and which can be connected to other
data
collectors as well. Each distribution transformer meter 22 sends a unique
identifier
code along with its AIPC measurement; hence, central computer 32 can compare
the
AIPC measurements received by each distribution transformer meter 22 and
compare
them to the AIPC measurement for the same time period from feeder current
meter 24.
This comparison is done by first converting AIPC to normalized active energy
or NAE.
NAE is simply AIPC multiplied by the nominal voltage. In the case of the
distribution
transformer meters 22 the nominal voltage would typically be 240 V. For the
feeder
current meter, the nominal voltage could for example be 7200 V if the
transformer
transformation ratio is 30. The total NAE derived from distribution
transformer meters
22 should be equal to the NAE derived from the measurement recorded by feeder
current meter 24 for the same time period within a reasonable margin of
measurement
error. If there is a significant difference between the totals of the NAE,
then this must
mean that there is an unknown load attached to the feeder. The utility, which
operates
central computer 32 can then investigate the extra load.
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This system of current accounting is not affected by line losses and is
therefore
more accurate than energy metering. Also, a device which measures only AIPC at
feeder current meter 24 does not require high voltage operation. For this
reason, AIPC
metering of feeder 12 is much safer and much less expensive than energy
metering.
Connectivity Information
The system of the present invention can be used to detect two different kinds
of
electricity theft. The first kind is theft of electricity from a utility owned
distribution
transformer. The second kind is the theft of electricity directly from the
feeder which
can occur with the unauthorized coupling of a distribution transformer
directly to the
high voltage feeder. The distribution transformer meter detects the first kind
of theft in
conjunction with electricity meters installed at the end users. The
electricity
consumption at the distribution transformer must substantially equal the sum
of the
electricity consumptions at the end users. To do this comparison, however, the
utility
must know which end users are connected to which distribution transformers.
Connectivity information is needed for detecting the second kind of theft as
well. This
information can be collected using mapping. This involves the generation of
two
dimensional images or diagrams (which can be on paper or in electronic form
for
display on computer monitor) which show, in representative form, the feeders
the
distribution transformers, the end-users and the interconnections between
them.
Generating these maps involves a fair amount of work, not only to produce them
initially, but also to keep them up to date as changes are made to the power
system.
Even once these maps have been produced and are up to date, there is still
some work
required to interpret the maps in order to generate the equations which are
used to
CA 02689776 2010-01-07
check for the unauthorized use of electricity.
The system of the present invention eliminates the need to produce maps and
eliminates the need to interpret them. Instead, a connectivity matrix can be
produced
automatically to indicate which customer meters (CMs) are connected to which
distribution transformer meters (DTMs) and where each distribution transformer
is on
the feeder reiative to the feeder current meters (FCMs). The basic approach is
to send
power line carrier signals into the grid, at various locations, which are
received by units
at other locations. The received signals are then processed to provide the
necessary
connectivity information in the form of a matrix. Software can then use this
matrix to
automatically generate the equations which are used to check for the
unauthorized use
of electricity.
The connectivity information requirements can be divided into three
categories;
namely, 1. DTM to customer meter, 2. FCM to DTM and 3. FCM to CCM (customer
Configuration Module). The following is a discussion of how the method of the
present
invention is used to define all three parts of the connectivity matrix.
1. DTM to customer meter
It is necessary to know which customer meter is connected to which
distribution
transformer. One approach to this is for the data collector to send an
instruction signal
to all the DTMs on a feeder phase to simultaneously transmit via power line
communication (PLC) a unique distribution transformer meter identifier (such
as the
DTM's serial number) to the customer meters. The DTMs respond by
simultaneously
sending their serial numbers via PLC. The customer meter receives the serial
number
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from its DTM (i.e. the DTM on the distribution transformer which supplies
power to the
customer meter) and then transmits the received serial number to its remote
data
collector together with the customer meter's own unique identifier. This
connectivity
information is preferably stored in a database coupled to the remote data
collector.
While a PLC signal transmitted on the secondary of one transformer can be
received at a low level on the secondary sides of other transformers, in
practice, the
signal strength of these signals will be low enough to be drowned out by the
desired
signal (i.e. the signal sent and received on the same secondary side) and only
the
correct serial number should be received. It would still be necessary to
measure the
signal strength of the received signal so that it will be known if a DTM
transmitter has
failed to transmit.
2. FCM to DTM
It is necessary to know which section of feeder a distribution transformer is
connected
to. The feeder section boundaries correspond to the locations on the feeder
where
FCMs are installed. This can be achieved by dividing an hour into a series of
time
windows. Each FCM would transmit a uniquely identifiable signal in its own
specified
time window. Indeed, the specific time window forms part of the uniquely
identifiable
portion of the signal from the FCM since no two FCMs on a feeder would
transmit in the
same time window at the same frequency. Instead, the FCMs would transmit in an
ordered sequence. The signal traveling upstream from the FCM would be a
positive
signal (phase +ve) while the signal traveling downstream from the FCM would be
a
negative signal (phase -ve). The DTM PLC receivers would not only be able to
detect
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the presence of the signal, they would be able to determine from the time
window which
FCM transmitted the signal, and the phase of the signal (i.e. whether the
signal was
positive or negative phase). This data is transmitted by each of the DTM's to
a remote
data collector along with a unique DTM identifier (such as the DTM's serial
number) for
each DTM. From this data, it would be possible to determine which section of
feeder
each DTM is connected to. For example let us suppose that a DTM received the
following FCM data:
FM1 -
FM2 -
FM3 +
FM4 +
In this case it would then be known that the DTM was connected to the feeder
section
between FM2 and FM3.
This method of determining where each DTM is in relation to the feeder current
meters is illustrated in figure 1. The process begins with the data collector
16 sending,
via power line carrier communications, a carrier duplicate instruction to all
of the feeder
current meters on the feeder. This instruction is followed by a pure carrier
sent by the
data collector for a fixed length of time. Then the feeder current meters 24,
26, and 28
transmit in succession a duplicate carrier which is substantially identical in
frequency
and phase using an inductive coupling to the feeder. The inductive coupling,
used by
the feeder meter power line carrier transmitter, results in the signal going
up-stream
from the feeder meter being 180 degrees out of phase with the signal going
down-
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stream. Thus these signals can be classified as positive signals or negative
signals. All
of the DTMs 22 on the feeder record, for each feeder current meter, whether
they have
received a positive or negative signal. This information is relayed to the
data collector
16 on request and thus the data collector 16 is not only provided with the
AIPC (or
energy or both) measurements from all of the feeder current meters 24, 26, and
28 and
DTMs 22, but is also provided with all the information required to do the
comparisons
for theft detection, thus eliminating the need to do any mapping.
Referring now to Figure 2, all of the DTMs connected to the feeder segment
between feeder current meter FM2 and feeder current meter FM3 will receive a
negative signal from feeder current meter FM2 and a positive signal from
feeder current
meter FM3. Any DTMs on the other side of the feeder current meter FM3 would
receive
a negative signal from both feeder current meters, and all of the DTMs on the
other side
of feeder current meter FM2 will receive positive signals from both feeder
current
meters. Thus the sum of the NAE measurements of all the DTMs which receive a
negative signal from feeder current meter FM2 and a positive signal from
feeder current
meter FM3 should substantially equal the NAE measurement of feeder current
meter
FM2 minus the NAE measurement of feeder current meter FM3.
A potential difficulty could arise if there was a three phase capacitor bank
which
transferred the signals from one feeder phase to the other two feeder phases.
It would
then be necessary to be able to determine not only which phase each FCM is
installed
on, but also which phase each DTM is installed on, however, without the
capacitor
bank, this can be easily determined because signals transmitted on one feeder
phase
would not be received on the other two phases.
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The capacitor bank or anything else which causes the signal from one feeder
phase to be coupled to the other two phases makes this task more difficult.
One
possible solution to this is to have the FCM transmit a signal which is
modulated by the
60 Hz power signal on its feeder phase. The DTM receiver would then demodulate
this
signal to recover the original 60 Hz signal. It would then measure the phase
angle
between this signal and the voltage that it is connected to. If the phase
angle difference
is close to zero or 180 degrees, then it would be known that this signal came
from a
FCM on the same feeder phase. If the phase angle difference is close to 120
degrees
or 60 degrees, then it would be known that the signal originated on one of the
other two
feeder phases. It could be further determined which of the other two feeder
phases the
FCM was located on by determining whether the phase difference of 120 degrees
or 60
degrees was leading or lagging.
3. FCM to Customer Configuration Module
In sparsely populated rural areas, it is common to have only one customer for
each
distribution transformer. Cost considerations are expected to prevent the
deployment
of DTMS on these transformers. Therefore, it is necessary for another device,
a
customer configuration module (CCM) to perform the functions described in the
previous section 2. This unit could be like a DTM installed at the
distribution
transformer, except that it does not sense or measure current, or it could be
a module
which plugs in somewhere in the customer's residence.
Signal Processing Requirements
1. Accurate Time-Base (Low Drift)
For a CCM to be able to detect and process signals from the FCM and for a
meter to be
CA 02689776 2010-01-07
able to detect and process signals from the DTM, it is necessary to have a
demodulation algorithm with an accurate time-base. A suitable time-base
algorithm is
described in U.S. Patent# 6,549,120.
2. Signal and Phase Detection
It will be necessary to determine which phase of the feeder the DTM or CCM is
coupled
to. This can be done by sending a feeder current meter signal on a carrier
from the
feeder to the DTM or CCM. This reference signal is sent for a period of which
may
need to be up to ten minutes long to give a DTM or CCM a chance to find the
phase
angle of the carrier. The feeder current meter signal will need to be
modulated by the
power system frequency on the phase which the signal is sent. The DTM or CCM
receives the modulated feeder current meter signal and demodulates it. The
demodulation can be done by the DTM or CCM producing a demodulation frequency
with a small frequency offset from normal carrier frequency. The demodulated
output
would then be a slow sine wave with zero-crossings that can be determined. One
method would be to wait for such a zero-crossing, and then remove the
frequency
offset. A phase offset of 90 degrees could then be applied to the demodulation
signal
to bring the demodulation signal in line with the received signal. An
additional phase
offset may need to be applied to compensate for delays in the filtering of the
demodulated signal. Once this phase alignment is achieved, it should remain
free of
drift for the entire duration of the configuration detection process due to
the accuracy of
the time-base.
After the reference frequency transmission is complete, the received signal is
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demodulated for the purpose of determining configuration. It is necessary for
the DTM
or CCM to be able to distinguish between positive and negative signals (phase
angle of
0 or 180) for single feeder phase connectivity detection, and other phase
angles as well
for rejecting signals from other feeders.
3. Time Window Detection
It is necessary for the DTM or CCM to be able to determine the time window in
which a
signal was received. This requires that the DTM or CCM have a clock with an
error less
than one half of the time window length for this to even be possible, but
ideally, for good
performance, it needs to be less than one 16th of the time window length. In
some
cases, this may require a resynchronizing of the clocks to avoid the need for
long time
windows which would make the configuration detection process very slow.
4. Data Decoding
It is necessary for the customer meter to be able to decode data in the form
of serial
numbers for communication from the DTM to the meter.
5. Signal Level
It is necessary for the customer meter to be able to determine the signal
strength so
that signals from DTMs in other distribution transformers can be rejected in
the event
that the DTM on the same distribution transformer as the customer meter fails
to
transmit.
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6. Three-Phase Cross-talk Rejection
On a three-phase circuit where signals are coupled together, it is necessary
to have a
method for rejecting signals originating on either of the two other phases.
This requires
that the data collector or other device be able to decode the 60 Hz frequency
modulation on the transmitted FCM signal to determine whether the phase of the
demodulated signal matches the phase of the 60 Hz power signal connected to
the
customer meter (or distribution transformer meter). Since the demodulation
filtering
would need to be slow in order to pick out the signal from the background
noise, the 60
Hz waveform may need to be demodulated on a piece-wise basis. The resolution
with
which this can be done is limited by the sampling frequency.
It is not necessary that this cross-talk rejection be done simultaneously with
other
configuration processes. This can be a separate function. Nevertheless, the
system
must know either which phase a customer meter is connected to, or which
customer
meters go with which FCMs. Since all of the FCMs, including the ones on other
phases, will each have a different time window, there should be no
interference
between FCMs on different phases.
An alternative method of determining which of the three phases a meter is
connected to is to use voltage profiling. As the load on a feeder goes up and
down
during the day, the voltage is affected. This voltage can be profiled at the
customer
meter. Since the three phases on a feeder do not see exactly the same load,
each
phase will have its own unique voltage signature, and this signature can be
recorded at
the customer meter or CCM and sent to a central computer. The central computer
then
compares the signature recorded at the customer meter or CCM with the voltage
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signature for the three phases and determines which has the best match. It
also
determines how good the match is. If the match is not good enough to provide
sufficient certainty as to which feeder phase the meter is connected to, the
central
computer continues the process with additional data until the required level
of certainty
is achieved.
Figure 2 shows a number of feeder current meters (FM1, FM2, FM3 and FM4),
distribution transformers (DT), and end-users (EU). Just as it is necessary to
know
which end-users are connected to which distribution transformers, it is also
necessary
to know which distribution transformers are associated with which feeder
current meter
and how. For connectivity detection, the situation is more complicated at the
feeder
level. The simplest feeder current meter topology would be one where a single
feeder
current meter monitors the entire feeder and its NAE values are compared to
the NAE
values for all of the distribution transformers, however, the accuracy
limitations could
result in total measurement error being greater than the amount of theft in
which case
the theft would not be detected. Thus it may be necessary to have more than
one
feeder current meter along the feeder and its branches. The distribution
transformers
are then not associated with any one feeder current meter. Instead they are
associated
with the feeder segment between two feeder current meters. The difference
between
the NAE measurements of two feeder current meters should be substantially
equal to
the sum of the DTM NAE measurements of all of the utility owned distribution
transformers on the feeder segment between the two feeder current meters.
A specific embodiment of the present invention has been disclosed; however,
several variations of the disclosed embodiment could be envisioned as within
the scope
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of this invention. It is to be understood that the present invention is not
limited to the
embodiments described above, but encompasses any and all embodiments within
the
scope of the following claims.
