Patent Publication Number: US-10768212-B2

Title: System and method for detecting theft of electricity with integrity checks analysis

Description:
BACKGROUND OF THE INVENTION 
     The present invention relates generally to electricity theft detection and, more particularly, to a system and method of detecting theft of electricity by performing an integrity checks analysis on a power distribution system using electrical data from various metering devices. 
     Theft of electricity is a serious problem worldwide. Electricity theft has become the third largest form of theft behind credit card data theft and automobile theft. In 2014, worldwide losses as a result of stolen electricity amounted to 89.3 billion dollars. Electricity theft losses in the United States amount to approximately 6 billion dollars every year. Approximately 80% of electricity theft is residential, with the remaining 20% of electricity theft being commercial. Electricity theft is one of the most prominent, if not the most prominent, form of non-technical losses. Non-technical losses are caused by actions external to a utility&#39;s power distribution system or caused by loads and/or conditions not taken into account in the computations for the power distribution system technical losses (naturally occurring or internal losses from power dissipation). 
     A variety of methods are used by utility customers to steal electricity from electric utilities. Many of the methods involve tampering with the primary meter that reads the electricity flowing into the residential or commercial load. One way to tamper with older meters is to pull out the meter that connects the electrical path from the utility to the electrical path into the property and put that meter back in upside down. Thus, the line side of the meter and the load side of the meter would be reversed, and the meter would record any measurements taken as a reverse flow of electricity. In other words, the meter would read that electricity is being provided to the utility from the load. Another way utility customers tamper with their utility meters is to put a shunt in the base of their meter to create a parallel electrical path that will not be monitored. Yet another common meter tampering method is to put one or more magnets on the meter. The magnets cause the meter to rotate slower than intended, resulting in a lower electric bill. 
     Utility customers also steal electricity from electrical utilities by tampering with the electrical lines leading into the property. Many utility customers bypass the meter within the meter housing by connecting a wire at the line side or input of the meter directly to the load side or output of the meter. In addition, some customers bypass their meters simply by tapping into an overhead power line on or near the property using a fish hook or similar device to bypass the meter. Other customers dig up underground power lines on their property and tap directly into those lines. 
     In any case, tampering with electric utility meters or power lines is dangerous and illegal. The traditional methods of detecting electricity theft include going to a customer&#39;s property to look for physical indications of tampering, gathering leads reported by the public, and investigating neighbors and relatives of customers found to be tampering to determine if they are also tampering. However, those methods are time consuming and expensive, so electric utilities developed methods of remotely detecting tampering. Several methods include monitoring meters for reverse flow events; power outages and blinks; load side voltages upon disconnecting power; magnetic detection using a Hall effect switch or a similar device; vibration or tilting of the meter; meter cover removal; and incorrect polyphase wiring. Further, transformers that feed primary meters electrically downstream therefrom may also be monitored so that the electricity or power readings at the transformer may be compared against the aggregated usage reported by the meters. 
     In addition to the above, substation feeder metering and advanced metering infrastructure (AMI) data may be incorporated into a power distribution model for the electric utility in order to determine the feeders with the greatest non-technical loss. Also, changes in current flow patterns may be detected before using thermal imaging to find overloaded transformers. Data analytics can be used to locate large spikes or drop offs from historical usage patterns at homes or commercial buildings. The data analytics can account for weather patterns, billing/payment information, comparisons to neighborhood consumption patterns, transformer to aggregate load comparisons, and various other factors. 
     While the above methods may be helpful in determining whether a customer is stealing electricity, those methods cannot perfectly determine whether electricity theft is occurring. None of the methods take advantage of every indicator of electricity theft. For example, none of the above methods monitor components downstream from the primary meter for indications of theft. In addition, the above methods only provide raw data that must be interpreted by the utility in order to determine how likely it is that electricity is being stolen by a customer. Interpretation of that raw data is time consuming and may not provide an indication of electricity theft or may provide a false positive indication of threat when viewed in isolation, depending on various factors. The utility may have to send someone to investigate, even if there is a low likelihood of theft. 
     It would therefore be desirable to provide a system and method for electricity theft detection that takes advantage of available electrical data in a power distribution system and that indicates the likelihood of electrical theft by an electric utility customer using multiple data sources. 
     BRIEF DESCRIPTION OF THE INVENTION 
     Embodiments of the present invention provide a system and method for electricity theft detection in a power distribution system by implementing an integrity checks analysis to examine electrical data from a variety of metering devices and indicate the probability that customers have been stealing electricity based on the examination. 
     In accordance with one aspect of the invention, a system for detecting electricity theft with an integrity checks analysis includes a graphical user interface (GUI) configured to display information related to a flow of electricity within a power distribution system and a controller in communication with the GUI. The controller is configured to receive electrical readings taken by a plurality of electricity meters and examine the electrical readings of the plurality of electricity meters for electricity theft indicators. The controller is also configured to determine a probability that electricity is being stolen at each of the plurality of electricity meters according to any electricity theft indicators affiliated therewith and output each probability to the GUI for display. 
     In accordance with another aspect of the invention, a method of detecting electricity theft in a power distribution system using an integrity checks analysis includes collecting electrical data from metering devices that measure a flow of electricity therethrough at a controller of the power distribution system. In addition, the method includes analyzing the electrical data with the controller to determine the existence of any electricity theft indicators at any metering devices, and based on the analysis of the electrical data, determining a status of each metering device with the controller, each status indicating a probability of electricity theft. The method further includes outputting each status from the controller to a GUI for display. 
     In accordance with yet another aspect of the invention, a power system that detects electricity theft using an integrity checks analysis includes a plurality of meters measuring the flow of electricity therethrough, a GUI configured to display at least a portion of the electricity flow measurements of the plurality of meters, and a control system for performing an integrity check analysis of the power distribution system. The control system is configured to receive the electricity flow measurements of the plurality of meters and assess the electricity flow measurements against a plurality of electricity theft indicators. The control system is additionally configured to determine the probability of electricity theft at each of the plurality of meters based on any electricity theft indicators associated therewith. Furthermore, the control system is configured to assign a color-coded status to each of the plurality of meters based on the probability of electricity theft associated therewith and output each color coded status to the GUI for display. 
     Various other features and advantages of the present invention will be made apparent from the following detailed description and the drawings. 
    
    
     
       BRIEF DESCRIPTION OF THE DRAWINGS 
       The drawings illustrate preferred embodiments presently contemplated for carrying out the invention. 
       In the drawings: 
         FIG. 1  is a diagram of a power distribution system including a system for electricity theft detection, according to an embodiment of the invention. 
         FIG. 2  is a flowchart illustrating a technique for detecting electricity theft in the power distribution system of  FIG. 1 , according to an embodiment of the invention. 
         FIG. 3  is a screenshot of an exemplary graphical user interface (GUI) displaying the status of several transformers in a power distribution system based on an integrity checks analysis, according to an embodiment of the invention. 
         FIG. 4  is a screenshot of the exemplary GUI of  FIG. 3  displaying the status of five meters electrically downstream from a residential transformer in the power distribution system based on the integrity checks analysis, according to an embodiment of the invention. 
         FIG. 5  is a screen shot of the exemplary GUI of  FIGS. 3-4  displaying electricity theft indicators for one meter displayed in  FIG. 4  based on the integrity checks analysis, according to an embodiment of the invention. 
     
    
    
     DETAILED DESCRIPTION 
     Embodiments of the invention relate to a system and method for detecting electricity theft in a power distribution system according to an integrity checks analysis in which the electricity usage and demand data from a variety of meters/metering devices is received or collected at a controller or control system of the power distribution system and assessed or examined for electricity theft indicators. A probability of electricity theft is then determined by the controller for each metering device, and the different levels of probability of electricity theft are displayed on a GUI as different colors to indicate the status of various metering devices in the power distribution system. The statuses of the metering devices displayed on the GUI indicate or designate no or essentially no probability of electricity theft, a slight probability of electricity theft, a medium probability of electricity theft, and a high probability of electricity theft. 
     Referring to  FIG. 1 , a diagram of an electrical or power distribution system  10  of an electric utility is illustrated, according to an embodiment of the invention. Power distribution system  10  includes a master station  12 . Master station  12  includes a master controller or control system  14  and an electrical power source  16 . Power source  16  may include one or more power-generating facilities such as, for example, fossil fuel, hydro-electric, and nuclear power plants. Power distribution system  10  also includes a power distribution network  18  electrically connecting station  12  to a transformer  20  for distributing electricity produced by power source  16  to various loads of electrical system  10 . Optionally, transformer  20  may be a smart transformer that includes a meter or sensor  22  for measuring or sensing the amount of electricity flowing therethrough and used by customers of the utility. Transformer  20  may also optionally include a controller or control system  23  and a transceiver  24  for sending electricity flow measurements to and receiving commands from controller  14  over a long-haul communications network  26  formed therebetween. 
     Long-haul communications network  26  may include a wireless network, as depicted in  FIG. 1 , or a wired network. As such, long-haul communications network  26  may use wired or wireless communications, telephonic communications, Internet Protocol-based communications, satellite system-based communications, and any other type of communications useful for communicating with the various components of electrical system  10 . Examples of such communications systems includes ZigBee®, wireless mesh network, Wi-Fi, wireless point-to-multipoint tower-based, fiber, cellular, and Power Line Carrier. Long-haul communications network  26  generally has two-way communications abilities, which allow controller  14  to both send commands to and receive data from the various components of electrical system  10 . 
     Transformer  20  delivers electricity to a primary electricity or power meter or metering device  28  having a sensor  30  for measuring or sensing the amount of electricity flowing therethrough in terms of energy used or consumed and power demanded or consumed at a property  32  having a residence  34 , which is the primary load of property  32 . Primary meter  28  also includes a transceiver  36  for sending electrical or electricity usage and demand data to and receiving commands from controller  14  over long-haul communications network  26 . In various embodiments, primary meter  28  also includes a controller or control system  31 . The electricity or energy usage data measured by primary meter  28  is used to calculate an electricity bill for property  32  over one or more intervals. The electricity demand data measured by primary meter is used to determine how much power is demanded or consumed by property  32  at any given time. 
     Primary meter  28  is shown here as the entire load for a property, but could also meter any energy and power that are then partially metered again further downstream. As a non-limiting example, primary meter  28  could be configured to meter only the energy used and power demanded by residence  34 , but not a garage (not shown) on property  32 . As another non-limiting example, primary meter  28  could be configured to meter a particular circuit within residence  34  that includes multiple loads. In addition, primary meter  28  is shown outside of residence  34 , but may also be positioned within residence  34 . As a non-limiting example, primary meter  28  could be a metered circuit breaker for residence  34 . While property  32  is shown as a residential property including residence  34 , property  32  may be a commercial property or another type of property having other types of buildings or facilities such as, for example, offices, restaurants, stores, movie theaters, or any other facilities that require electricity from electrical system  10 . 
     In the illustrated embodiment, residence  34  has three secondary loads including two smart loads  38 ,  40 . Smart loads  38 ,  40  may be any type of applicable residential equipment such as, for example, a smart appliance like a refrigerator, an oven, a hot water heater, or a dishwasher; a smart system like a smart heating, ventilation, and air conditioning system or a lighting system; or a circuit that is metered separately from the other circuits in the property, by, for example, a metered circuit breaker. However, smart loads  38 ,  40  will be referred to as smart appliances below. Smart appliances  38 ,  40  each include a respective secondary or sub-meter or metering device  42 ,  44  having respective sensors  46 ,  48  for measuring or sensing the amount of electricity flowing therethrough in terms of energy usage and power demanded by loads  50 ,  52  of smart appliances  38 ,  40 , respectively. Sub-meters  42 ,  44  each also include a respective transceiver  54 ,  56  for sending the measured electrical or electricity flow data to and receiving commands from master controller  14  over long-haul communications network  26  or from controller  31  of primary meter  28  or controller  23  of transformer  20 . 
     While sub-meters  42 ,  44  are shown as being integrated with smart appliances  38 ,  40 , sub-meters  42 ,  44  may be separate devices positioned at a different location than loads  50 ,  52 . As a non-limiting example, sub-meters  42 ,  44  may be located outside of residence  34  with primary meter  28 . In addition, in various embodiments, both or one of sub-meters  42 ,  44  may be a demand response or load management device, such as, for example, a load control relay, that controls when electricity may flow to smart appliances  38 ,  40 . Residence  34  may further include a plurality of non-smart household loads represented by a single load  58 . It is recognized that the loads  50 ,  52 ,  58  illustrated in  FIG. 1  are for illustrative purposes only and that a greater or lesser number of loads (and associated sub-meters) could be present in the residence  34 . 
     As shown in  FIG. 1 , the utility customer at residence  34  is stealing electricity by bypassing primary meter  28  with an electrical or bypass line  60 . Bypass  60  effectively shunts primary meter  28  by directly connecting an electrical or circuit path or line  62  of power distribution network  18  of the utility and an electrical or circuit path or line  64  of residence  34 . By shunting around primary meter  28 , the utility customer at residence  34  prevents primary meter  28  from reading the full amount of electricity flowing to residence  34 , which will result in a lower electric bill for the customer. While bypass  60  is shown in  FIG. 1  as connected between transformer  20  and primary meter  28  and between primary meter  28  and residence  34 , bypass  60  may be connected in any manner to shunt primary meter  28  such as, for example, on the other side of transformer  20  or even entirely within a housing (not shown) of primary meter  28 . In addition, another method of electricity theft may be used instead of bypass  60 . 
     Even though primary meter  28  is shunted, sub-meters  42 ,  44  of smart appliances  38 ,  40  have not been shunted. Therefore, sub-meters  42 ,  44  will still read the electricity used and power demanded by respective smart appliances  38 ,  40  and transmit the readings to controller  14  at station  12 . Controller  14  can use all of the electrical usage and power demand data gathered by meters  28 ,  42 ,  44  to determine if the utility customer at residence  34  is stealing electricity. As will be described in more detail below with respect to  FIG. 2 , controller  14  can compare the readings from sub-meters  42 ,  44  to the readings from primary meter  28  in order to determine if the readings from sub-meters  42 ,  44  are consistent with the readings from primary meter  28 . In other words, controller  14  will analyze the readings to evaluate if there is a change in energy consumption or power demand at primary meter  28  and sub-meters  42 ,  44 . When controller  14  detects discrepancies or conflicts between the readings such that the readings are inconsistent, controller  14  can alert the utility of electricity theft at residence  34 . The utility can then take action against the electricity theft such as, for example, sending out a lineman to remove bypass  60  or to shut off the power to property  32 . While controller  14  is described above as performing the analysis of the data gathered by meters  28 ,  42 ,  44 , controller  31  of primary meter  28  may also perform the analysis upon receiving the data from sub-meters  42 ,  44  and alert the utility of any discrepancies via transceivers  36  and long-haul communications network  26 . Controller  23  of transformer  20  may additionally be used to perform the analysis after receiving the data from meters  28 ,  42 ,  44  under various circumstances. 
     Referring now to  FIG. 2 , and with reference back to  FIG. 1 , a technique or process  66  for detecting the electricity theft at property  32  and, more specifically, residence  34  is shown with process  66  being performed by a controller or control system in or associated with the utility, such as controller  14  of station  12  of the utility. Process  66  will be described below with respect to readings at primary meter  28  and sub-meter  42  with the analysis of the readings being performed by controller  14 . However, as described above, the analysis of the readings at primary meter  28  and sub-meter  42  may instead be performed by controller  31  of primary meter  28  or controller  23  of transformer  20 , with the results of the analysis being transmitted to controller  14 . Process  66  may be used to monitor the energy consumption and power demand data obtained by primary meter  28  and sub-meter  44  separately from sub-meter  42  or may be used to monitor the electrical usage and demand data obtained by primary meter  28  and sub-meters  42 ,  44  collectively. Further, process  66  is not limited to being used to monitor two sub-meters and one primary meter. Process  66  may be used to monitor multiple transformers, primary meters, and sub-meters as needed within electrical system  10 . 
     Process  66  begins at STEP  68  when electricity is provided to property  32  and residence  34  through transformer  20  and primary meter  28  and at least one electricity flow reading has been taken by primary meter  28  and sub-meter  42 . At STEP  70 , primary meter  28  reads the electricity usage and demand for property  32 , and sub-meter  42  reads the electricity usage for load  50  of smart appliance  38 . The readings taken by primary meter  28  and sub-meter  42  may occur over the course of one interval and be transmitted to controller  14  such that controller  14  monitors or analyzes the flow of electricity over one period of time. However, controller  14  may also analyze usage data collected over multiple intervals to calculate demand over different intervals to watch for changes in demand as load  50  turns on and off. That way controller  14  may incorporate historical data processing to present more complete and accurate results. At STEP  72 , controller  14  determines whether the absolute value of a change in power demand or consumption measured by sub-meter  42  (|Δ sub-meter demand) in  FIG. 2 ) at any point during the one or more intervals analyzed is greater than a deadband or predetermined minimum change in usage threshold or magnitude. In a non-limiting embodiment, the deadband is set to 25% of a maximum change in power consumption by load  50  of smart appliance  38 . The deadband may be changed by the utility using controller  14  at any time. 
     If changes in demand measured by sub-meter  42  at any time during the one or more intervals analyzed is not greater than the predetermined threshold, controller  14  filters out the demand data for sub-meter  42  at those points in time with respect to the electricity theft detection analysis. In other words, any change in demand data sensed by sub-meter  42  that is not larger than the deadband is omitted from the electricity theft detection analysis. Controller  14  filters the demand data because it does not indicate a noteworthy or significant change in the demand at load  50  of smart appliance  38 . Once controller  14  filters the demand data for sub-meter  42 , process  66  returns to STEP  70 , where controller  14  continues to receive readings from primary meter  28  and sub-meter  42 . 
     If controller  14  determines at STEP  72  that the absolute value of any changes in demand measured by sub-meter  42  are larger than the minimum change in usage threshold, process  66  moves to STEP  76 . At STEP  76 , controller  14  compares changes in demand measured by primary meter  28  (A primary meter demand in  FIG. 2 ) to changes in demand measured by sub-meter  42  (A sub-meter demand in  FIG. 2 ) to determine whether there has been a change in power consumption by load  50  of smart appliance  38  without a corresponding change in power consumption measured by primary meter  28 . That circumstance would indicate that load  50  is consuming more power, but primary meter  28  did not measure that same or a similar increase in power consumption for residence  34  overall. In that case, the power consumption of load  50  measured by sub-meter  42  has deviated from the power consumption for residence  34  measured by primary meter  28 , which indicates a bypass of primary meter  28 . After STEP  76 , process  66  moves to STEP  80 . 
     At STEP  80 , controller  14  calculates a tamper, interference, or bypass percentage or coefficient corresponding to the level of tampering, interference, or bypass of the electrical path  62  through primary meter  28  assessed by controller  14 . Controller  14  is generally configured or programmed to display a tamper percentage as a percentage of tampering and to display a tamper coefficient as a number between 0 and 1 proportional to the amounting of tampering. For example, in non-limiting embodiments, a tamper percentage of 20% would indicate that the utility customer has stolen 20% of the electricity used at residence  34 , and a tamper coefficient of 0.8 would indicate the same. Thus, if no tampering is detected by controller  14  (in other words, no or a minimal number changes in demand at sub-meter are flagged by controller  14 ), the tampering coefficient should be close to 1 and the tampering percentage should be close to 0%. However, tamper percentages and coefficients may be displayed according to any desired format. 
     The tamper coefficient or percentage may be calculated by a variety of methods. In a non-limiting embodiment, the tamper coefficient may be calculated using a linear regression slope equation given by: 
                     T   =         Σ   ⁡     (       M     SU   ⁢           ⁢   Δ       -       M     SU   ⁢           ⁢   Δ       _       )       ⁢     (       M     PU   ⁢           ⁢   Δ       -       M     PU   ⁢           ⁢   Δ       _       )           Σ   ⁡     (       M     SU   ⁢           ⁢   Δ       -       M     SU   ⁢           ⁢   Δ       _       )       2         ,           [     Eqn   .           ⁢   1     ]               
where T is the tamper coefficient, M SUΔ  is the change in demand measured by sub-meter  42 ,  M SUΔ    is the average change in sub-meter demand, M PUΔ  is the change in primary meter demand, and  M PUΔ    is the average change in primary meter demand. The tamper coefficient may be converted into the tamper percentage by simply subtracting the tamper coefficient from a value of 1 and multiplying the result by 100.
 
     Once controller  14  calculates the extent that the utility customer has tampered with primary meter  28 , controller  14  outputs the tamper coefficient and/or tamper percentage to a display at STEP  82  such as, for example, a GUI (not shown) at master station  12  of the utility. By displaying the tamper coefficient and/or percentage at the utility, controller  14  alerts employees of the utility that property  32  needs to be examined to fix the bypass of primary meter  28 . Controller  14  will continue to output the tamper coefficient and/or percentage to the utility indicating the bypass of primary meter  28  until bypass  60  positioned around primary meter  28  has been removed. When bypass  60  has been removed, the tamper coefficient and percent would change to values more favorable to the utility. After controller  14  alerts the utility of the bypass, process  66  proceeds to STEP  70  to continue monitoring for electricity theft at property  32 . 
     Referring now to  FIGS. 3-5 , screenshots of an exemplary GUI  84  displaying the status of several transformers and meters in a power distribution system, such as power distribution  10  of  FIG. 1 , based on an integrity checks analysis is illustrated, according to an embodiment of the invention. The integrity checks analysis is performed by a controller or control system, such as master controller or control system  14  of power distribution system  10  of  FIG. 1 , and may incorporate the electricity theft detection method of  FIG. 2 . The integrity checks analysis includes a variety of parameters that have various indications of the probability or likelihood that electricity is being stolen from a utility. The integrity checks analysis includes a scoring or ranking system that assigns a score or rank to each monitored trigger for an indication of theft. 
     In the non-limiting embodiment described in more detail below, the controller performing the integrity checks analysis assigns a predetermined number of points to each different type of theft indicator. The controller adds the number of points of each theft indicator associated with each monitored component in the power distribution system. The number of points will indicate whether there is no or essentially no probability of theft, a slight probability of theft, a medium probability of theft, or a high probability of theft affiliated with a monitored component. Any monitored components with no theft indicators associated therewith will have zero points. The controller uses the number of points associated with each monitored component to determine a status for each monitored component and then displays the status of each monitored component in the power distribution system on GUI  84 . The controller displays each status as a color that indicates the probability that electricity is being stolen from the transformer. The colors are displayed based on a color-coded system in which green indicates no or essentially no probability of theft, yellow indicates a slight probability of theft, orange indicates a medium probability of theft, and red indicates a high probability of theft. 
     The indicators of theft monitored in the integrity checks analysis are generally divided into three different categories: slight probability, medium probability, and high probability indicators of theft. However, a different number of categories may be used based on preference. Typically, each category has a number of points assigned to it to indicate the probability of electricity theft, and the assigned number of points indicates the corresponding status. In other words, slight probability indicators are assigned a number of points to indicate a slight probability of theft by themselves, medium probability indicators are assigned a number of points to indicate a medium probability of theft by themselves, and high probability indicators are assigned a number of points to indicate a high probability of theft by themselves. The slight and medium probability indicators may be assigned a number of points so that it takes a specific number of slight and medium probability indicators to indicate the next level of probability of theft. As a non-limiting example, the slight probability indicators may be assigned a number of points so that it takes the existence of three slight probability indicators at a single monitored component to indicate a medium probability of electrical theft at that monitored component. However, each theft indicator may be assigned a different number of points regardless of whether they are in the same category. In addition, while the non-limiting embodiment of the integrity checks analysis described herein uses a points system, another system may be used to rank the various theft indicators. 
     Non-limiting examples of slight probability theft indicators may include the worst feeders for non-technical losses (determined using system modeling techniques with feeder and transformer metering and AMI data); existing outage flags for any monitored system components; zero consumption measured at system components over consecutive intervals; spikes or drops in usage, such as, for example, approximately 15% or more changes daily; and discrepancies found in comparisons between usage measured at a home and usage measured at similar neighboring homes. Medium probability theft indicators may include, for example, multiple outages over the course of a few or several days; outages followed by significant usage changes, such as a 15% or more daily reduction in consumption; and outages that are not widespread within a relatively short distance such as, for example, a half mile radius that may be based on global positioning system coordinates. 
     High probability theft indicators might include, as non-limiting examples, existing or available meter flags for events such as, for example, reverse flow, vibration and/or tilt, and magnetic detection; an outage at a meter downstream from a transformer, but other meters downstream from the same transformer are unaffected; the aggregated usage of downstream meters does not add up to the same usage at an upstream meter within an acceptable range; and a sub-meter on a smart apparatus or system or a load control relay, for example, experiences large changes in demand, but the primary meter upstream therefrom does not measure the same or a similar change in demand. The theft indicator of a large difference in demand change between upstream and downstream metering devices corresponds to process  66  of  FIG. 2 . The power distribution system controller compiles all electrical or electricity data for all of monitored system components; performs the integrity checks analysis using the data to determine any existing slight, medium, and high probability theft indicators; and outputs the status of the system components to GUI  84  to alert the utility. The electrical data with which the integrity checks analysis is performed generally includes all available data relating to power consumption, electricity usage, and electrical events or flags (such as, for example, outage, reverse flow, vibration/tilt, and magnetic/DC detection flags). 
     While many types of electricity theft indicators are listed above, additional or less indicators may be analyzed depending on the equipment available to the utility or the preference of the utility. In fact, it may be more advantageous to monitor theft indicators in the case where the high probability indicators, such as, for example, the large changes in demand between different meters monitored by process  66  of  FIG. 2 , are not analyzed. The high probability indicators are generally sufficient on their own to indicate theft of electricity, so the utility may use them separately from the integrity checks analysis when they are available. However, the high probability indicators are included in the description of GUI  84  below in order to provide a complete description of the integrity checks analysis. 
     As shown in  FIGS. 3-5 , the GUI  84  includes an outage section or portion  86 , a tamper flag section or portion  88 , and a transformer status section or portion  90 , each including data from the integrity checks analysis. GUI  84  may include many other sections relevant to the integrity checks analysis depending on the characteristics of the power distribution system, the preference of the utility, and supporting technology. Outage section  86  of GUI  84  displays whether there are currently any outages within the associated power distribution system. In the case of  FIGS. 3-5 , the controller of the power distribution system is monitoring  138  system components, and none of those components are experiencing an outage violation. Tamper flag section  88  displays whether any of the system components are being monitored for tampering and if any tampering violations have occurred. Tampering violations may appear for any monitored instances of tampering with system components such as, for example, removing the cover of a transformer or primary meter and vibration and/or tilting of a transformer or primary meter. At the time of  FIGS. 3-5 , no system components are being monitored for tampering. 
     Transformer section  90  of GUI  84  displays select data for different monitored transformers. While transformer section  90  may include a multitude of transformers, the statuses of three transformers are displayed in transformer section  90  in  FIGS. 3-5  for simplicity. Referring to  FIG. 3 , transformer section  90  displays data for two residential-use transformers, Residential 1 and Residential 2, along with one commercial-use transformer, Commercial 1. Transformer section  90  displays the size of each transformer measured in kilovolt-amperes (kVA), the usage at each transformer measured in kilowatt hours (kWh), the metered usage downstream from each transformer measured in kWh, the number of primary meters downstream from each transformer, and the status of each transformer. The status of each transformer is displayed as a color that indicates the probability that electricity is being stolen from the transformer based on the color-coded system described above. The status of each transformer is affected at least in part by the status of each meter downstream therefrom, as described in more detail with respect to  FIGS. 4 and 5 . However, in  FIG. 3 , the data for each transformer is fully collapsed so that available data for any meters downstream therefrom is not shown. In  FIGS. 3-5  colors are illustrated as different line patterns that represent corresponding colors, but the line patterns will be referred to as colors herein. 
     As shown in  FIG. 3 , Residential 1 and Residential 2 are both 50 kVA transformers, while Commercial 1 is a 100 kVA transformer. Residential 1 has a usage of 35.1 kWh and a metered usage of 33.1 kWh measured by 8 meters downstream therefrom. The status of Residential 1 is orange, which indicates a medium probability of electricity theft. Residential 2 has a usage of 29.6 kWh and a metered usage of 24 kWh measured by 5 meters. The status of Residential 2 is red, which indicates a high probability of electricity theft. The status of Residential 2 will be discussed further with respect to  FIGS. 4 and 5  below. Commercial 1 has a usage of 87.4 kWh and a metered usage of 86.1 kWh measured by 4 meters downstream. The status of the Commercial 1 is green, which indicates no or essentially no probability of electricity theft. 
     Referring to  FIGS. 4 and 5 , the status of Residential 2 will be discussed in more detail in order to illustrate a non-limiting example of how GUI  84  displays data for monitored system components.  FIG. 4  shows that the data for Residential 2 can be expanded to include data  92  for the meters downstream therefrom. Meter data  92  is displayed upon touching or clicking on the Residential 2 line in transformer section  90  on GUI  84 . Residential 1 and Commercial 1 generally include the same meter data for their downstream meters. Meter data  92  includes the names of downstream meters, Meters 1-5; the usage of the meters measured in kWh; and the status of the meters. The usage for each of Meters 1-5, respectively, is 4.2 kWh, 8.5 kWh, 4.8 kWh, 3.9 kWh, and 2.6 kWh. When added together, the usage for Meters 1-5 equals the 24 kWh measured usage displayed for Residential 2. The status for Meters 1, 2, and 5 are green, which indicates no or essentially no probability of electricity theft. The status of Meter 4 is yellow, which indicates a slight probability of electricity theft. The status of Meter 3 is red, which indicates a high probability of electricity theft. In this case, the red status of Meter 3 controls the red status of Residential 2 to indicate that Meter 3 requires immediate attention even if the data for Meters 1-5 of Residential 2 is collapsed. 
       FIG. 5  shows a detailed explanation of the status of Meter 3 in a separate integrity checks window  94  displayed over the top of other data in transformer section  90  upon touching or clicking on the Meter 3 line in meter data  92  on GUI  84 . Integrity checks window  94  displays all of the existing electricity theft indicators for Meter 3 and may be closed by touching or clicking on the “x” in its upper right-hand corner. Each of Meters 1, 2, 4, and 5 generally include a similar integrity checks window. 
     Integrity checks window  94  shows that Meter 3 has three existing electricity theft indicators. The first is an outage at Meter 3 with no outage at Residential 2. The second theft indicator is a discrepancy between the readings taken at Meter 3 and a sub-meter downstream from Meter 3. The second theft indicator was found as a result of the controller performing process  66  described above with respect to  FIG. 2 . As explained previously, the first and second theft indicators for Meter 3 are both high probability theft indicators, so a red status is displayed to the left of each theft indicator description. 
     The third electricity theft indicator for Meter 3 is a significant drop in usage, which is typically set to a 15% or more reduction in daily usage, but could be set to a different level depending on different circumstances or preferences. As set forth above, that type of electricity theft indicator is a slight probability indicator, so a yellow status is displayed to the left of its description. Since the integrity checks analysis found two high probability theft indicators and one slight probability theft indicator, the probability of electricity theft at Meter 3 is quite high. This is why the overall status for Residential 2 is indicated in red. Because that is the case, the utility will almost certainly send a lineman to investigate Meter 3. Based on the data for Meter 3 in integrity checks window  94 , the lineman is likely to find that Meter 3 has been at least partially bypassed using a method such as, for example, the bypass method shown in  FIG. 1 . 
     As shown by way of the example on GUI  84  in  FIGS. 3-5 , the integrity checks analysis is useful in determining whether electricity is being stolen at a particular property, and the output of the analysis to GUI  84  is useful to alert the utility of the theft. The color-coded ranking system and organization of the data allows the utility to quickly understand the probability of electricity theft for every monitored system component and take the appropriate action such as, for example, sending a lineman to investigate system components or monitoring the status of particular components more closely in the future. It is important for utilities to have reliable indicators of electricity theft at specific locations in order to prevent the current losses amounting to billions of dollars. 
     Beneficially, embodiments of the invention thus provide a system for detecting electricity theft. The system includes a controller that receives electricity usage and demand data from a primary meter and a sub-meter and monitors changes in the measured demand data from the primary meter and the sub-meter and/or changes in demand data interpreted from the primary meter and sub-meter usage data over multiple intervals. If changes in the demand data from the sub-meter rise above a minimum threshold, the controller compares the changes in demand data from the sub-meter to corresponding changes in demand data from the primary meter measured at the same time. The controller then calculates a tamper percentage and/or coefficient that indicates how much the primary meter has been tampered with or bypassed. If a discrepancy exists between the demand data from the primary meter and the sub-meter, the tamper percentage and/or coefficient will indicate a percentage that the primary meter has been bypassed by a utility customer to reduce the electric utility bill. 
     Other embodiments of the invention provide that the system also includes a GUI that displays the results of an integrity checks analysis performed by the system controller. The system controller monitors or analyzes data from various meters and sensors on system components such as, for example, multiple transformers and primary meters. The data is analyzed to determine the probability that electricity theft is occurring at the system components. The system controller monitors for electricity theft indicators that designate a slight, medium, or high probability of theft. The controller ranks the indicators based on point system. The probability of theft determined by the controller based on the theft indicators for all monitored system components is then displayed on the GUI as a color according to a color-coded ranking system. The GUI displays the probability of theft as different colors in order to make it easy for the utility to take action. 
     According to one embodiment of the present invention, a system for detecting electricity theft with an integrity checks analysis includes a GUI configured to display information related to a flow of electricity within a power distribution system and a controller in communication with the GUI. The controller is configured to receive electrical readings taken by a plurality of electricity meters and examine the electrical readings of the plurality of electricity meters for electricity theft indicators. The controller is also configured to determine a probability that electricity is being stolen at each of the plurality of electricity meters according to any electricity theft indicators affiliated therewith and output each probability to the GUI for display. 
     According to another embodiment of the present invention, a method of detecting electricity theft in a power distribution system using an integrity checks analysis includes collecting electrical data from metering devices that measure a flow of electricity therethrough at a controller of the power distribution system. In addition, the method includes analyzing the electrical data with the controller to determine the existence of any electricity theft indicators at any metering devices, and based on the analysis of the electrical data, determining a status of each metering device with the controller, each status indicating a probability of electricity theft. The method further includes outputting each status from the controller to a GUI for display. 
     According to yet another embodiment of the present invention, a power system that detects electricity theft using an integrity checks analysis includes a plurality of meters measuring the flow of electricity therethrough, a GUI configured to display at least a portion of the electricity flow measurements of the plurality of meters, and a control system for performing an integrity check analysis of the power distribution system. The control system is configured to receive the electricity flow measurements of the plurality of meters and assess the electricity flow measurements against a plurality of electricity theft indicators. The control system is additionally configured to determine the probability of electricity theft at each of the plurality of meters based on any electricity theft indicators associated therewith. Furthermore, the control system is configured to assign a color-coded status to each of the plurality of meters based on the probability of electricity theft associated therewith and output each color coded status to the GUI for display. 
     The present invention has been described in terms of the preferred embodiment, and it is recognized that equivalents, alternatives, and modifications, aside from those expressly stated, are possible and within the scope of the appending claims.