A method and system for identifying load characteristics and determining electricity stealing behavior of an electric energy metering box

Abstract

The application discloses a kind of electric energy metering box load feature identification and electricity stealing behavior determination method and system.The method obtains the metering electrical quantity sequence and the outgoing line electrical quantity sequence of target metering branch, identifies load state change event and determines channel alignment parameter;Two electrical quantity sequences are aligned and event matching is carried out, and the load state change event that is not matched to corresponding metering event or event characteristic difference satisfies preset difference condition is determined as un-metered event;According to change direction and event characteristic, un-metered load input event and removal event are paired, and the running interval and load feature of un-metered load are determined;Electricity stealing behavior determination result is generated in combination with the working state of metering channel in running interval.The application can identify the complete running process of un-metered load, and distinguish electricity stealing behavior from metering channel anomaly.

Description

Technical Field

[0001] This invention pertains to electricity metering and abnormal electricity consumption monitoring, and particularly relates to a method and system for identifying load characteristics of electricity metering boxes and determining electricity theft. Background Technology

[0002] Electricity metering boxes are important metering devices between power supply lines and user power lines. With the development of smart meters and electricity information collection technology, they can monitor the user's electricity status through data such as current, voltage, power, and energy, and identify potential electricity theft based on abnormal electrical quantities, metering circuit abnormalities, or historical load changes.

[0003] Existing methods for identifying electricity theft typically establish a baseline of normal electricity consumption based on historical electricity consumption, load curves, industry electricity consumption patterns, or distribution area line losses. They then use fixed thresholds, data clustering, or classification models to screen for abnormal users. Some methods also determine metering anomalies by comparing current or power at different measurement locations. However, user loads are easily affected by seasonal changes, production plans, and lifestyle habits. Furthermore, sampling time offsets, measurement deviations, and communication delays may exist between different measurement channels, making it easy to misjudge normal electricity consumption changes as metering anomalies, thus leading to false positives for electricity theft.

[0004] Furthermore, single electrical quantity discrepancies can be caused by bypass power consumption or partial current diversion, or by communication interruptions, data loss, or measurement equipment errors. Existing methods struggle to verify unmetered loads by utilizing the correlation between load input, continuous operation, and load shedding. Consequently, it is difficult to accurately distinguish between electricity theft and metering channel anomalies, and it is also difficult to determine the operating range and unmetered electrical energy of unmetered loads, making it impossible to accurately judge electricity theft. Summary of the Invention

[0005] This invention provides a method and system for identifying load characteristics of electricity metering boxes and determining electricity theft, aiming to solve the above-mentioned technical problems.

[0006] This invention is implemented as follows: a method for identifying load characteristics of an electricity metering box and determining electricity theft, characterized by comprising: Obtain the metering electrical quantity sequence and outgoing line electrical quantity sequence of the target metering branch, identify the corresponding load state change events based on the two electrical quantity sequences, and determine the channel alignment parameters between the metering channel and the outgoing line observation channel; The two electrical quantity sequences are aligned according to the channel alignment parameters, and the load state change events in the two electrical quantity sequences are matched. Load state change events that are not matched with corresponding metering events in the outgoing observation channel or whose feature differences with the corresponding metering events meet the preset difference conditions are determined as unmetered events. Based on the direction of change and characteristics of each unmetered event, unmetered load input events and unmetered load cut-off events are paired, and the operating range and characteristics of the unmetered load are determined based on the pairing results. Based on the operating range of the unmetered load, the characteristics of the unmetered load, and the working status of the metering channel within the operating range, a determination result of the electricity theft behavior of the target metering branch is generated.

[0007] Preferably, the metered electrical quantity sequence is collected by an energy meter installed on the target metering branch, and the outgoing electrical quantity sequence is collected by an independent monitoring device installed at the downstream user outgoing line location of the energy meter.

[0008] Preferably, the method of identifying the corresponding load state change event based on two electrical quantity sequences includes: Determine the stable range before and after the change in electrical quantity; Determine the change in at least one electrical quantity between two stable intervals; When the change meets the preset event conditions, the change in electrical quantity between the two stable intervals is determined as a load state change event.

[0009] Preferably, determining the channel alignment parameters between the metering channel and the outgoing observation channel includes: Identify multiple corresponding load state change events from two electrical quantity sequences; Based on the occurrence time of each corresponding load state change event, determine the time offset between the metering channel and the outgoing observation channel; Based on the correspondence of event characteristics of each corresponding load state change event, the value mapping relationship between the metering channel and the outgoing observation channel is determined.

[0010] Preferably, the event characteristics include at least two of the following: active power change, reactive power change, current change, power factor change, harmonic variation characteristics, transient duration, and electrical quantity change rate.

[0011] Preferably, matching load state change events in two electrical quantity sequences includes: The event search range corresponding to the load state change event to be matched in the outgoing observation channel and the metering channel is determined according to the channel alignment parameters, and the value conversion is performed between the load state change event to be matched and the candidate metering events within the event search range. Filter candidate metering events from the candidate metering events that have the same direction of change as the load state change event to be matched; The corresponding metering event is determined based on the differences in event characteristics between the load state change event to be matched and each of the selected candidate metering events.

[0012] Preferably, pairing unmetered load input events with unmetered load shedding events includes: Candidate shelving events are identified from unmetered load shelving events following unmetered load input events; Based on the correspondence of event characteristics between the unmetered load input events and each candidate cut-off event, the paired unmetered load cut-off events are determined; The time range between the paired unmetered load input event and the unmetered load cut-off event is defined as the operating interval of the unmetered load.

[0013] Preferably, determining the characteristics of the unmetered load includes: The load change baseline for unmetered loads is determined based on the paired unmetered load input events and unmetered load removal events; Based on the load change benchmark and the electrical quantity difference between the two electrical quantity sequences within the operating range, the operating power, operating duration, and unmetered electrical energy of the unmetered load are determined.

[0014] Preferably, generating the electricity theft determination result includes: Acquire the communication status and metering data continuity of the metering channel within the operating range; When the metering channel is communicating normally, the metering data is continuous, and the unmetered load appears repeatedly in multiple monitoring cycles or the unmetered electrical energy meets the preset electrical energy conditions, a judgment result indicating that there is electricity theft is generated. When communication is interrupted or metering data is missing in the metering channel, a judgment result of metering channel abnormality is generated.

[0015] This invention also provides another system for identifying load characteristics of electricity metering boxes and determining electricity theft behavior, including an electricity meter, an independent monitoring device, a data acquisition device, a memory, and a processor; The electricity meter is installed on the target metering branch, and the independent monitoring device is installed at the user outgoing line downstream of the electricity meter; The data acquisition device is connected to the energy meter, the independent monitoring device and the processor respectively, and the memory is connected to the processor; The memory stores a computer program, and when the processor executes the computer program, it implements the method for identifying load characteristics of the electricity metering box and determining electricity theft behavior as described in any one of claims 1 to 9.

[0016] Compared with the prior art, the present invention has at least the following beneficial effects: This invention uses corresponding load state change events in the metering channel and the outgoing line observation channel as references to determine the time offset and value mapping relationship between the two channels. This makes the electrical quantity sequences generated by different acquisition devices comparable, reducing the impact of device clock asynchrony and measurement deviations on subsequent identification results. This invention extracts event features from electrical quantity changes caused by load connection or disconnection. By determining whether events in the outgoing line observation channel can be found in the metering channel, it identifies load changes that are not recorded or are significantly under-recorded by the energy meter. Compared to directly comparing the instantaneous power or cumulative energy of the two channels, it can more accurately pinpoint the occurrence time of unmetered loads.

[0017] This invention pairs unmetered load input and output events with opposite directions of change and corresponding event characteristics, and uses these paired events to define the operating range of the unmetered load. This allows isolated abnormal changes to be reconstructed into a complete load process with input, operation, and output times, thereby improving the reliability of the correlation between unmetered events. By integrating load change benchmarks and the electrical quantity differences between the two channels within the operating range, this invention determines the operating power, operating duration, and unmetered electrical energy of the unmetered load. It not only determines whether unmetered electricity consumption exists but also quantifies the energy loss caused by unmetered loads, providing data for abnormal electricity consumption verification and subsequent processing.

[0018] This invention combines the identification results of unmetered loads with the communication status and continuity of metering data in the metering channel to make a joint judgment. This allows for the differentiation between abnormal electricity consumption caused by loads bypassing metering or insufficient metering, and channel anomalies caused by communication interruptions or missing metering data. This reduces the likelihood of misjudging equipment malfunctions as electricity theft. Furthermore, this invention utilizes the repeatability of unmetered loads across multiple monitoring cycles and the conditions of unmetered electrical energy to form the basis for judgment. This provides multi-layered evidence support for determining electricity theft, including event correspondence, operating range, and electrical energy results, thereby improving the stability and verifiability of the judgment results. Attached Figure Description

[0019] Figure 1 This is an overall flowchart of the method of the present invention; Figure 2 Flowchart for identifying load status change events and determining channel alignment parameters; Figure 3 A flowchart for matching load state change events in two electrical quantity sequences; Figure 4 Flowchart for pairing unmetered load input events and unmetered load removal events; Figure 5 Flowchart for determining the characteristics of unmetered loads; Figure 6 Flowchart for determining electricity theft; Figure 7 This is a schematic diagram of the system of the present invention. Detailed Implementation

[0020] To make the objectives, technical solutions, and advantages of this invention clearer, the invention will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the invention.

[0021] This invention provides a system for identifying loads in an electricity metering box and determining electricity theft, such as... Figure 7 As shown.

[0022] It includes an electricity meter, independent monitoring equipment, data acquisition device, memory, and processor. The electricity meter is connected in series in the power supply line of the target metering branch to collect the metered electrical quantities of the target metering branch. The electricity meter can send the metered electrical quantity sequence to the data acquisition device via RS-485, carrier communication, wireless communication, or other data interfaces.

[0023] The target metering branch refers to any user metering branch in the electricity metering box that requires load characteristic identification and electricity theft determination.

[0024] The independent monitoring device is installed downstream of the electricity meter at the user's outgoing line. This location, after the metering output of the electricity meter, enables the detection of the actual current and power entering the user's line. Even when a bypass exists that bypasses the electricity meter and reconnects to the user's outgoing line, the independent monitoring device can still detect changes in electrical quantities caused by the bypass load.

[0025] Independent monitoring equipment may include a current transformer, voltage acquisition circuit, metering chip, and communication interface. This independent monitoring equipment is separate from the electricity meter and does not use the current sampling signal from the electricity meter's internal circuitry as the outgoing electrical quantity.

[0026] The data acquisition device receives the metered electrical quantity sequences from the electricity meter and the outgoing line electrical quantity sequences from the independent monitoring equipment, and then sends both sequences to the processor. The device also records the data acquisition time, communication status, data frame number, and the location of missing data.

[0027] The memory stores the computer program, two electrical quantity sequences, channel alignment parameters, event identification conditions, event matching conditions, event pairing conditions, and electricity theft determination conditions. The processor executes the computer program to complete load state change event identification, channel alignment, event matching, unmetered event pairing, unmetered load characteristic determination, and electricity theft determination.

[0028] Among them, the metering channel refers to the electrical quantity acquisition channel formed by the electricity meter set on the target metering branch and its data transmission path.

[0029] The outgoing observation channel refers to the electrical quantity acquisition channel formed by independent monitoring equipment installed at the downstream user outgoing line location of the electricity meter and its data transmission path.

[0030] The electrical quantity sequence refers to one or more data points among current, voltage, active power, reactive power, power factor, and harmonics that are collected or output by an electricity meter in chronological order.

[0031] Outgoing electrical quantity sequence refers to one or more data points among current, voltage, active power, reactive power, power factor, and harmonics collected by independent monitoring equipment in chronological order.

[0032] A load state change event refers to the process in which the electrical load in the target metering branch is put into operation, disconnected, or its operating power changes, causing at least one electrical quantity to change from a stable state before the change to a stable state after the change.

[0033] A metering event is a load state change event identified from a sequence of metered electrical quantities.

[0034] Unmetered events refer to load state change events that are not matched with corresponding metered events in the online observation channel, or that are matched with corresponding metered events but whose event characteristics differ from the preset difference conditions.

[0035] The processor executes the method for identifying load characteristics of electricity metering boxes and determining electricity theft behavior provided in the following embodiments.

[0036] like Figure 1 As shown, the method steps of this embodiment include S100 to S400.

[0037] S100: Obtain the metering electrical quantity sequence and outgoing line electrical quantity sequence of the target metering branch, identify the corresponding load state change event based on the two electrical quantity sequences, and determine the channel alignment parameters between the metering channel and the outgoing line observation channel.

[0038] The metered electrical quantity sequence is collected by the energy meter installed on the target metering branch, while the outgoing electrical quantity sequence is collected by an independent monitoring device installed at the downstream user outgoing line location of the energy meter.

[0039] Obtain the metered electrical quantity sequence and outgoing electrical quantity sequence of the target metering branch. Both electrical quantity sequences must include at least the sampling time, active power, and current, and may also include reactive power, power factor, harmonic current, transient duration, and rate of change of electrical quantity.

[0040] In this embodiment, the data sampling period of the electricity meter is 1 second, and the data sampling period of the independent monitoring device is 1 second. For cases with different sampling periods, the two electrical quantity sequences can be resampled according to the larger sampling period, but the same time point after resampling is not directly regarded as strictly synchronized.

[0041] For specific steps on load state change event identification, please refer to [link / reference]. Figure 2 This includes steps S110 to S160.

[0042] In step S110, the stable intervals before and after the change in electrical quantity are determined respectively; in step S120, the change in at least one electrical quantity between the two stable intervals is determined; in step S130, when the change in quantity meets the preset event conditions, the change in electrical quantity between the two stable intervals is determined as a load state change event.

[0043] For any given time point to be detected, a first sliding window is set before that time point, and a second sliding window is set after that time point. The data within the first sliding window forms the stable interval before the change in electrical quantity, and the data within the second sliding window forms the stable interval after the change in electrical quantity.

[0044] Taking active power as an example, calculate the average active power in the first stable interval and the average active power in the second stable interval respectively:

[0045] The change in active power is:

[0046] Where N1 and N2 are the number of sampling points in the first stable interval and the second stable interval, respectively.

[0047] When the active power fluctuations in the first and second stable intervals do not exceed the corresponding stable thresholds, and |ΔP| reaches the active power event threshold, the change in electrical quantity between the two stable intervals is determined as a load state change event.

[0048] When ΔP>0, the event is identified as a load input event; when ΔP<0, the event is identified as a load cut-off event.

[0049] In one implementation, the length of both the first and second sliding windows is 10 seconds, the difference between the maximum and minimum active power values ​​within the stable interval is no greater than 5% of the average value of the stable interval, and the active power event threshold is 0.1 kW. These values ​​can be adjusted according to the user load level and the measurement accuracy of the independent monitoring equipment.

[0050] For loads with continuously changing power, such as variable frequency air conditioners, charging piles, or variable frequency motors, when the electrical quantity changes from the first stable operating level to the second stable operating level, and the change meets the preset event conditions, the change will also be identified as a load state change event.

[0051] In step S140, multiple corresponding load state change events are determined from the two electrical quantity sequences.

[0052] Before obtaining the channel alignment parameters, first set the initial time tolerance and initial feature tolerance.

[0053] In this embodiment, the initial time tolerance is 5 seconds. For any load status change event in the outgoing observation channel, metering events that occur within 5 seconds of the event, have the same direction of change, and whose active power change differs by no more than 30% are selected from the metering channel to form an initial candidate event pair.

[0054] When multiple candidate metering events exist within the same time frame, the differences in initial event characteristics are determined by combining the changes in reactive power, current, and harmonics, and the candidate metering event with the smallest differences in initial event characteristics is selected.

[0055] To avoid misusing unmetered events for channel alignment, this embodiment selects only event pairs whose event characteristic differences are less than the initial consistency threshold and which repeatedly form a stable correspondence within multiple monitoring periods as corresponding load state change events.

[0056] Step S150: Determine the time offset between the metering channel and the outgoing observation channel based on the occurrence time of each corresponding load state change event.

[0057] Let t be the time when the i-th corresponding event occurs in the metering channel. m,i The occurrence time in the outgoing observation channel is t. o,i Then the time difference of the event pair is:

[0058] The time offset between two channels is determined based on the time differences between multiple event pairs. In this embodiment, the median of the multiple time differences is used as the time offset:

[0059] Using the median can reduce the impact of individual event identification time deviations on the time offset. In other implementations, the time offset can also be determined using the average value after removing outliers, the weighted average value, or the fitted value.

[0060] Step S160: Determine the value mapping relationship between the metering channel and the outgoing observation channel based on the corresponding event characteristics of each load state change event.

[0061] Let F be a certain event feature of the i-th corresponding event in the outgoing observation channel. o,i The corresponding event characteristic in the metering channel is F. m,i The value mapping relationship is expressed as:

[0062] Where aF is the scaling parameter of the corresponding event feature, and bF is the offset parameter of the corresponding event feature. This is to convert the event characteristics of the outgoing observation channel to the characteristic values ​​of the measurement channel.

[0063] Based on multiple corresponding load state change events, aF and bF are determined through least squares fitting, robust regression, or piecewise fitting.

[0064] For different event characteristics such as changes in active power, changes in reactive power, and changes in current, corresponding value mapping relationships can be determined separately.

[0065] When there is a significant difference in the measurement ratio under low-power load and high-power load, multiple value intervals can be divided according to the load change, and value mapping relationships can be determined for different value intervals.

[0066] The time offset and the magnitude mapping relationship together constitute the channel alignment parameters.

[0067] Channel alignment parameters can be updated according to a preset cycle. When the feature ratios of multiple normal corresponding events gradually change in the same direction, it is determined that there may be independent monitoring device drift, and the value mapping relationship is re-determined; when the feature ratio changes suddenly and cannot be verified by multiple normal events, the channel alignment parameters are not updated temporarily.

[0068] S200, align the two electrical quantity sequences according to the channel alignment parameters, match the load state change events in the two electrical quantity sequences, and determine the load state change events in the outgoing observation channel that do not match the corresponding metering events or whose feature differences with the corresponding metering events meet the preset difference conditions as unmetered events.

[0069] See Figure 3 This includes steps S210 to S230. S210, determine the event search range in the metering channel corresponding to the load state change event to be matched in the outgoing observation channel according to the channel alignment parameters, and perform value conversion between the event to be matched and the candidate metering event.

[0070] S220: Select candidate metering events from the candidate metering events that have the same direction of change as the load state change event to be matched.

[0071] S230, determine the corresponding metering event based on the difference in event characteristics between the load state change event to be matched and each of the selected candidate metering events.

[0072] The event occurrence times of the two electrical quantity sequences are aligned based on the time offset. For the event time t in the outgoing observation channel... o Its corresponding time on the metering channel time scale is:

[0073] by Set the event search range for the center and filter candidate metering events that fall within the event search range from the metering channels.

[0074] Normalized calculation of time difference:

[0075] t m,j Let t be the occurrence time of the j-th candidate measurement event; o +Δt represents the time of occurrence of the event to be matched after alignment; S t The time normalization scale can be either the half-width of the event search range or a preset maximum allowed time difference; the normalized D t,j It is a dimensionless numerical value.

[0076] This embodiment uses the differences in event characteristics to determine the degree of matching between the event to be matched and the candidate measurement event:

[0077] Among them, D j D represents the event characteristic differences of the j-th candidate measurement event; t,j For time difference; D r,j w represents the normalized difference of the r-th event feature; t and w r Corresponding weights; the sum of all weights is 1.

[0078] Normalized differences can be expressed as:

[0079] Among them, F m,r,j Let r be the event feature of the candidate measurement event. S represents the r-th event feature of the event to be matched after conversion. r R is the normalization scale corresponding to the event features, where R is the total number of event features involved in event matching, and r is the event feature index. And all weights are non-negative.

[0080] Candidate measurement events with the smallest difference in event characteristics and not exceeding the matching threshold are identified as the corresponding measurement events.

[0081] When a load status change event in the outgoing observation channel does not find a corresponding metering event within the event search range, it is identified as a completely unmatched unmetered event.

[0082] When a corresponding metering event can be found, but the difference in active power change, reactive power change, current change, or other event characteristics between the two events meets the preset difference conditions, the load state change event is identified as a partially unmetered event.

[0083] For example, after conversion according to the value mapping relationship, the change in active power in the outgoing observation channel should correspond to 1.8kW, while the corresponding event in the metering channel only changes by 0.7kW. The difference between the two exceeds 0.3kW and the difference ratio exceeds 20%, so the event is identified as a partially unmetered event.

[0084] S300, based on the change direction and event characteristics of each unmetered event, pairs the unmetered load input event with the unmetered load cut-off event, and determines the operating range and characteristics of the unmetered load based on the pairing results.

[0085] like Figure 4 As shown, it includes steps S310 to S330.

[0086] S310, determine candidate cut-off events from unmetered load cut-off events located after unmetered load input events.

[0087] S320, based on the correspondence of event characteristics between the unmetered load input events and each candidate cut-off event, determine the paired unmetered load cut-off events.

[0088] S330, the time range between the paired unmetered load input event and the unmetered load cut-off event is determined as the operating interval of the unmetered load.

[0089] For any unmetered load input event, determine candidate load cut-off events from the unmetered load cut-off events that follow that event.

[0090] For the same unmetered load, the changes in active and reactive power during the input and output events are in opposite directions but have similar absolute values, exhibiting a corresponding harmonic variation characteristic. Therefore, the degree of correspondence between input and candidate output events can be determined using the following pairing differences:

[0091] Where ε is a positive number set to prevent the denominator from being zero, and its value can be determined according to the measurement accuracy of the electrical quantity; C H To determine the similarity of harmonic variation features between input events and candidate resection events, C H The value range of C is [0,1]. H The closer the value is to 1, the more similar the harmonic variation characteristics of the two events are; αP, αQ, and αH are the weights corresponding to the active power, reactive power, and harmonic variation characteristics, respectively, and satisfy the following:

[0092] Furthermore, the specific calculation method for CH should be added here, for example, using cosine similarity:

[0093] Among them, H on and H off These are the harmonic feature vectors formed by the harmonic changes corresponding to the input and removal events, respectively. Since the directions of change for input and removal are opposite, the harmonic feature vector for the removal event is inverted before calculating the similarity.

[0094] When the pairing difference does not exceed the pairing threshold and the load operation duration is within the preset duration range, the candidate cut-off event is identified as an unmetered load cut-off event paired with the input event.

[0095] When multiple candidate resection events meet the conditions, the candidate resection event with the smallest pairing difference is selected first. If multiple loads are running concurrently, a pairing matrix is ​​formed based on the pairing differences between each input event and each candidate resection event, and the pairing relationship is determined with the goal of minimizing the sum of the pairing differences of all events.

[0096] The time range between the paired unmetered load input event and the unmetered load cut-off event is defined as the operating interval of the unmetered load.

[0097] Based on the electrical quantity difference between the metered electrical quantity sequence and the outgoing electrical quantity sequence within the operating range to be verified, it is determined whether the electrical quantity difference persists. Based on the electrical quantity difference between the two electrical quantity sequences after an unmetered load shedding event, it is determined whether the electrical quantity difference has returned to the range before the unmetered load energizing event. When the electrical quantity difference persists within the operating range to be verified and returns to the range before the energizing event after the unmetered load shedding event, the operating range to be verified is determined as the operating range of the unmetered load.

[0098] To rule out the possibility of two random events being mismatched, the electrical quantity differences between the two electrical quantity sequences are continuously compared within the operating range.

[0099] Let P be the baseline for the channel power difference before the pairing event occurs. d,0 The outgoing power within the operating range, after conversion, is P. oc(t) The power of the metering channel is P. m(t) The unmetered power is:

[0100] Within the operating range, if the unmetered power at all sampling points at a preset ratio is consistent with the load change benchmark corresponding to the input event, it is determined that the electrical quantity difference persists within the operating range.

[0101] For example, if the difference between the unmetered power and the load change benchmark does not exceed 15% of the load change benchmark at no less than 80% of the effective sampling points within the operating range, then the continuous verification is passed.

[0102] Set up a recovery verification interval after an unmetered load shedding event. Calculate the electrical quantity difference between the two channels within the recovery verification interval.

[0103] When the difference between the channel power difference within the recovery verification interval and the channel power difference benchmark before the input event does not exceed the recovery threshold, it is determined that the channel difference has been recovered after the unmetered load was removed.

[0104] After verification of the continuity of the operating interval and the recovery of differences after the shedding, the paired events were identified as a complete input-operation-shearing process formed by the same unmetered load.

[0105] like Figure 5 As shown, the determination of unmetered load characteristics includes steps S340 to S350.

[0106] S340, determine the load change benchmark for unmetered loads based on paired unmetered load input events and unmetered load removal events.

[0107] S350, based on the load change benchmark and the electrical quantity difference between the two electrical quantity sequences within the operating range, determine the operating power, operating duration, and unmetered electrical energy of the unmetered load.

[0108] The load change baseline is determined based on paired power initiation and power outage events. The load change baseline can be the average of the absolute values ​​of the power changes during power initiation and power outage events, or it can be the median or steady-state average of the unmetered power over the operating range.

[0109] The operating power of unmetered loads can be expressed as:

[0110] Where N is the number of valid sampling points within the operating range.

[0111] The operating duration of unmetered load is:

[0112] Among them, t on t represents the time of occurrence of unmetered load input events. off The occurrence time of the unmeasured load shedding event paired with it.

[0113] Unmetered electrical energy is:

[0114] When the power unit is kW and the sampling time interval unit is seconds, the unmetered electrical energy can be expressed as:

[0115] Unmetered load characteristics include operating power, operating duration, and unmetered electrical energy, and may also include power factor, harmonic variation characteristics, and repetitive operating cycles.

[0116] S400, based on the operating range of the unmetered load, the characteristics of the unmetered load, and the working status of the metering channel within the operating range, generate the electricity theft behavior determination result of the target metering branch.

[0117] like Figure 6 As shown, steps S410 to S430 are included. S410, acquire the communication status and metering data continuity of the metering channel within the operating range.

[0118] S420: When the metering channel communication is normal, the metering data is continuous, and the unmetered load appears repeatedly in multiple monitoring cycles or the unmetered electrical energy meets the preset electrical energy conditions, a judgment result indicating that electricity theft has occurred is generated.

[0119] S430 generates a judgment result of metering channel abnormality when communication is interrupted or metering data is missing in the metering channel.

[0120] Communication status can be determined based on the electricity meter's communication heartbeat, data frame response status, and communication anomaly records. Metering data continuity can be determined based on the time interval between adjacent data, data frame sequence number, and the proportion of missing data.

[0121] A determination of electricity theft is generated when the electricity meter communication is normal and the metering data is continuous within the operating range, and any of the following conditions are met: Unmetered loads with similar characteristics repeatedly appear in multiple monitoring periods; The cumulative unmetered electrical energy corresponding to one or more unmetered loads reaches the preset electrical energy condition.

[0122] When communication is interrupted or metering data is missing in the metering channel, a judgment result indicating the existence of electricity theft is not generated directly; instead, a judgment result indicating an abnormal metering channel is generated.

[0123] When the proportion of values ​​from independent monitoring devices changes slowly and continuously across multiple normal corresponding events, an independent monitoring device drift alert is generated, and the channel alignment parameters are updated or redefined. Only when a sudden change occurs in a single event that cannot be verified by other electrical quantities is the event marked as invalid and not used for determining electricity theft.

[0124] This invention establishes channel alignment parameters between the electricity meter's metering channel and its downstream outgoing observation channel. By aligning the electrical quantity sequences collected from the two channels in time and converting their values, it reduces the impact of sampling clock deviations and measurement scale differences on load event matching results, improving the accuracy of the correspondence between load state change events. Furthermore, by matching load state change events in the two channels, outgoing load events that do not match corresponding metering events or whose event characteristics meet preset difference conditions are identified as unmetered events. This allows for the identification of electrical loads that the electricity meter failed to record properly at the load switching process level, reducing misjudgments caused by relying solely on cumulative electricity differences.

[0125] This invention pairs unmetered load input events with unmetered load disconnection events based on the direction of change and event characteristics of unmetered events. It also combines the persistence of electrical quantity differences between the two channels within the operating range and the recovery of differences after disconnection to determine the operating range, operating power, operating duration, and unmetered electrical energy of the unmetered load. This can form a complete unmetered load operation process and improve the reliability and traceability of unmetered load identification results.

[0126] In summary, this invention enables continuous processing from dual-channel data alignment, load status change event matching, unmetered event identification, pairing of power-on and power-off events, determination of operating range, to determination of electricity theft. It identifies unmetered loads without relying on pre-registration of user load types, providing a reliable basis for monitoring abnormal electricity consumption in electricity metering boxes, locating electricity theft, and estimating unmetered energy.

[0127] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of the present invention should be included within the protection scope of the present invention.

Claims

1. A method for identifying load characteristics of an electricity metering box and determining electricity theft, characterized in that, include: Obtain the metering electrical quantity sequence and outgoing line electrical quantity sequence of the target metering branch, identify the corresponding load state change events based on the two electrical quantity sequences, and determine the channel alignment parameters between the metering channel and the outgoing line observation channel; The two electrical quantity sequences are aligned according to the channel alignment parameters, and the load state change events in the two electrical quantity sequences are matched. Load state change events that are not matched with corresponding metering events in the outgoing observation channel or whose feature differences with the corresponding metering events meet the preset difference conditions are determined as unmetered events. Based on the direction of change and characteristics of each unmetered event, unmetered load input events and unmetered load cut-off events are paired, and the operating range and characteristics of the unmetered load are determined based on the pairing results. Based on the operating range of the unmetered load, the characteristics of the unmetered load, and the working status of the metering channel within the operating range, a determination result of the electricity theft behavior of the target metering branch is generated.

2. The method for identifying load characteristics of electricity metering boxes and determining electricity theft behavior according to claim 1, characterized in that, The metered electrical quantity sequence is collected by the energy meter installed on the target metering branch, and the outgoing electrical quantity sequence is collected by an independent monitoring device installed at the downstream user outgoing line location of the energy meter.

3. The method for identifying load characteristics of electricity metering boxes and determining electricity theft behavior according to claim 1, characterized in that, Identify the corresponding load state change events based on two electrical quantity sequences, including: Determine the stable range before and after the change in electrical quantity; Determine the change in at least one electrical quantity between two stable intervals; When the change meets the preset event conditions, the change in electrical quantity between the two stable intervals is determined as a load state change event.

4. The method for identifying load characteristics of electricity metering boxes and determining electricity theft behavior according to claim 1, characterized in that, Determine the channel alignment parameters between the metering channel and the outgoing observation channel, including: Identify multiple corresponding load state change events from two electrical quantity sequences; Based on the occurrence time of each corresponding load state change event, determine the time offset between the metering channel and the outgoing observation channel; Based on the correspondence of event characteristics of each corresponding load state change event, the value mapping relationship between the metering channel and the outgoing observation channel is determined.

5. The method for identifying load characteristics of electricity metering boxes and determining electricity theft behavior according to claim 1, characterized in that, The event characteristics include at least two of the following: changes in active power, changes in reactive power, changes in current, changes in power factor, harmonic variation characteristics, transient duration, and rate of change of electrical quantities.

6. The method for identifying load characteristics of electricity metering boxes and determining electricity theft behavior according to claim 1, characterized in that, Matching load state change events in two electrical quantity sequences, including: The event search range corresponding to the load state change event to be matched in the outgoing observation channel and the metering channel is determined according to the channel alignment parameters, and the value conversion is performed between the load state change event to be matched and the candidate metering events within the event search range. Filter candidate metering events from the candidate metering events that have the same direction of change as the load state change event to be matched; The corresponding metering event is determined based on the differences in event characteristics between the load state change event to be matched and each of the selected candidate metering events.

7. The method for identifying load characteristics of electricity metering boxes and determining electricity theft behavior according to claim 1, characterized in that, Pairing unmetered load input events with unmetered load shedding events includes: Candidate shelving events are identified from unmetered load shelving events following unmetered load input events; Based on the correspondence of event characteristics between the unmetered load input events and each candidate cut-off event, the paired unmetered load cut-off events are determined; The time range between the paired unmetered load input event and the unmetered load cut-off event is defined as the operating interval of the unmetered load.

8. The method for identifying load characteristics of electricity metering boxes and determining electricity theft behavior according to claim 7, characterized in that, Determining the characteristics of the unmetered load includes: The load change baseline for unmetered loads is determined based on the paired unmetered load input events and unmetered load removal events; Based on the load change benchmark and the electrical quantity difference between the two electrical quantity sequences within the operating range, the operating power, operating duration, and unmetered electrical energy of the unmetered load are determined.

9. The method for identifying load characteristics of an electricity metering box and determining electricity theft as described in claim 8, characterized in that, The generation of the electricity theft determination result includes: Acquire the communication status and metering data continuity of the metering channel within the operating range; When the metering channel is communicating normally, the metering data is continuous, and the unmetered load appears repeatedly in multiple monitoring cycles or the unmetered electrical energy meets the preset electrical energy conditions, a judgment result indicating that there is electricity theft is generated. When communication is interrupted or metering data is missing in the metering channel, a judgment result of metering channel abnormality is generated.

10. A system for identifying load characteristics of an electricity metering box and determining electricity theft, characterized in that, Includes electricity meters, independent monitoring equipment, data acquisition devices, memory, and processors; The electricity meter is installed on the target metering branch, and the independent monitoring device is installed at the user outgoing line downstream of the electricity meter; The data acquisition device is connected to the energy meter, the independent monitoring device and the processor respectively, and the memory is connected to the processor; The memory stores a computer program, and when the processor executes the computer program, it implements the method for identifying load characteristics of the electricity metering box and determining electricity theft behavior as described in any one of claims 1 to 9.

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