A power stealing monitoring method based on power energy storage system

Abstract

The present application relates to the technical field of power management, and particularly relates to a kind of anti-electricity-stealing monitoring method based on power energy storage system, comprising: real-time acquisition of the charge-discharge electric quantity data of power energy storage system energy storage equipment, based on the charge-discharge electric quantity data of power energy storage system energy storage equipment, create the contrast line graph indicating the change of charge-discharge electric quantity of energy storage equipment;Monitoring the time threshold covered by the horizontal axis in the contrast line graph, when the time threshold covered by the horizontal axis in the contrast line graph is not less than two weeks, the line segment corresponding to each week indicating the change of charge-discharge of energy storage equipment is extracted in the contrast line graph, the present application creates the contrast line graph indicating the change of charge-discharge electric quantity of energy storage equipment by the charge-discharge electric quantity data of power energy storage system energy storage equipment, thereby realizing independent anti-electricity-stealing monitoring of each energy storage equipment, in the process of anti-electricity-stealing monitoring, according to the line segment indicating the change of electric quantity in the contrast line graph, comprehensive anti-electricity-stealing monitoring is carried out from the energy storage system end and the electricity user end.

Description

Technical Field

[0001] The present invention relates to the technical field of power management, and in particular to an anti-electricity theft monitoring method based on an electric energy storage system. Background Art

[0002] The issue of electricity theft within energy storage systems is a growing concern. Some criminals may steal electricity by tampering with equipment data or illegally connecting lines. This not only harms the interests of power supply companies but also threatens the stable operation of the power system. Strengthening monitoring technology, improving management systems, and increasing law enforcement are key to addressing the issue.

[0003] The invention patent with application number 202110237945.5 discloses a detection system suitable for group fixed-ratio electricity theft behavior, which is characterized by including: a preprocessing module, a detection module and a judgment module; the preprocessing module is connected to the detection module and performs data transmission: the detection module is connected to the judgment module and performs data transmission; the preprocessing module is used to: ① extract the user's electricity data per unit time from the electricity consumption information acquisition system, and perform vectorization and standardization processing on the data, and input the data into the detection module; ② extract the electricity data of the line loss of the substation per unit time from the integrated line loss management system, and perform vectorization and standardization processing on the data, and input the data into the detection module; the detection module is used to: ① use the increasing property of the covariance between the standardized substation line loss electricity vector and the meter electricity consumption vector of the fixed-ratio electricity theft user to detect group fixed-ratio electricity theft behavior; ② judge whether the electricity consumption scenario is a fixed-ratio electricity theft scenario; ③ output the set C of suspected electricity theft users sus , and transmits it to the judgment module; the judgment module is used to calculate the user's suspicion of electricity theft.

[0004] The application aims to solve the problem of "taking into account that most of the electricity theft methods that start from hardware tampering with electricity meters are manifested as fixed-ratio electricity theft, and the current trend of electricity theft is increasingly showing a group and collective trend."

[0005] However, electricity theft in energy storage systems can occur anywhere in the transmission circuit between the energy storage system and the electricity user. Accurate, comprehensive, and real-time monitoring of electricity theft is an urgent issue that needs to be addressed.

[0006] To this end, we propose an anti-electricity theft monitoring method based on power energy storage system. Summary of the Invention

[0007] In view of the above shortcomings of the prior art, the present invention provides an anti-electricity theft monitoring method based on an electric energy storage system, which solves the technical problems raised in the above background technology.

[0008] To achieve the above objectives, the present invention is implemented through the following technical solutions:

[0009] An anti-electricity theft monitoring method based on an electric energy storage system, comprising:

[0010] Real-time collection of charge and discharge data of energy storage devices in the power energy storage system, and creation of a comparative line chart showing changes in charge and discharge data of the energy storage devices based on the charge and discharge data of the energy storage devices in the power energy storage system;

[0011] Monitoring the time threshold covered by the horizontal axis of the comparison line graph. When the time threshold covered by the horizontal axis of the comparison line graph is not less than two weeks, extracting the line segments representing the charge and discharge changes of the energy storage device corresponding to each consecutive week in the comparison line graph, further segmenting the line segments representing the charge and discharge changes of the energy storage device, and then analyzing the differentiated time domains on the line segments representing the charge and discharge changes of the energy storage device based on the segmentation results;

[0012] During the next week not recorded in the comparison line chart, the time domain corresponding to the differentiated time domain captures the charging and discharging data of the energy storage system's energy storage equipment and the electricity consumption data of the electricity users served by the energy storage system. Based on the charging and discharging data of the energy storage equipment and the electricity consumption data of the electricity users served by the energy storage system, an analysis is conducted to determine whether there is electricity theft at the initial end of the energy storage system, the probability of electricity theft among the electricity users served by the energy storage system, and the users who are found to be the victims of electricity theft.

[0013] The analysis logic of whether there is electricity theft at the initial end of the power energy storage system is expressed as follows:

[0014]

[0015] Where: E out Output power to the power storage system; I out is the output current of the power energy storage system; P out is the active power output of the power energy storage system; L is the total length of the power distribution line of the power energy storage system; U out is the output voltage of the power energy storage system; S out is the cross-sectional area of ​​the distribution line conductor; is the power factor; t out is the output time of the power energy storage system; E0 is the compensation; u is the total number of electricity users served by the power energy storage system; E v is the electricity consumption of the vth electricity user;

[0016] Among them, the power consumption of the electricity user is the output time t of the power storage system out If the above formula is established, it means that there is electricity theft at the initial end of the power storage system. Otherwise, it means that there is no electricity theft at the initial end of the power storage system. The compensation E0 is defined by the power storage system end management user, and the compensation E0

[0017]

[0018] Evaluate the load on the energy storage system from electricity users who engage in electricity theft, and generate a processing queue for electricity users who engage in electricity theft based on the load on the energy storage system from the electricity users;

[0019] Among them, after the processing queue of electricity users with electricity theft is generated, the power storage system manages the user offline and performs electricity theft line detection on the power circuits of the electricity users with electricity theft in turn.

[0020] Furthermore, the charge and discharge power data of the energy storage device of the power energy storage system is collected at the charge and discharge ends of the energy storage device based on a specified collection frequency. In the comparative line graph, the horizontal axis represents the corresponding timestamp of the collection frequency, the vertical axis represents the charge and discharge power, and the broken line representing the charge data and the broken line representing the discharge data are distinguished by different colors.

[0021] The frequency of collecting charging and discharging power data of the energy storage equipment in the power energy storage system follows the following rules: the more electricity users the power energy storage system serves, the more and longer the historical daily discharge volume and daily discharge time of the power energy storage system, the faster the collection frequency.

[0022] Furthermore, the frequency of collecting the charge and discharge data of the energy storage device in the power energy storage system specifically complies with:

[0023]

[0024] Where: p is the frequency of collecting charge and discharge data of the energy storage device in the power energy storage system; p0 is the base number of the collection frequency; m is the number of electricity users served by the energy storage device in the power energy storage system; n is the number of historical operation days of the energy storage device in the power energy storage system; Q i is the discharge amount of the energy storage device on day i; t use is the discharge duration of the energy storage device on day i; t0 is the daily service duration of the energy storage device; P is the final application acquisition frequency; f(p) is the constraint function;

[0025] in, Express The average, Express The average, represents the ratio of the discharge time of the energy storage device to the service time on day i, (t0-t use ) iIt represents the idle time of the energy storage device on day i. The daily service time t0 of the energy storage device and the acquisition frequency base p0 are customized by the user of the power energy storage system management end. The daily service time t0 of the energy storage device is set to 24 by default. The acquisition frequency p of the charge and discharge power data of the energy storage device in the power energy storage system is rounded up. The constraint function f(p) is based on the p value. If 3≤p≤24, then P=f(p)=p. Otherwise, the difference between the p value in f(p) and 3 is the smallest, P=3, and the difference between the p value in f(p) and 24 is the smallest, P=24. The unit of the final application acquisition frequency P is: times / day.

[0026] Furthermore, when segmenting the line segments representing the charge and discharge changes of the energy storage device, the number of segmentations is seven. When further analyzing the differentiated time domains on the line segments representing the charge and discharge changes of the energy storage device based on the segmentation results, similarity recognition is first performed on each segmented sub-segment representing the charge and discharge changes of the energy storage device, and based on the similarity recognition results, the differentiated time domain is determined.

[0027] Furthermore, the similarity recognition logic of the sub-segments representing the charge and discharge changes of the energy storage device is expressed as:

[0028]

[0029] Where: SIMM(L1,L′1) is the similarity between the sub-segments L1 and L′1 representing the charge and discharge changes of the energy storage device; Q1(max) use is the maximum value of the line segment representing discharge in sub-segment L1; Q1′(max) use is the maximum value of the line segment representing discharge in sub-segment L′1; Q1(min) use is the minimum value of the line segment representing discharge in sub-segment L1; Q1′(min) use is the minimum value of the line segment representing discharge in the sub-line segment L′1; γ is the first correction factor; m use is the set of sub-segments representing discharge in L1 and L′1; Q 1j Q1′ is the vertical axis value on the line graph corresponding to the jth point in the sub-segment L1; j is the vertical axis value on the line graph corresponding to the j-th point in the sub-segment L′1; Q1(max) in The maximum value of the charging segment in sub-segment L1; Q1 (min) in The minimum value of the charging segment in the sub-segment L1; Q1′(max) in The maximum value of the segment marked with charging in sub-segment L′1; Q1′ (min) in is the minimum value of the segment marked with charging in the sub-segment L′1; τ is the second correction factor;

[0030] Among them, L1 and L′1 are derived from the sub-segments of the same day in the line segments corresponding to the continuous weekly segments representing the charging and discharging changes of the energy storage equipment. The larger the SIMM(L1, L′1), the higher the similarity between the two groups of sub-segments. When determining the differentiated time domain, the user of the power energy storage system defines the differentiated judgment threshold. Based on the set differentiated judgment threshold and SIMM(L1, L′1), the paired time domains of the sub-segments belonging to SIMM(L1, L′1) within the differentiated judgment threshold are determined to be differentiated time domains.

[0031] Furthermore, the value of the first correction factor γ is subject to the following conditions: if the numerator of the fraction in the correction target bracket is not greater than the denominator, the first correction factor is 1; if the numerator of the fraction in the correction target bracket is greater than the denominator, the first correction factor is -1;

[0032] The value of the second correction factor τ follows: Then the second correction factor takes the value of 1. Then the second correction factor takes the value of -1;

[0033] Among them, the time threshold corresponding to L1 is always earlier than the time threshold corresponding to L′1.

[0034] Furthermore, the analysis logic of the probability that the power storage system serves electricity users and there is electricity theft is expressed as follows:

[0035]

[0036] Where: SEI is the electricity theft determination index, that is, the probability; P m is the actual measured power value; P e is the expected power value; I m is the actual measured current value; I e is the expected current value; V m is the actual measured voltage value; V e is the expected voltage value; a, b, c are weights;

[0037] The electricity consumption data of the electricity users served by the power system include: m 、P e , I m , I e 、V m 、V e After obtaining the electricity theft determination index SEI, the user of the power storage system defines the electricity theft determination threshold. The electricity theft determination threshold is initially set to 20%, that is, if the electricity theft determination index SEI>20%, it is determined that the electricity user has committed electricity theft. e , I e 、V eThe weights a, b, and c are greater than zero and the sum of the three is 1, which are defined by the end user of the power storage system according to the power supply standard.

[0038] Further, the analysis logic of the user with electricity stealing behavior is represented as:

[0039] The determination results of whether the electricity stealing behavior exists for each electricity user based on the electricity stealing determination index SEI are recorded, and when the determination results of the cumulative records of the same electricity user contain not less than two times of being determined as existing electricity stealing behavior, the electricity user is determined as the user with electricity stealing behavior;

[0040] The user determined as existing electricity stealing behavior is disconnected from the real-time power transmission connection of the power storage system, and only the end user of the power storage system has the manual opening permission.

[0041] Further, when the electricity user determined as existing electricity stealing behavior is disconnected from the power transmission connection between the electricity user and the power storage system, the end user of the power storage system synchronously feeds back the determination information of existing electricity stealing behavior to the disconnected electricity user;

[0042] The determination information includes the determination results of whether the electricity stealing behavior exists each time and the determination time stamp.

[0043] Further, the evaluation logic of the electricity user with electricity stealing behavior on the load of the power storage system is represented as:

[0044]

[0045] In the formula, ε is the influence degree of the electricity user with electricity stealing behavior on the load of the power storage system, P n is the normalized expected load power of the power storage system, P a is the actual load power of the power storage system when the electricity stealing behavior occurs, E d is the energy loss of the power storage system caused by the electricity stealing behavior, E t is the total energy capacity of the power storage system, and ω is the weight.

[0046] The weight ω ∈ (0, 1), the normalized expected load power P n The greater the value of ε, the greater the influence degree of the electricity user with electricity stealing behavior on the load of the power storage system, and the processing queue of the electricity user with electricity stealing behavior is generated based on the descending order of the corresponding ε value of the electricity user.

[0047] Compared with the known public technology, the technical solution provided by the present invention has the following beneficial effects:

[0048] The present invention provides an anti-electricity theft monitoring method based on an electric energy storage system. During the execution of the method, a comparative line graph representing the charge and discharge power changes of the energy storage devices is created through the charge and discharge power data of the energy storage devices in the electric energy storage system, thereby realizing independent anti-electricity theft monitoring of each energy storage device. During the anti-electricity theft monitoring process, comprehensive anti-electricity theft monitoring is carried out from the energy storage system end and the electricity user end based on the line segments representing the power changes in the comparative line graph. When the electricity theft problem occurs at the electricity user end, the electricity theft user can be accurately captured. At the same time, when the electricity theft user is not unique, a queue can be generated based on the severity of the electricity theft situation to realize priority offline processing of the electricity theft problem. BRIEF DESCRIPTION OF THE DRAWINGS

[0049] To more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are only some embodiments of the present invention. Those skilled in the art can also derive other drawings based on these drawings without inventive effort.

[0050] Figure 1 A flowchart of an anti-electricity theft monitoring method based on an electric energy storage system is provided;

[0051] Figure 2 This is an example schematic diagram of a comparison line graph in the present invention;

[0052] Figure 3 Schematic diagram of the logic of L′1 and the source of L′1 used in obtaining SIMM(L1, L′1) in the present invention. DETAILED DESCRIPTION

[0053] To make the purpose, technical solutions, and advantages of the embodiments of the present invention more clear, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making any creative efforts shall fall within the scope of protection of the present invention.

[0054] The present invention will be further described below with reference to the embodiments.

[0055] Example 1:

[0056] This embodiment is based on an anti-electricity theft monitoring method of an electric energy storage system, such as Figure 1 Shown, including:

[0057] Real-time collection of charge and discharge power data of the energy storage device of the power storage system, and creation of a comparative line graph representing the change in charge and discharge power of the energy storage device based on the charge and discharge power data of the energy storage device of the power storage system;

[0058] Monitoring the time threshold covered by the horizontal axis of the comparative line graph, and when the time threshold covered by the horizontal axis of the comparative line graph is not less than two weeks, extracting the line segment corresponding to each week representing the change in charge and discharge of the energy storage device in the comparative line graph, further segmenting the line segment representing the change in charge and discharge of the energy storage device, and analyzing the differential time domain on the line segment representing the change in charge and discharge of the energy storage device based on the segmentation result;

[0059] When the line segment representing the change in charge and discharge of the energy storage device is segmented, the number of segments is seven, and when the differential time domain on the line segment representing the change in charge and discharge of the energy storage device is analyzed based on the segmentation result, first, the similarity of each segmented sub-line segment representing the change in charge and discharge of the energy storage device is identified, and based on the similarity identification result, the differential time domain is determined;

[0060] The similarity identification logic of the sub-line segment representing the change in charge and discharge of the energy storage device is represented as:

[0061]

[0062] In the formula: SIMM(L1, L'1) is the similarity of the sub-line segment L1 and L'1 representing the change in charge and discharge of the energy storage device; Q1(max) use is the maximum value of the line segment representing discharge in the sub-line segment L1; Q1'(max) use is the maximum value of the line segment representing discharge in the sub-line segment L'1; Q1(min) use is the minimum value of the line segment representing discharge in the sub-line segment L1; Q1'(min) use is the minimum value of the line segment representing discharge in the sub-line segment L'1; γ is the first correction factor; m use is the set of sub-line segments representing discharge in L1 and L'1; Q 1j is the vertical axis value of the jth point on the line graph in the sub-line segment L1; Q1' j is the vertical axis value of the jth point on the line graph in the sub-line segment L'1; Q1(max) in is the maximum value of the line segment representing charge in the sub-line segment L1; Q1(min) in is the minimum value of the line segment representing charge in the sub-line segment L1; Q1'(max) in is the maximum value of the line segment representing charge in the sub-line segment L'1; Q1'(min) in is the minimum value of the line segment representing charge in the sub-line segment L'1; τ is the second correction factor;

[0063] Among them, L1 and L′1 are derived from the sub-segments of the same day in the line segments corresponding to the charging and discharging changes of the energy storage equipment on consecutive weeks. The larger the SIMM(L1, L′1), the higher the similarity between the two groups of sub-segments. When determining the differentiated time domain, the user of the power energy storage system defines a differentiated judgment threshold. Based on the set differentiated judgment threshold and SIMM(L1, L′1), the paired time domains of the sub-segments belonging to SIMM(L1, L′1) within the differentiated judgment threshold are determined to be differentiated time domains.

[0064] The value of the first correction factor γ follows the following rules: if the numerator of the fraction in the correction target bracket is not greater than the denominator, the first correction factor is 1; if the numerator of the fraction in the correction target bracket is greater than the denominator, the first correction factor is -1.

[0065] The value of the second correction factor τ follows: Then the second correction factor takes the value of 1. Then the second correction factor takes the value of -1;

[0066] Among them, the time threshold corresponding to L1 is always earlier than the time threshold corresponding to L′1;

[0067] During the next week not recorded in the comparison line chart, the time domain corresponding to the differentiated time domain captures the charging and discharging data of the energy storage system's energy storage equipment and the electricity consumption data of the electricity users served by the energy storage system. Based on the charging and discharging data of the energy storage equipment and the electricity consumption data of the electricity users served by the energy storage system, an analysis is conducted to determine whether there is electricity theft at the initial end of the energy storage system, the probability of electricity theft among the electricity users served by the energy storage system, and the users who are found to be the victims of electricity theft.

[0068] The analytical logic for the probability of electricity theft by electricity users served by the power storage system is expressed as follows:

[0069]

[0070] Where: SEI is the electricity theft determination index, that is, the probability; P m is the actual measured power value; P e is the expected power value; I m is the actual measured current value; I e is the expected current value; V m is the actual measured voltage value; V e is the expected voltage value; a, b, c are weights;

[0071] Among them, the electricity consumption data of the power system service users include: m 、P e , I m , I e、V m 、V e After obtaining the electricity theft determination index SEI, the user of the power storage system defines the electricity theft determination threshold. The electricity theft determination threshold is initially set to 20%, that is, if the electricity theft determination index SEI>20%, it is determined that there is electricity theft behavior at the electricity user end. e , I e 、V e The power storage system user customizes the weights a, b, and c based on the power supply standard. The weights a, b, and c are all greater than zero, and the sum of the three is 1.

[0072] The analysis logic for users who steal electricity is expressed as follows:

[0073] The SEI is used to record the results of whether each electricity user has committed electricity theft. If the accumulated records of the same electricity user show at least two instances of electricity theft, the user is considered to have committed electricity theft.

[0074] Among them, users who are judged to have committed electricity theft will have their power transmission connection with the power storage system disconnected in real time, and only users on the power storage system management end have the authority to manually open the connection;

[0075] The analysis logic for whether there is electricity theft at the initial end of the power storage system is expressed as follows:

[0076]

[0077] Where: E out Output power to the power storage system; I out is the output current of the power energy storage system; P out is the active power output of the power energy storage system; L is the total length of the power distribution line of the power energy storage system; U out is the output voltage of the power energy storage system; S out is the cross-sectional area of ​​the distribution line conductor; is the power factor; t out is the output time of the power energy storage system; E0 is the compensation; u is the total number of electricity users served by the power energy storage system; E v The power consumption of the vth electricity user;

[0078] Among them, the power consumption of the electricity user is the output time t of the power storage system out If the above formula is established, it means that there is electricity theft at the initial end of the power storage system. Otherwise, it means that there is no electricity theft at the initial end of the power storage system. The compensation E0 is defined by the power storage system end management user, and the compensation E0

[0079]

[0080] Evaluate the load on the energy storage system from electricity users who engage in electricity theft, and generate a processing queue for electricity users who engage in electricity theft based on the load on the energy storage system from the electricity users;

[0081] Among them, after the processing queue of electricity users with electricity theft is generated, the power storage system manages the user offline and performs electricity theft line detection on the power circuits of the electricity users with electricity theft in turn.

[0082] In this embodiment, through the operation of the system in the above embodiment, full coverage of electricity theft monitoring is provided for the power energy storage system, ensuring that possible electricity theft behaviors at the initial end and the electricity user end of the power energy storage system can be accurately captured based on this method, thereby avoiding the adverse effects of electricity theft on the power energy storage system.

[0083] See also Figure 2 As shown, the figure further shows the specific form of the comparative line chart representing the charge and discharge capacity changes of the energy storage device;

[0084] See also Figure 3 As shown, the figure further shows the similarity recognition target and target source logic in the similarity recognition logic of the sub-segment representing the charging and discharging changes of the energy storage device.

[0085] Example 2:

[0086] In terms of specific implementation, based on Example 1, this example refers to Figure 1 The anti-electricity theft monitoring method based on the electric energy storage system in Example 1 is further described in detail:

[0087] The charge and discharge data of the energy storage device in the power energy storage system is collected at the charge and discharge ends of the energy storage device based on the specified collection frequency. In the comparison line chart, the horizontal axis represents the corresponding timestamp of the collection frequency, and the vertical axis represents the charge and discharge data. The broken line representing the charge data and the broken line representing the discharge data are distinguished by different colors.

[0088] The frequency of collecting charge and discharge data of energy storage devices in the power storage system follows the following rules: the more electricity users the power storage system serves, the more and longer the historical daily discharge volume and daily discharge time of the power storage system, the faster the collection frequency.

[0089] The frequency of collecting charging and discharging data of energy storage devices in the power energy storage system is specifically subject to:

[0090]

[0091] Where: p is the frequency of collecting charge and discharge data of the energy storage device in the power energy storage system; p0 is the base number of the collection frequency; m is the number of electricity users served by the energy storage device in the power energy storage system; n is the number of historical operation days of the energy storage device in the power energy storage system; Q i is the discharge amount of the energy storage device on day i; t use is the discharge duration of the energy storage device on day i; t0 is the daily service duration of the energy storage device; P is the final application acquisition frequency; f(p) is the constraint function;

[0092] in, Express The average, Express The average, represents the ratio of the discharge time of the energy storage device to the service time on day i, (t0-t use ) i It represents the idle time of the energy storage device on day i. The daily service time t0 of the energy storage device and the acquisition frequency base p0 are customized by the user of the power energy storage system management end. The daily service time t0 of the energy storage device is set to 24 by default. The acquisition frequency p of the charge and discharge power data of the energy storage device in the power energy storage system is rounded up. The constraint function f(p) is based on the p value. If 3≤p≤24, then P=f(p)=p. Otherwise, the difference between the p value in f(p) and 3 is the smallest, P=3, and the difference between the p value in f(p) and 24 is the smallest, P=24. The unit of the final application acquisition frequency P is: times / day.

[0093] In this embodiment, the collection frequency of the charging and discharging power data of the energy storage device in the electric energy storage system is designed by the above-mentioned logic, and the collection frequency of the charging and discharging power data of the energy storage device in the electric energy storage system is set, thereby achieving stable collection of the charging and discharging power data, and providing necessary execution data and logic support for the further execution of the method in Example 1.

[0094] Example 3:

[0095] In terms of specific implementation, based on Example 1, this example refers to Figure 1 The anti-electricity theft monitoring method based on the electric energy storage system in Example 1 is further described in detail:

[0096] When a power user who is determined to have committed electricity theft disconnects from the power transmission connection with the power storage system, the power storage system management user will simultaneously feedback the determination information of the electricity theft to the disconnected power user;

[0097] When the power storage system management user simultaneously feeds back information on the existence of electricity theft to the disconnected electricity user, the system sends the information to the mobile computer device held by the electricity user via the communication network. The information includes the results of each electricity theft determination and the timestamp of the determination.

[0098] The evaluation logic of the load of the power storage system by the electricity user who steals electricity is expressed as follows:

[0099]

[0100] Where: ε is the impact of electricity users with electricity theft behavior on the load of the power energy storage system; P n is the normalized expected load power of the electric energy storage system; P a is the actual load power of the power storage system when the electricity theft occurs; E d Energy loss of the power storage system caused by electricity theft; E t is the total energy capacity of the power energy storage system; ω is the weight;

[0101] Among them, the weight ω∈(0,1), the normalized expected load power P of the power storage system n The ε value is defined by the user managing the power storage system. The larger the ε value, the greater the impact of the electricity theft user on the power storage system load. A processing queue for electricity theft users is generated and sorted in descending order based on their corresponding ε values.

[0102] In this embodiment, through the above further settings and the formula for calculating the degree of impact ε of electricity users who engage in electricity theft on the load of the power energy storage system, logical support is provided for the generation of a processing queue for electricity users who engage in electricity theft, thereby ensuring the stable operation of the system in Example 1.

[0103] In summary, during the execution of the method in the above embodiment, a comparative line graph representing the charge and discharge power changes of the energy storage devices is created through the charge and discharge power data of the energy storage system energy storage devices, thereby realizing independent anti-electricity theft monitoring of each energy storage device. During the anti-electricity theft monitoring process, based on the line segments representing power changes in the comparative line graph, comprehensive anti-electricity theft monitoring is carried out from the energy storage system end and the electricity user end. When the electricity theft problem occurs at the electricity user end, the electricity theft user can be accurately captured. At the same time, when the electricity theft user is not unique, a queue can be generated based on the severity of the electricity theft situation to realize priority offline processing of the electricity theft problem.

[0104] The above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit the same. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein. However, these modifications or replacements will not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the various embodiments of the present invention.

Claims

1. A method for monitoring anti-electricity theft based on an electric energy storage system, characterized in that: include: Real-time collection of charge and discharge data of energy storage devices in the power energy storage system, and creation of a comparative line chart showing changes in charge and discharge data of the energy storage devices based on the charge and discharge data of the energy storage devices in the power energy storage system; Monitoring the time threshold covered by the horizontal axis of the comparison line graph. When the time threshold covered by the horizontal axis of the comparison line graph is not less than two weeks, extracting the line segments representing the charge and discharge changes of the energy storage device corresponding to each consecutive week in the comparison line graph, further segmenting the line segments representing the charge and discharge changes of the energy storage device, and then analyzing the differentiated time domains on the line segments representing the charge and discharge changes of the energy storage device based on the segmentation results; During the next week not recorded in the comparison line chart, the time domain corresponding to the differentiated time domain captures the charging and discharging data of the energy storage system's energy storage equipment and the electricity consumption data of the electricity users served by the energy storage system. Based on the charging and discharging data of the energy storage equipment and the electricity consumption data of the electricity users served by the energy storage system, an analysis is conducted to determine whether there is electricity theft at the initial end of the energy storage system, the probability of electricity theft among the electricity users served by the energy storage system, and the users who are found to be the victims of electricity theft. The analysis logic of whether there is electricity theft at the initial end of the power energy storage system is expressed as follows: Where: E out Output power to the power storage system; I out is the output current of the power energy storage system; P out is the active power output of the power energy storage system; L is the total length of the power distribution line of the power energy storage system; U out is the output voltage of the power energy storage system; S out is the cross-sectional area of ​​the distribution line conductor; is the power factor; t out is the output time of the power energy storage system; E0 is the compensation; u is the total number of electricity users served by the power energy storage system; E v The power consumption of the vth electricity user; Among them, the power consumption of the electricity user is the output time t of the power storage system out If the above formula is established, it means that there is electricity theft at the initial end of the power storage system. Otherwise, it means that there is no electricity theft at the initial end of the power storage system. The compensation E0 is defined by the power storage system end management user, and the compensation E0 Evaluate the load on the energy storage system from electricity users who engage in electricity theft, and generate a processing queue for electricity users who engage in electricity theft based on the load on the energy storage system from the electricity users; Among them, after the processing queue of electricity users with electricity theft is generated, the power storage system manages the user offline and performs electricity theft line detection on the power circuits of the electricity users with electricity theft in turn.

2. The anti-electricity theft monitoring method based on the electric energy storage system according to claim 1 is characterized in that: The charge and discharge data of the energy storage device of the power energy storage system is collected at the charge and discharge ends of the energy storage device based on a specified collection frequency. In the comparative line graph, the horizontal axis represents the corresponding timestamp of the collection frequency, the vertical axis represents the charge and discharge data, and the broken line representing the charge data and the broken line representing the discharge data are distinguished by different colors; The frequency of collecting charging and discharging power data of the energy storage equipment in the power energy storage system follows the following rules: the more electricity users the power energy storage system serves, the more and longer the historical daily discharge volume and daily discharge time of the power energy storage system, the faster the collection frequency.

3. The anti-electricity theft monitoring method based on the electric energy storage system according to claim 2 is characterized in that: The frequency of collecting the charging and discharging data of the energy storage device in the power energy storage system specifically complies with: Where: p is the frequency of collecting charge and discharge data of the energy storage device in the power energy storage system; p0 is the base number of the collection frequency; m is the number of electricity users served by the energy storage device in the power energy storage system; n is the number of historical operation days of the energy storage device in the power energy storage system; Q i is the discharge amount of the energy storage device on day i; t use is the discharge duration of the energy storage device on day i; t0 is the daily service time of the energy storage device; P is the final application acquisition frequency; f(p) is the constraint function; in, Express The average, Express The average, represents the ratio of the discharge time of the energy storage device to the service time on day i, (t0-t use ) i It represents the idle time of the energy storage device on day i. The daily service time t0 of the energy storage device and the acquisition frequency base p0 are customized by the user of the power energy storage system management end. The daily service time t0 of the energy storage device is set to 24 by default. The acquisition frequency p of the charge and discharge power data of the energy storage device in the power energy storage system is rounded up. The constraint function f(p) is based on the p value. If 3≤p≤24, then P=f(p)=p. Otherwise, the difference between the p value in f(p) and 3 is the smallest, P=3, and the difference between the p value in f(p) and 24 is the smallest, P=24. The unit of the final application acquisition frequency P is: times / day.

4. The anti-electricity theft monitoring method based on the electric energy storage system according to claim 1 is characterized in that: When segmenting the line segments representing the charging and discharging changes of the energy storage device, the number of segments is seven. When further analyzing the differentiated time domains on the line segments representing the charging and discharging changes of the energy storage device based on the segmentation results, similarity recognition is first performed on each segmented sub-segment representing the charging and discharging changes of the energy storage device. Based on the similarity recognition results, the differentiated time domain is determined.

5. The anti-electricity theft monitoring method based on the electric energy storage system according to claim 4 is characterized in that: The similarity recognition logic of the sub-segments representing the charge and discharge changes of the energy storage device is expressed as: Where: SIMM(L1,L′1) is the similarity between the sub-segments L1 and L′1 representing the charge and discharge changes of the energy storage device; Q1(max) use is the maximum value of the line segment representing discharge in sub-segment L1; Q1′(max) use is the maximum value of the line segment representing discharge in sub-segment L′1; Q1(min) use is the minimum value of the line segment representing discharge in sub-segment L1; Q1′(min) use is the minimum value of the line segment representing discharge in the sub-line segment L′1; γ is the first correction factor; m use is the set of sub-segments representing discharge in L1 and L′1; Q 1j Q1′ is the vertical axis value on the line graph corresponding to the jth point in the sub-segment L1; j is the vertical axis value on the line graph corresponding to the j-th point in the sub-segment L′1; Q1(max) in The maximum value of the charging segment in sub-segment L1; Q1 (min) in The minimum value of the charging segment in the sub-segment L1; Q1′(max) in The maximum value of the segment marked with charging in sub-segment L′1; Q1′ (min) in is the minimum value of the segment marked with charging in the sub-segment L′1; τ is the second correction factor; Among them, L1 and L′1 are derived from the sub-segments of the same day in the line segments corresponding to the continuous weekly segments representing the charging and discharging changes of the energy storage equipment. The larger the SIMM(L1, L′1), the higher the similarity between the two groups of sub-segments. When determining the differentiated time domain, the user of the power energy storage system defines the differentiated judgment threshold. Based on the set differentiated judgment threshold and SIMM(L1, L′1), the paired time domains of the sub-segments belonging to SIMM(L1, L′1) within the differentiated judgment threshold are determined to be differentiated time domains.

6. The anti-electricity theft monitoring method based on the electric energy storage system according to claim 5 is characterized in that: The value of the first correction factor γ is determined as follows: if the numerator of the fraction in the correction target bracket is not greater than the denominator, the first correction factor is 1; if the numerator of the fraction in the correction target bracket is greater than the denominator, the first correction factor is -1; The value of the second correction factor τ follows: Then the second correction factor takes the value of 1. Then the second correction factor takes the value of -1; Among them, the time threshold corresponding to L1 is always earlier than the time threshold corresponding to L′1.

7. The anti-electricity theft monitoring method based on the electric energy storage system according to claim 1 is characterized in that: The analytical logic for the probability that the power storage system serves electricity users who engage in electricity theft is expressed as follows: Where: SEI is the electricity theft determination index, that is, the probability; P m is the actual measured power value; P e is the expected power value; I m is the actual measured current value; I e is the expected current value; V m is the actual measured voltage value; V e is the expected voltage value; a, b, and c are weights; The electricity consumption data of the power storage system serving the electricity users include: m 、P e , I m , I e 、V m 、V e After obtaining the electricity theft determination index SEI, the user of the power storage system defines the electricity theft determination threshold. The electricity theft determination threshold is initially set to 20%, that is, if the electricity theft determination index SEI>20%, it is determined that the electricity user has committed electricity theft. e , I e 、V e The power storage system user customizes it according to the power supply standard. The weights a, b, and c are all greater than zero, and the sum of the three is 1.

8. The anti-electricity theft monitoring method based on the electric energy storage system according to claim 7 is characterized in that: The analysis logic of the user who steals electricity is expressed as follows: The SEI is used to record the results of whether each electricity user has committed electricity theft. If the accumulated records of the same electricity user show at least two instances of electricity theft, the user is considered to have committed electricity theft. Among them, users who are judged to have committed electricity theft will have their power transmission connection with the power storage system disconnected in real time, and only users on the power storage system management end have the authority to manually open it.

9. The anti-electricity theft monitoring method based on the electric energy storage system according to claim 1 is characterized in that: When the electricity user determined to have committed electricity theft disconnects from the power transmission connection with the power energy storage system, the power energy storage system management user synchronously feeds back information on the determination of electricity theft to the disconnected electricity user; Among them, when the power energy storage system management user synchronously feeds back the judgment information of the existence of electricity theft to the disconnected electricity user, the judgment information is sent to the mobile computer device held by the electricity user based on the communication network. The judgment information includes: the judgment result of whether there is electricity theft each time and the judgment timestamp.

10. The anti-electricity theft monitoring method based on the electric energy storage system according to claim 1, characterized in that: The evaluation logic of the load of the power storage system by the electricity user who has committed electricity theft is expressed as follows: Where: ε is the impact of electricity users with electricity theft behavior on the load of the power energy storage system; P n is the normalized expected load power of the electric energy storage system; P a is the actual load power of the power storage system when the electricity theft occurs; E d Energy loss of the power storage system caused by electricity theft; E t is the total energy capacity of the electric energy storage system; ω is the weight; Among them, the weight ω∈(0,1), the normalized expected load power P of the power storage system n The ε value is defined by the user managing the power storage system. The larger the ε value, the greater the impact of the electricity theft user on the power storage system load. A processing queue for electricity theft users is generated and sorted in descending order based on their corresponding ε values.

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