CN109490679B - Intelligent electricity stealing inspection system and method based on non-invasive load monitoring - Google Patents
Intelligent electricity stealing inspection system and method based on non-invasive load monitoring Download PDFInfo
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Abstract
The invention discloses an intelligent electricity stealing inspection method based on non-invasive load monitoring, which mainly comprises the steps of (1) judging whether an electricity consumer is a suspected electricity stealing user; (2) the electric equipment of the user is divided into electric equipment with the running state capable of reflecting the all-day electricity utilization behavior of the user and suitable for analyzing the intermittent meter-throwing electricity-stealing behavior and electric equipment with the running state monitoring result not influenced by the less-metering electricity-stealing behavior; then, calculating a power stealing behavior judgment index; (3) judging the electricity stealing behavior of the user; (4) and estimating the electricity stealing amount of the user by utilizing the relation between the accumulated electricity consumption of the same type of electrical equipment and the total electricity consumption of the user under normal conditions and the electricity stealing behavior judgment result of the user. The invention utilizes the non-invasive load monitoring technology to obtain the electricity consumption detail data, not only overcomes the defects of difficult household entry and difficult evidence collection of the traditional method, but also improves the accuracy and reliability of the check of the two electricity stealing behaviors.
Description
Technical Field
The invention belongs to the field of electric power user electricity stealing inspection, and particularly relates to an intelligent electricity stealing inspection system and method based on non-invasive load monitoring.
Background
China's power system develops rapidly, and the generated energy, installed capacity of electric power and related infrastructure almost increase exponentially. However, since the development speed is not matched with the related supervision and control, and the electricity utilization management technology is not complete, a practical and effective countermeasure for abnormal electricity utilization supervision is not always found. The energy and economic losses caused by electricity stealing are huge every year, and the rising trend is obvious, so that a reasonable method is found to recuperate the electricity stealing behavior of the power consumers.
Several typical cases highlight the severity of electricity theft in our country. 2003 + 2004, 68 yuan was stolen from a certain power supply bureau in Guangzhou, and 798232.80 yuan was recovered. In 12 days 4 months in 2003, the office checks a certain property management company in Guangzhou city, and in five months, 12 cables are connected in front of a metering meter of a low-voltage power transformation house in a private mode, so that 42 thousands of kilowatt hours of electric energy is stolen and hands are turned to supply the electric energy to a certain supermarket in a community to earn electric charge, and the total amount of electricity stealing reaches 45 thousands of RMB.
The high-tech electricity stealing means are hidden day by day, which leads to the remarkable increase of the law enforcement difficulty in the process of judging the electricity stealing behavior of the user or estimating and discussing the electricity stealing charge during the inspection of electricity stealing. In addition, although the electric quantity measurement is found to be wrong, the electric quantity cannot be identified as the electricity stealing behavior because the reasonable electricity using behavior analysis cannot be carried out, and the electric energy is lost.
[1] The method is characterized by comprising the following steps of (1) zerano, non-invasive resident load monitoring key technology research [ D ] facing intelligent electricity utilization, North China electric power university (Beijing), 2017.
[2] Mytilus edulis, Liubo, Koelreuteric; non-invasive resident power load monitoring and decomposition technology [ J ], southern power grid technology, 2013,7(04): 1-5.
[3] The fourth Anhui province Motor engineering society of Anhui province of Qingke Tang, the Anhui province of China, the Anhui province of China, the 2006: 5.
[4] Chenshijun, wangtianjiang; the intelligent recognition and early warning of electricity stealing [ J ], Zhejiang electric power, 2017,36(12):33-36 based on curve similarity and correlation analysis.
[5] Shanghang, Lupengcong, Li Meng, Chengyang; an abnormal electricity utilization monitoring method [ J ] based on a local power reference, an electric measuring and instrument 2014,51(08) and 1-5.
[6] Yaowanzhi, linguisu, serena, zhengqingna, and poplars; research on a low-voltage user electricity stealing online monitoring analysis method based on electricity utilization behavior analysis [ J ]. China New communication, 2015,17(02): 97-99.
[7] Chenyang, a new method [ D ] for monitoring abnormal electricity consumption based on a local power reference, north china university of electric power 2014.
[8] Zhangqi, research and discussion on novel intelligent electricity-stealing prevention technology [ J ], oil and gas field ground engineering, 2017,36(9): 75-79.
Disclosure of Invention
In order to effectively solve the above problems, it is necessary to analyze power consumption data of an electrical appliance, including an operating state, power consumption, accumulated power, and the like of the electrical appliance. For acquiring the electricity detail data, invasive power load monitoring and non-invasive load monitoring schemes exist[1-2]. However, the former needs to install a sensor (such as a smart socket) with a communication function for each main electrical appliance inside the load, which is not suitable for checking the electricity stealing of users, and the latter can obtain the electricity consumption data of the main electrical appliances inside the load only by analyzing the total electricity consumption data of the load. Therefore, the invention designs an intelligent electricity stealing inspection system based on non-invasive load monitoring.
In order to solve the technical problems, the invention provides an intelligent electricity stealing inspection system based on non-invasive load monitoring, which comprises a data acquisition module, an electricity stealing suspicion user evaluation module, an electricity stealing behavior index calculation module, a user electricity stealing behavior judgment module, an electricity stealing reference value estimation module and an information transmission module, wherein the electricity stealing behavior index calculation module is used for calculating electricity stealing behavior indexes of users;
the data acquisition module acquires user daily electricity consumption data and load electricity consumption detail data from an electric power company database, wherein the load electricity consumption detail data are acquired by a non-invasive load monitoring technology and related monitoring equipment;
the electricity stealing suspicion user evaluation module is used for summarizing and expressing a description index system for reflecting and representing electricity stealing and electricity consuming behaviors according to the daily electricity consumption data of the user in the data acquisition module, determining an index threshold value serving as preliminary screening of electricity stealing detection, and screening and positioning the user suspected of having the electricity stealing and electricity consuming behaviors according to the threshold value;
the electricity stealing behavior index calculation module establishes and calculates an electricity stealing behavior evaluation index based on the power load electricity consumption detail data in the data acquisition module, and the evaluation index can be directly used for the subsequent electricity stealing behavior analysis;
the user electricity stealing behavior judging module judges whether the electricity stealing behavior exists in the user according to the electricity stealing behavior judging index, including judging the type of the electricity stealing behavior; if the user is judged not to have electricity stealing behavior, the suspicion of the user is eliminated, otherwise, the type of the electricity stealing behavior of the user is marked, and a judgment result is provided for an electricity stealing inspection department through an information transmission module;
the electricity stealing reference value estimation module estimates the electricity stealing reference value of the user according to the electricity stealing type of the user and provides an electricity stealing estimation result to an electricity stealing inspection department through the information transmission module;
the information transmission module is used for carrying out necessary data information transmission between the intelligent electricity stealing inspection system based on non-invasive load monitoring and related departments or users; the specific functions of the system depend on actual requirements and at least comprise the display and output of monitoring and analysis results.
The method for checking by using the intelligent electricity stealing checking system based on the non-invasive load monitoring comprises the following steps:
step one, judging whether the power consumer is a suspected electricity stealing user:
the electricity consumer types comprise industrial users, commercial users and residential users; the method comprises the steps of judging by utilizing daily electricity consumption data of users acquired by an electric power company, determining an index system for describing abnormal electricity consumption behaviors according to electricity consumption data records of all users in an inspection area and electricity consumption data records of users who historically have electricity stealing behaviors in the inspection area, wherein the index system comprises the following 4 indexes:
1) monthly electric quantity ratio D of user1The ratio of the monthly electricity consumption of the user to the monthly electricity consumption of the industry to which the user belongs;
2) average value D of the ratio of the monthly electricity consumption of each month of the user to the monthly electricity consumption of the industry to which the corresponding month user belongs2；
3) Electricity consumption ratio D of users in holidays3The ratio of the daily average electric quantity of the user during the holiday period to the daily average electric quantity of the industry to which the user belongs during the holiday period;
4) electric proportion D for summer, autumn, winter and spring4The method is characterized by comprising the following steps of (1) referring to the ratio of seasonal power consumption of a user to seasonal power consumption of an industry to which the user belongs;
respectively calculating user indexes and set threshold values D according to the system10，D20，D30，D40Comparing, and judging that the user has abnormal power utilization when the actual calculation result of a certain index is greater than the threshold; wherein D10＝0.45、D20＝0.60、D30The holiday time of the holiday is 3-7 days according to the festivals, the value range is 0.5-0.6, and D40＝0.65；
Calculating the electricity stealing suspicion index H according to the formula (1):
in the formula (1), the weight score α of each indexm∈[0.5,2]Its initial value is set to 1.
The obtained electricity stealing suspicion index H and a threshold value H0Comparing, typically with a threshold H of the suspicion index of electricity theft0Setting the index as 2.5, if the electricity stealing suspicion index H of a certain user in the inspection area is smaller than a set threshold, judging the user as an electricity stealing suspicion user, and transferring to the second step; otherwise, the inspection area is not provided with electricity stealing suspected users, and the electricity stealing inspection aiming at the area is finished;
step two, calculating the electricity stealing behavior evaluation index:
firstly, dividing electrical equipment of a user into A-type electrical equipment and B-type electrical equipment, wherein the A-type electrical equipment is electrical equipment of which the running state can reflect that the all-day electricity consumption behavior of the user is suitable for analyzing the intermittent meter-throwing electricity stealing behavior, and the B-type electrical equipment is electrical equipment of which the running state monitoring result is not influenced by the less-metering electricity stealing behavior;
then, calculating the electricity stealing behavior judgment index, including:
2-1) establishing an evaluation vector L of the working state of the electrical equipmentjAs shown in formula (2):
Lj＝[l1,l2,l3,...li,...ln]T (2)
in the formula (2), LjA vector l representing the working state of certain electrical equipment at any monitoring time i on the j th dayiE {0, 1}, wherein 0 represents that the electrical equipment is in a shutdown state at the monitoring time i, and 1 represents that the electrical equipment is in an operating state at the monitoring time i;
indicating the cumulative number of switches of the appliance on day j,
representing the daily average number of switching of the electrical apparatus during a monitoring period comprising λ days;
2-2) establishing an electric power evaluation vector for the electric equipment, wherein the electric power evaluation vector is expressed as a formula (3):
Pj＝[p1,p2,p3,...pi,...pn]T (3)
in the formula (3), piIs represented byiThe unit of the running active power value of the corresponding electrical equipment is W;
2-3) establishing an evaluation vector of the duration of the electricity stealing behavior, as shown in formula (4):
Tj＝[t1,t2,t3,...ti,...tn]T (4)
in the formula (4), tiIs represented byiThe corresponding running time length is in the unit of s;
step three, judging the electricity stealing behavior of the user, comprising the following steps:
step 3-1) calculating the variance S of the daily switching times of the user electrical equipment in a monitoring period containing lambda daysn；
Step 3-2) judging whether intermittent meter-throwing electricity-stealing behaviors exist or not, and if so, judging whether intermittent meter-throwing electricity-stealing behaviors exist or notn＞S0Judging that the user has intermittent meter-throwing electricity-stealing rows, and turning to the step 3-5), otherwise, turning to the step 3-3), wherein S0Counting the variance of the daily switching times in normal users for the same type of electrical equipment;
step 3-3) judging the electricity stealing behavior with less metering, for PjOf (5) an arbitrary element piIf p is not satisfiedi∈(pmin,pmax) And p isi＜pminIf yes, judging that the number of the electricity stealing users is less, and turning to the step 3-5), otherwise, turning to the step 3-4); wherein p isminAnd pmaxRespectively representing real-time minimum power and maximum power values of the same type of electrical equipment during normal operation; the period of time for implementing electricity stealing behavior is p with abnormalityiRecording the monitoring time i in a corresponding monitoring time period;
step 3-4) the user does not have electricity stealing behavior, and the user inspection is finished;
step 3-5) judging that the user is a suspected electricity stealing user, and recording the electricity stealing behavior of the user and evaluation indexes of the electricity stealing behavior;
step four, estimating the electricity stealing amount:
estimating the electricity stealing amount of the user by utilizing the relation between the accumulated electricity consumption of the same type of electrical equipment and the total electricity consumption of the user under normal conditions and the judgment result and the index of the electricity stealing behavior of the user recorded in the step three, wherein the estimation comprises the following steps:
4-1) on the day when electricity stealing behavior is suspected, the normal value W of the total daily electricity consumption of the load is estimated according to the following formula:
in the formula (5), wkThe total electricity consumption of the kth user in sigma normal electricity consumers of the same type in the same day is represented by kWh;
4-2) total amount of normal daily electricity consumption W of electrical equipmentrAccording to the types of electricity stealing behaviors, the estimation is carried out according to the following formula:
when the electricity stealing behavior of a certain user is that the meter is intermittently thrown to steal electricity,
Wr1＝lmax×pavg×tavg (6)
when the electricity stealing behavior of a certain user is the low-metering electricity stealing,
in formulae (6) and (7), tavgIs an average value of the operating duration of the electrical appliance,
pavgis the average value of the active power of the electrical equipment for all the operation periods,
where j has a value of ljAnd lmaxCorresponding date numbers when equal;
4-3) obtaining the proportionality coefficient K of the estimated electricity stealing quantity1，K2：
When the electricity stealing behavior of a certain user is intermittent meter throwing and electricity stealing, K1＝Wr1W; when the electricity stealing behavior of a certain user is that of few metering electricity stealing, K2＝Wr2/W
4-4) estimating the electricity stealing amount:
when the electricity stealing behavior of a certain user is that the meter is intermittently thrown to steal electricity, the estimated value W of the electricity stealing amountsAccording to equation (8):
Ws＝(lmax-lj)×pavg×tavg/K1 (8)
in the formula (8), lmaxFor the user's working state evaluation vector L indicating the number of times the electrical appliance is switched on and off the day mostmaxThe total number of non-zero elements in (1); ljSwitching times of the electric appliance for the day with the swinging meter running;
when the electricity stealing behavior of a certain user is that of electricity stealing with less metering, the estimated value W of the electricity stealing amountsThe reference value is obtained by equation (9):
thus, the electricity stealing inspection analysis aiming at the user is completed;
step five, repeating the step one to the step four until the electricity stealing inspection analysis of all target users in the specified area is completed;
step six, aiming at the electricity stealing cases generated by the electricity stealing inspection analysis, according to the matching degree of the abnormal user judgment result based on each single index and the inspection analysis result, adjusting the weight value of each single index in the next inspection, and taking the adjusted weight value as the weight value of the next electricity stealing inspection analysis;
wherein, the regulation rule of the weight scores of the single indexes is as follows: if the coincidence degree of the abnormal user judgment result based on a certain single index and the current inspection analysis result is higher, the corresponding weight score is increased, and if the coincidence degree of the abnormal user judgment result based on a certain single index and the current inspection analysis result is lower, the corresponding weight score is decreased.
Compared with the prior art, the invention has the beneficial effects that:
the invention provides an intelligent electricity stealing inspection system and method based on non-invasive load monitoring. It uses the power consumption data of two electric equipments of "A-type indicating electric equipment" and "B-type indicating electric equipment" which are obtained by non-invasive load monitoring technique and have obvious correlation with power consumption behavior to establish user power-stealing determination index, and uses the power consumption data of said two electric equipmentsTo judge whether there are two kinds of electricity stealing behaviors of A kind of electricity stealing 'intermittently meter throwing' and B kind of electricity stealing 'little metering' with great inspection difficulty for various low-voltage users[8]And gives a stealing power reference value. The invention utilizes the non-invasive load monitoring technology to obtain the electricity consumption detail data, not only overcomes the defects of difficult household entry and difficult evidence collection of the traditional method, but also improves the accuracy and reliability of the check of the two electricity stealing behaviors. In addition, compared with a manual screening method or a power stealing inspection method based on invasive monitoring data, the method is more economical and practical.
Drawings
FIG. 1 is a schematic diagram of an intelligent electricity stealing inspection system of the present invention;
FIG. 2 is a flow chart of the main steps;
FIG. 3 is a normal user daily total load power curve;
FIG. 4 vector LjAnd TjElement corresponding relation is shown;
FIG. 5 is a flow chart of a user electricity stealing behavior determination;
FIG. 6 is a daily load power curve of an electricity stealing user of the intermittent throwing meter;
FIG. 7 is a graph showing the daily load power curve of a power stealing user by an undervoltage method.
Detailed Description
The technical solutions of the present invention are further described in detail with reference to the accompanying drawings and specific embodiments, which are only illustrative of the present invention and are not intended to limit the present invention.
The intelligent electricity stealing inspection system based on non-intrusive load monitoring is shown in figure 1, and can be divided into four main steps according to the working method flow of the system shown in figure 2.
Step one, judging whether the power consumer is a suspected electricity stealing user:
considering that electricity stealing behaviors exist in a few users, in order to ensure electricity stealing inspection efficiency and reduce the influence on the normal work and life of the users, all user groups need to be screened first so as to narrow the range of the users needing to be investigated in detail. A plurality of methods for finding out users suspected of having electricity stealing behaviors based on statistical analysis of user electricity consumption data are provided, but in order to ensure the accuracy of screening, higher requirements are often provided for the refinement degree of the electricity consumption data, the difficulty of data acquisition is greatly increased, and the methods are difficult to popularize. Therefore, the method for screening the electricity stealing suspected users by using the daily electricity consumption data of the users which are easily acquired by the power company and then carrying out detailed investigation on the suspected users based on the non-invasive power load decomposition technology ensures the economy and the popularization of the system.
The electricity consumer types comprise industrial users, commercial users and residential users; the daily electricity consumption data of the users acquired by the power company is used for judging, an index system of abnormal electricity consumption behaviors is determined according to the electricity consumption data records of all users in the inspection area and the electricity consumption data records of the users with electricity stealing behaviors in the inspection area historically, and a description index system of the abnormal electricity consumption behaviors of the users can be reflected and represented (shown in a table 1).
TABLE 1 user Electricity consumption behavior description index
According to the user electricity utilization behavior description indexes, a user electricity stealing judgment index system is established, and the system comprises the following 4 indexes:
1) user monthly electric quantity ratio D1The ratio of the monthly power consumption of the user to the monthly power consumption of the industry is referred to;
2) average value D of ratio of monthly electricity consumption of each month of user to monthly electricity consumption of corresponding month industry2；
3) User festival, holiday power utilization ratio D3The ratio of the daily average electric quantity during the holiday period of the user to the daily average electric quantity during the holiday period of the industry is represented;
4) electric proportion D for summer, autumn, winter and spring4The ratio of the seasonal power consumption of the user to the seasonal power consumption of the industry is referred to;
respectively calculating user indexes and set threshold values D according to the system10，D20，D30，D40Comparing, and when the actual calculation result of a certain index is greater than the threshold value, judging that the user has abnormal power utilization; wherein D10＝0.45、D20＝0.60、D30The holiday time of the holiday is 3-7 days according to the festivals, the value range is 0.5-0.6, and D40＝0.65；
Comprehensively considering the indexes, calculating the electricity stealing suspicion index H according to the formula (1):
in the formula (1), the weight score α of each indexm∈[0.5,2]Its initial value is set to 1.
The obtained electricity stealing suspicion index H and a threshold value H0Comparing, typically with a threshold H of the suspicion index of electricity theft0Setting the index as 2.5, if the electricity stealing suspicion index H of a certain user in the inspection area is smaller than a set threshold, judging the user as an electricity stealing suspicion user, and transferring to the second step; otherwise, the suspected electricity stealing users are not in the inspection area, and the electricity stealing inspection aiming at the area is finished.
Since the power utilization tracks of the low-voltage users are various and a small number of normal users are likely to be contained in the abnormal threshold range, the suspected users of power stealing in the step one are only users suspected to have power stealing and utilization behaviors. Table 2 shows the result of calculating the suspicion index of electricity stealing by a group of users in the inspection area according to the above method, and the weight scores are all set to 1. The obtained suspicion index H of electricity stealing of each user and a threshold value H0In comparison, user 4 and user 5 may be specifically listed as suspect users.
TABLE 2 index of electricity stealing behavior of user and suspicion index list of electricity stealing
In practical application, for a concerned high-loss distribution area, the suspected electricity stealing suspicion index of the monitored low-voltage user can be automatically calculated every month, and then the suspected users with electricity stealing behaviors and the geographical positions of the suspected users with the electricity stealing behaviors are screened and confirmed through the suspected electricity stealing suspicion index, whether the suspected users with the electricity stealing behaviors actually have the electricity stealing behaviors or not and the specific numerical values of the electricity stealing amounts of the suspected users with the electricity stealing behaviors need to be further analyzed.
Step two, calculating the electricity stealing behavior evaluation index:
firstly, electrical equipment of a user is divided into type A electrical equipment and type B electrical equipment, wherein the type A electrical equipment is electrical equipment (such as an electromagnetic oven, a refrigerator, a washing machine and the like) which has an operation state capable of reflecting the all-day electricity consumption behavior of the user and is suitable for electrical equipment (such as a refrigerator, a dehumidifier and the like) which is constantly opened for 24 hours and is analyzed by intermittent meter-throwing electricity-stealing behavior, and the type B electrical equipment is electrical equipment (such as an electromagnetic oven, a refrigerator, a washing machine and the like) of which the non-intrusive load monitoring result of the operation state is not influenced by the. Fig. 3 is a data display of a non-invasive load monitoring technique when a normal user is monitored in real time, by which various operation data of the class a and B electrical devices can be monitored and analyzed;
and then calculating the electricity stealing behavior judgment index, including:
(1) establishing an evaluation vector L of the working state of the electrical equipmentjAs shown in formula (2):
Lj＝[l1,l2,l3,...li,...ln]T (2)
in the formula (2), LjA vector l representing the working state of certain electrical equipment at any monitoring time i on the j th dayiE {0, 1}, wherein 0 represents that the electrical equipment is in a shutdown state at the monitoring time i, and 1 represents that the electrical equipment is in an operating state at the monitoring time i;
indicating the cumulative number of switches of the appliance on day j,
representing the daily average number of switching of the electrical apparatus during a monitoring period comprising λ days;
(2) whether the user has the few-metering electricity stealing behavior cannot be judged only by the working state vector of the electrical equipment, and the power utilization evaluation vector P of the electrical equipment needs to be establishedjAs shown in formula (3):
Pj＝[p1,p2,p3,...pi,...pn]T (3)
in the formula (3), piIs represented byiThe unit of the running active power value of the corresponding electrical equipment is W;
(3) in order to ensure reasonable estimation of electricity stealing quantity, an evaluation vector T for duration of electricity stealing behavior needs to be establishedjAs shown in formula (4):
Tj＝[t1,t2,t3,...ti,...tn]T (4)
in the formula (4), tiIs represented byiThe corresponding running time length is in units of s, and a certain electrical equipment vector L is visually shown in FIG. 4jAnd vector TjThe corresponding relation among all elements;
step three, judging the electricity stealing behavior of the user:
the decision flow of the electricity stealing behavior of the user is shown in fig. 5 and is divided into the following five sub-steps.
(1) Calculating the variance S of the number of times of day switching of the user electrical equipment in a monitoring period comprising lambda daysn；
(2) Judging whether intermittent meter-throwing electricity-stealing behaviors exist or not, wherein under the condition of normal use, the running times of the same type of electrical equipment are approximately the same every day, and the behavior is expressed as l in electricity-stealing behavior judgment index datajThe value tends to be stable,. ljVariance S ofnIs smaller. Therefore, if ljIf the value is abnormally changed, Sn＞S0Judging that the user has intermittent meter-throwing electricity stealing behavior, and turning to the step (5), otherwise, turning to the step (3), wherein S0The number of times of day switch is counted in normal users, and the date of possible electricity stealing behavior is less than l0L ofjThe corresponding date. As shown in the area surrounded by the dotted line in fig. 6For the monitoring result of the electricity stealing behavior of the meter throwing, the implementation time interval of the electricity stealing behavior can be obviously seen, and each electric appliance is in a long-time abnormal stop state, so that the electric appliance at the dayjAbnormal condition occurs and passes SnCan be visually reflected;
(3) and judging the electric larceny behavior with less measurement, wherein the electric larceny behavior with less measurement can be judged and determined more accurately if any one of the modes of under current, under voltage or changing power factor is adopted, and the electricity consumption of the user can be accurately estimated and compared in real time. Thus, for PjOf (5) an arbitrary element piIf p is not satisfiedi∈(pmin,pmax) And p isi＜pminThen it is judged as the user with less metering electricity stealing, where pminAnd pmaxRespectively representing real-time minimum power and maximum power values of the same type of electrical equipment during normal operation; the period of time for implementing electricity stealing behavior is p with abnormalityiAnd (3) recording the monitoring time i in the corresponding monitoring time period, and turning to (5), otherwise turning to (4), taking fig. 7 as an example, in the corresponding time period of the area enclosed by the dotted line, the user obviously has the behavior of few metering electricity stealing, and the real-time power of the electrical equipment operated in the implementation time period of the electricity stealing behavior is obviously smaller than the normal value.
(4) The user does not have electricity stealing behavior and finishes the user inspection;
(5) judging that the user is a suspected electricity stealing user, and recording the electricity stealing behavior of the user and the judgment index of the electricity stealing behavior;
step four, estimating the electricity stealing amount:
estimating the electricity stealing amount of the user by utilizing the relation between the accumulated electricity consumption of the same type of electrical equipment and the total electricity consumption of the user under normal conditions and the judgment result and the index of the electricity stealing behavior of the user recorded in the step three, wherein the specific method comprises the following steps:
firstly, on the day when electricity stealing behavior is suspected, the normal value W of the total daily electricity load is estimated according to the following formula:
in the formula (5), wkThe total electricity consumption of the kth user in sigma normal electricity consumers of the same type in the same day is represented by kWh;
second, the total amount of normal daily electricity consumption W of the electrical equipmentrAccording to the types of electricity stealing behaviors, the estimation is carried out according to the following formula:
1) when the electricity stealing behavior of a certain user is that the meter is intermittently thrown to steal electricity,
Wr1＝lmax×pavg×tavg (6)
2) when the electricity stealing behavior of a certain user is the low-metering electricity stealing,
in formulae (6) and (7), tavgAs average value of the duration of operation of the electrical apparatus
pavgAs an average value of active power for all operating periods of the electrical apparatus
Where j has a value of ljAnd lmaxCorresponding date numbers when equal;
thirdly, obtaining a proportionality coefficient K of the estimated electricity stealing quantity1，K2：
1) When the electricity stealing behavior of a certain user is intermittent meter throwing and electricity stealing, K1＝Wr1/W；
2) When the electricity stealing behavior of a certain user is that of few metering electricity stealing, K2＝Wr2/W；
Fourthly, estimating the electricity stealing amount:
1) when the electricity stealing behavior of a certain user is that the meter is intermittently thrown to steal electricity, the estimated value W of the electricity stealing amountsAccording to equation (8):
Ws＝(lmax-lj)×pavg×tavg/K1 (8)
in the formula (8), lmaxFor the user's working state evaluation vector L indicating the number of times the electrical appliance is switched on and off the day mostmaxThe total number of non-zero elements in (1); ljSwitching times of the electric appliance for the day with the swinging meter running; t is tavgAnd pavgThe same as above.
2) When the electricity stealing behavior of a certain user is that of electricity stealing with less metering, the estimated value W of the electricity stealing amountsThe reference value is obtained by equation (9):
thus, the electricity stealing inspection analysis aiming at the user is completed;
step five, repeating the step one to the step four until the electricity stealing inspection analysis of all target users in the specified area is completed;
step six, aiming at the electricity stealing cases generated by the electricity stealing inspection analysis, according to the matching degree of the abnormal user judgment result based on each single index and the inspection analysis result, the weight value of each single index is adjusted in a limited range during the next inspection, and the adjusted weight value is used as the weight value of the next electricity stealing inspection analysis; specifically, the adjustment rule of the weight score of each single index is as follows: if the matching degree of the abnormal user judgment result based on a certain single index and the current inspection result is higher, the corresponding weight score can be properly increased, and if the matching degree of the abnormal user judgment result based on a certain single index and the current inspection result is lower, the corresponding weight score can be properly decreased. Therefore, as the electricity stealing inspection work is carried out, the weight value of each index gradually tends to be optimal along with the adjustment, so as to continuously improve the accuracy of the electricity stealing inspection.
Example (b): the estimation process of the electricity stealing amount of the electricity stealing users of intermittent meter throwing and little metering is as follows:
1) when electricity stealing behavior of a certain user is intermittent meter throwingWhen electricity is stolen, the following data can be obtained through calculation and statistics, K1＝Wr128 × 89.87 × 1233/3600000/12.3 ═ 0.07,/W, and l when electricity stealing is monitoredj17. Therefore, the current electricity stealing amount reference value of the user is as follows:
Ws＝(lmax-lj)×pavg×tavg/K1＝(28-17)×89.87×1233/3600000/0.07＝4.84kWh
table 3 a certain intermittent meter-throwing electricity-stealing user electricity-stealing behavior index list
| lmax | pavg | tavg | W |
| 28 | 89.87W | 1233s | 12.3kWh |
2) When the electricity stealing behavior of a certain user is the electricity stealing with less measurement, the following data can be obtained through calculation and statistics, and K is2＝Wr20.5 x (110+80) x 647 x 44/3600000/12.3 0.061, and L is the electricity stealing behavior judgment index on the day when the electricity stealing behavior is monitoredj＝[0,1,0,...,1],Pj＝[0,59.2,0,61.4,...,58.0],Tj＝[1199,635,1156,...,644]. Therefore, the current electricity stealing amount reference value of the user is as follows:
table 4 list of some few metering electricity stealing user electricity stealing behavior indexes
| lmax | tavg | pmax | pmin | W |
| 44 | 647s | 110W | 80W | 12.3kWh |
While the present invention has been described above in connection with the accompanying drawings, it is not intended to be limited to the specific embodiments described above, which are intended to be illustrative only and not limiting. Those skilled in the art, having the benefit of this disclosure, will appreciate that many modifications are possible in the exemplary embodiments without departing from the scope and spirit of the present invention, as described herein.
Claims (1)
1. An intelligent electricity stealing inspection method based on non-invasive load monitoring, wherein the related intelligent electricity stealing inspection system comprises a data acquisition module, an electricity stealing suspicion user evaluation module, an electricity stealing behavior index calculation module, a user electricity stealing behavior judgment module, an electricity stealing amount reference value estimation module and an information transmission module;
the data acquisition module acquires user daily electricity consumption data and load electricity consumption detail data from an electric power company database, wherein the load electricity consumption detail data are acquired by a non-invasive load monitoring technology and related monitoring equipment;
the electricity stealing suspicion user evaluation module is used for summarizing and expressing a description index system for reflecting and representing electricity stealing and electricity consuming behaviors according to the daily electricity consumption data of the user in the data acquisition module, determining an index threshold value serving as preliminary screening of electricity stealing detection, and screening and positioning the user suspected of having the electricity stealing and electricity consuming behaviors according to the threshold value;
the electricity stealing behavior index calculation module establishes and calculates an electricity stealing behavior evaluation index based on the power load electricity consumption detail data in the data acquisition module, and the evaluation index can be directly used for the subsequent electricity stealing behavior analysis;
the user electricity stealing behavior judging module judges whether the electricity stealing behavior exists in the user according to the electricity stealing behavior judging index, including judging the type of the electricity stealing behavior; if the user is judged not to have electricity stealing behavior, the suspicion of the user is eliminated, otherwise, the type of the electricity stealing behavior of the user is marked, and a judgment result is provided for an electricity stealing inspection department through an information transmission module;
the electricity stealing reference value estimation module estimates the electricity stealing reference value of the user according to the electricity stealing type of the user and provides an electricity stealing estimation result to an electricity stealing inspection department through the information transmission module;
the information transmission module is used for transmitting data information between the intelligent electricity stealing inspection system based on non-invasive load monitoring and relevant departments or people; the functions at least comprise the display and output of monitoring and analysis results;
the method is characterized in that: the intelligent electricity stealing inspection method comprises the following steps:
step one, judging whether the power consumer is a suspected electricity stealing user:
the electricity consumer types comprise industrial users, commercial users and residential users; the method comprises the steps of utilizing user daily electricity quantity data acquired by an electric power company to judge, determining an index system for describing abnormal electricity utilization behaviors according to electricity utilization data records of all users in an inspection area and combined with the electricity utilization data records of the users who historically have electricity stealing behaviors in the inspection area, wherein the index system comprises the following 4 indexes:
1) monthly electric quantity ratio D of user1The ratio of the monthly electricity consumption of the user to the monthly electricity consumption of the industry to which the user belongs;
2) average value D of the ratio of the monthly electricity consumption of each month of the user to the monthly electricity consumption of the industry to which the corresponding month user belongs2；
3) Electricity consumption ratio D of users in holidays3The ratio of the daily average electric quantity of the user during the holiday period to the daily average electric quantity of the industry to which the user belongs during the holiday period;
4) electric proportion D for summer, autumn, winter and spring4The method is characterized by comprising the following steps of (1) referring to the ratio of seasonal power consumption of a user to seasonal power consumption of an industry to which the user belongs;
respectively calculating user indexes and set threshold values D according to the system10，D20，D30，D40Comparing, and judging that the user has abnormal power utilization when the actual calculation result of a certain index is greater than the threshold; wherein D10＝0.45、D20＝0.60、D30The holiday time of the holiday is 3-7 days according to the festivals, the value range is 0.5-0.6, and D40＝0.65；
Calculating the electricity stealing suspicion index H according to the formula (1):
in the formula (1), the weight score α of each indexm∈[0.5,2]Its initial value is set to 1;
the obtained electricity stealing suspicion index H and a threshold value H0Comparing, and comparing the threshold value H of the electricity stealing suspicion index0Setting the index as 2.5, if the electricity stealing suspicion index H of a certain user in the inspection area is smaller than a set threshold, judging the user as an electricity stealing suspicion user, and transferring to the second step; otherwise, the suspected users of electricity stealing are not in the inspection area,finishing the electricity stealing inspection aiming at the area;
step two, calculating the electricity stealing behavior evaluation index:
firstly, dividing electrical equipment of a user into A-type electrical equipment and B-type electrical equipment, wherein the A-type electrical equipment is electrical equipment of which the running state can reflect that the all-day electricity consumption behavior of the user is suitable for analyzing the intermittent meter-throwing electricity stealing behavior, and the B-type electrical equipment is electrical equipment of which the running state monitoring result is not influenced by the less-metering electricity stealing behavior;
then, calculating the electricity stealing behavior judgment index, including:
2-1) establishing an evaluation vector L of the working state of the electrical equipmentjAs shown in formula (2):
Lj＝[l1,l2,l3,...li,...ln]T (2)
in the formula (2), LjA vector l representing the working state of certain electrical equipment at any monitoring time i on the j th dayiE {0, 1}, wherein 0 represents that the electrical equipment is in a shutdown state at the monitoring time i, and 1 represents that the electrical equipment is in an operating state at the monitoring time i;
indicating the cumulative number of switches of the appliance on day j,
representing the daily average number of switching of the electrical apparatus during a monitoring period comprising λ days;
2-2) establishing an electric power evaluation vector for the electric equipment, wherein the electric power evaluation vector is expressed as a formula (3):
Pj＝[p1,p2,p3,...pi,...pn]T (3)
in the formula (3), piIs represented byiThe unit of the running active power value of the corresponding electrical equipment is W;
2-3) establishing an evaluation vector of the duration of the electricity stealing behavior, as shown in formula (4):
Tj＝[t1,t2,t3,...ti,...tn]T (4)
in the formula (4), tiIs represented byiThe corresponding running time length is in the unit of s;
step three, judging the electricity stealing behavior of the user, comprising the following steps:
step 3-1) calculating the variance S of the daily switching times of the user electrical equipment in a monitoring period containing lambda daysn；
Step 3-2) judging whether intermittent meter-throwing electricity-stealing behaviors exist or not, and if so, judging whether intermittent meter-throwing electricity-stealing behaviors exist or notn＞S0Judging that the user has intermittent meter-throwing electricity-stealing behavior, and turning to the step 3-5), otherwise, turning to the step 3-3), wherein S0Counting the variance of the daily switching times in normal users for the same type of electrical equipment;
step 3-3) judging the electricity stealing behavior with less metering, for PjOf (5) an arbitrary element piIf p is not satisfiedi∈(pmin,pmax) And p isi＜pminIf yes, judging that the number of the electricity stealing users is less, and turning to the step 3-5), otherwise, turning to the step 3-4); wherein p isminAnd pmaxRespectively representing real-time minimum power and maximum power values of the same type of electrical equipment during normal operation; the period of time for implementing electricity stealing behavior is p with abnormalityiRecording the monitoring time i in a corresponding monitoring time period;
step 3-4) the user does not have electricity stealing behavior, and the user inspection is finished;
step 3-5) judging that the user is a suspected electricity stealing user, and recording the electricity stealing behavior of the user and evaluation indexes of the electricity stealing behavior;
step four, estimating the electricity stealing amount:
estimating the electricity stealing amount of the user by utilizing the relation between the accumulated electricity consumption of the same type of electrical equipment and the total electricity consumption of the user under normal conditions and the judgment result and the index of the electricity stealing behavior of the user recorded in the step three, wherein the estimation comprises the following steps:
4-1) on the day when electricity stealing behavior is suspected, the normal value W of the total daily electricity consumption of the load is estimated according to the following formula:
in the formula (5), wkThe total electricity consumption of the kth user in sigma normal electricity consumers of the same type in the same day is represented by kWh;
4-2) total amount of normal daily electricity consumption W of electrical equipmentrAccording to the types of electricity stealing behaviors, the estimation is carried out according to the following formula:
when the electricity stealing behavior of a certain user is that the meter is intermittently thrown to steal electricity,
Wr1＝lmax×pavg×tavg (6)
when the electricity stealing behavior of a certain user is the low-metering electricity stealing,
in formulae (6) and (7), tavgIs an average value of the operating duration of the electrical appliance,
pavgis the average value of the active power of the electrical equipment for all the operation periods,
where j has a value of ljAnd lmaxCorresponding date numbers when equal;
4-3) obtaining the proportionality coefficient K of the estimated electricity stealing quantity1，K2：
When the electricity stealing behavior of a certain user is intermittent meter throwing and electricity stealing, K1＝Wr1W; when the electricity stealing behavior of a certain user is that of few metering electricity stealing, K2＝Wr2/W；
4-4) estimating the electricity stealing amount:
when the electricity stealing behavior of a certain user is that the meter is intermittently thrown to steal electricity, the estimated value W of the electricity stealing amountsAccording to equation (8):
Ws＝(lmax-lj)×pavg×tavg/K1 (8)
in the formula (8), lmaxFor the user's working state evaluation vector L indicating the number of times the electrical appliance is switched on and off the day mostmaxThe total number of non-zero elements in (1); ljSwitching times of the electric appliance for the day with the swinging meter running;
when the electricity stealing behavior of a certain user is that of electricity stealing with less metering, the estimated value W of the electricity stealing amountsThe reference value is obtained by equation (9):
thus, the electricity stealing inspection analysis aiming at the user is completed;
step five, repeating the step one to the step four until the electricity stealing inspection analysis of all target users in the specified area is completed;
step six, aiming at the electricity stealing cases generated by the electricity stealing inspection analysis, according to the matching degree of the abnormal user judgment result based on each single index and the inspection analysis result, adjusting the weight value of each single index in the next inspection, and taking the adjusted weight value as the weight value of the next electricity stealing inspection analysis;
wherein, the regulation rule of the weight scores of the single indexes is as follows: if the coincidence degree of the abnormal user judgment result based on a certain single index and the current inspection analysis result is higher, the corresponding weight score is increased, and if the coincidence degree of the abnormal user judgment result based on a certain single index and the current inspection analysis result is lower, the corresponding weight score is decreased.
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