CN107328974B - Electricity stealing identification method and device - Google Patents
Electricity stealing identification method and device Download PDFInfo
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Abstract
The embodiment provides a method and a device for identifying electricity stealing, wherein the method comprises the following steps: acquiring power consumption data of a user to be identified; calculating a preset abnormal power utilization index according to the power utilization data of the user to be identified; if the user to be identified is an abnormal user, generating a power utilization characteristic vector of the user to be identified according to the abnormal power utilization index of the user to be identified; respectively calculating similarity values of the electricity utilization characteristic vector of the user to be identified and preset electricity stealing fingerprint vectors of each electricity stealing method; and if any one of the calculated similarity values exceeds a preset threshold value, indicating that the user to be identified is a suspected electricity stealing user. In the embodiment, whether the user to be identified belongs to the electricity stealing suspected user or not is automatically identified by calculating the similarity value of the electricity utilization characteristic vector of the user to be identified and the electricity stealing fingerprint vector, so that the subjective assumption of the expert on electricity stealing identification is avoided, and the accuracy of electricity stealing identification is improved.
Description
Technical Field
The invention relates to the field of electric power, in particular to an electricity stealing identification method and device.
Background
With the rapid development of economy in China, the electricity utilization demand of users is rapidly increased. However, the electricity stealing behavior, especially the electricity stealing behavior of the special transformer, is increasingly serious, the electricity stealing methods are increasingly abundant, hidden and the electricity stealing loss is increased dramatically year by year.
In the prior art, the identification of the electricity stealing behavior of the special transformer is generally analyzed according to expert experience, and the analysis mode has strong subjectivity and lower identification accuracy.
Disclosure of Invention
In view of this, embodiments of the present invention provide a method and an apparatus for identifying electricity stealing, which can not only automatically identify an electricity stealing method by a vector similarity matching method, but also improve accuracy of electricity stealing identification.
The embodiment of the invention provides an electricity stealing identification method, which comprises the following steps:
acquiring power consumption data of a user to be identified;
calculating a preset abnormal power utilization index according to the power utilization data of the user to be identified;
judging whether the user to be identified belongs to an abnormal user, if so, generating a power utilization characteristic vector of the user to be identified according to the abnormal power utilization index;
respectively calculating similarity values of the electricity utilization characteristic vector of the user to be identified and preset electricity stealing fingerprint vectors of each electricity stealing method;
and if any one of the calculated similarity values exceeds a preset threshold value, indicating that the user to be identified is a suspected electricity stealing user.
Optionally, the abnormal electricity utilization index includes:
the method comprises the following steps of wiring mode, metering mode, line loss capacity increase, daily electricity quantity sudden drop, A phase undervoltage percentage, B phase undervoltage percentage, C phase undervoltage percentage, current unbalance rate, power over capacity, power factor sudden drop, A phase current sudden drop, B phase current sudden drop and C phase current sudden drop.
Optionally, the determining whether the user to be identified belongs to an abnormal user includes:
respectively judging whether each abnormal electricity utilization index of the user to be identified is in a corresponding preset normal range;
and if any abnormal electricity utilization index of the user to be identified is not in a preset normal range, determining that the user to be identified is an abnormal user.
Optionally, the calculating the similarity between the power consumption feature vector of the user to be identified and the preset electricity stealing fingerprint vector of each electricity stealing method respectively includes:
sequentially acquiring a power stealing fingerprint vector corresponding to each power stealing method from a preset power stealing fingerprint library;
and sequentially calculating the power utilization characteristic vector of the user to be identified and the cosine value of the electricity stealing fingerprint vector corresponding to each electricity stealing method.
Optionally, the method for generating the electricity stealing fingerprint vector of the electricity stealing method includes:
acquiring power consumption data of the electricity stealing method;
calculating a preset abnormal power utilization index according to the power utilization data of the power stealing method;
and arranging the abnormal electricity utilization indexes according to a preset sequence to generate a feature vector of an electricity stealing method.
A theft identification device comprising:
the first acquisition unit is used for acquiring the electricity consumption data of the user to be identified;
the first abnormal electricity utilization index calculation unit is used for calculating a preset abnormal electricity utilization index according to the electricity utilization data of the user to be identified;
the first generation unit is used for judging whether the user to be identified belongs to an abnormal user or not, and if the user to be identified belongs to the abnormal user, generating a power utilization characteristic vector of the user to be identified according to the abnormal power utilization index;
the similarity calculation unit is used for respectively calculating the similarity value of the electricity utilization characteristic vector of the user to be identified and the preset electricity stealing fingerprint vector of each electricity stealing method;
and the marking unit is used for indicating that the user to be identified is a suspected electricity stealing user if the calculated value of any one of the similarity degrees exceeds a preset threshold value.
Optionally, the abnormal electricity utilization index includes:
the method comprises the following steps of wiring mode, metering mode, line loss capacity increase, daily electricity quantity sudden drop, A phase undervoltage percentage, B phase undervoltage percentage, C phase undervoltage percentage, current unbalance rate, power over capacity, power factor sudden drop, A phase current sudden drop, B phase current sudden drop and C phase current sudden drop.
Optionally, the generating unit includes:
the first judgment subunit is used for respectively judging whether each abnormal electricity utilization index of the user to be identified is in a corresponding preset normal range;
and the marking subunit is used for determining that the user to be identified is an abnormal user if any abnormal electricity utilization index of the user to be identified is not within a preset normal range.
Optionally, the similarity calculation unit includes:
the acquisition subunit is used for sequentially acquiring the electricity stealing fingerprint vector corresponding to each electricity stealing method from a preset electricity stealing fingerprint library;
and the similarity value calculating subunit is used for sequentially calculating the electricity utilization characteristic vector of the user to be identified and the cosine value of the electricity stealing fingerprint vector corresponding to each electricity stealing method.
Optionally, the method further includes:
the second acquisition unit is used for acquiring the electricity utilization data of the electricity stealing method;
the second abnormal electricity utilization index calculation unit is used for calculating a preset abnormal electricity utilization index according to the electricity utilization data of the electricity stealing method;
and the second generation unit is used for arranging the abnormal electricity utilization indexes according to a preset sequence to generate a feature vector of an electricity stealing method.
The embodiment provides a method for identifying electricity stealing, which comprises the following steps: acquiring power consumption data of a user to be identified; calculating a preset abnormal power utilization index according to the power utilization data of the user to be identified; if the user to be identified is an abnormal user, generating a power utilization characteristic vector of the user to be identified according to the abnormal power utilization index of the user to be identified; respectively calculating similarity values of the electricity utilization characteristic vector of the user to be identified and preset electricity stealing fingerprint vectors of each electricity stealing method; and if any one of the calculated similarity values exceeds a preset threshold value, indicating that the user to be identified is a suspected electricity stealing user. In the embodiment, whether the user to be identified belongs to the electricity stealing suspected user or not is automatically identified by calculating the similarity value of the electricity utilization characteristic vector of the user to be identified and the electricity stealing fingerprint vector, the subjective assumption of experts on electricity stealing identification is avoided, and the accuracy of electricity stealing identification is improved.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, it is obvious that the drawings in the following description are only embodiments of the present invention, and for those skilled in the art, other drawings can be obtained according to the provided drawings without creative efforts.
Fig. 1 is a flow chart illustrating a method for identifying electricity stealing according to an embodiment of the present invention;
fig. 2 is a schematic structural diagram illustrating an electricity stealing identification device according to an embodiment of the present invention.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
Referring to fig. 1, a flow chart of a method for identifying electricity stealing according to an embodiment of the present invention is shown, in the embodiment, the method is used for a dedicated transformer, and the method includes:
s101: and acquiring the electricity utilization data of the user to be identified.
In this embodiment, the power consumption data of the user to be identified includes: information of users of the special transformer, information of equipment of the special transformer, line loss information, voltage information, current information, electric quantity information and the like. In addition to this, the electricity usage data of the user to be identified may also include historical violation records.
In this embodiment, it should be noted that, because the method is used for identifying electricity stealing of a dedicated transformer, all the users to be identified in this embodiment are users who use the dedicated transformer, which is referred to as dedicated transformer users for short.
S102: and calculating a preset abnormal power utilization index according to the acquired power utilization data of the user to be identified.
In this embodiment, the preset abnormal power utilization index includes: power over capacity, daily electricity quantity sudden drop, line loss sudden increase, current unbalance rate, power unbalance rate, A phase under-voltage percentage, B phase under-voltage percentage, C term under-voltage percentage, current A sudden drop rate, current B sudden drop rate, current C sudden drop rate, power factor sudden drop and daily power sudden drop.
Wherein, each abnormal electricity utilization index has a corresponding calculation method, as shown in the following table 1:
s103: and judging whether the user to be identified belongs to an abnormal user, if so, generating a power utilization characteristic vector according to the abnormal power utilization index obtained by calculation.
In this embodiment, the abnormal electricity utilization indicators calculated in S102 all have a normal range value, and whether an abnormal condition occurs is determined by determining whether the abnormal electricity utilization indicators are within the normal range, specifically, the method includes:
respectively judging whether each abnormal user index of the user to be identified is in a corresponding normal range;
and if any abnormal user index of the user to be identified is not in the preset normal range, the user to be identified is an abnormal user.
It should be noted that if all the abnormal electricity utilization indexes are within the preset normal range, indicating that the user to be identified is not an abnormal user, the subsequent operation is not required; and if any user index to be identified is not in the normal range of the index, indicating that the user to be identified is an abnormal user.
In this embodiment, the generated electricity utilization feature vectors are obtained by arranging the abnormal electricity utilization indicators in a preset order, and each abnormal electricity utilization indicator exists in the form of a vector.
For example, the following steps are carried out: characteristic vector of electricity consumption A ═ a1,a2,a3,a4,…,a10,a11,a12,a13) Wherein each component has the meaning of:
wherein the order of the individual components in the feature vector A, i.e. a1,a2,a3,a4,…,a10,a11,a12,a13Is the preset arrangement sequence of the abnormal indexes.
S104: and respectively calculating the similarity between the electricity utilization characteristic vector of the user to be identified and the preset electricity stealing fingerprint vector of each electricity stealing method.
S105: and if any one of the calculated similarity values exceeds a preset threshold value, the user to be identified is the suspected electricity stealing user.
In this embodiment, the electricity stealing methods are stored in an electricity stealing fingerprint database, and each electricity stealing method corresponds to one electricity stealing fingerprint vector. The electricity stealing method comprises the following steps: private capacity increasing, secondary side A phase shunt, secondary side C phase shunt, secondary side symmetrical shunt, secondary side A, B, C balanced shunt, CT primary side A phase shunt, CT primary side C phase shunt, CT primary side symmetrical shunt, cross-winding measurement, four wire high meter B phase voltage loss undervoltage, four wire high meter A phase voltage loss undervoltage, four wire high meter C phase voltage loss undervoltage, four wire low meter B voltage loss, four wire low meter A voltage loss, four wire low meter C voltage loss, three wire high meter A voltage loss, three wire high meter C voltage loss, three wire low meter A voltage loss, three wire low meter C voltage loss, etc.
It should be noted that the preset electricity stealing fingerprint vector includes all electricity stealing methods in the electricity stealing fingerprint database. Therefore, it is necessary to calculate the similarity between the power consumption feature vector of the user to be identified and the electricity stealing fingerprint vector of each electricity stealing technique in the electricity stealing fingerprint database.
Wherein S104 can be implemented by the following formula:
wherein X is (X)1,x2,x3...xn) Representing a power stealing fingerprint vector; y ═ Y1,y2,y3...yn) Representing the feature vector of the user to be identified.
When cos (theta) > a, the user to be identified is marked as a suspected electricity stealing user, wherein a is a constant and represents a preset threshold value.
For example, when cos (θ) > 0.9, the to-be-identified user may be marked as a suspected electricity stealing user by marking that the similarity is greater than 90 minutes, and the electricity stealing method corresponding to the electricity stealing fingerprint vector is the electricity stealing method used by the suspected electricity stealing user.
In this embodiment, the generation process of the specific electricity stealing fingerprint vector of the electricity stealing method includes:
acquiring power utilization data of a power stealing method;
calculating a preset abnormal power utilization index according to the power utilization data of the power stealing method;
and arranging the abnormal electricity utilization indexes according to a preset sequence to generate a feature vector of an electricity stealing method.
The sequence of the abnormal electricity utilization indexes can be as follows: wiring mode, metering mode, line loss sudden increase, daily electricity quantity sudden drop, A under voltage, B under voltage, C under voltage, current unbalance rate, power over capacity, power factor sudden drop, current A sudden drop, current B sudden drop and current C sudden drop.
For example, the electricity stealing method is private augmented feature vector B ═ B1,b2,b3,b4,…,b10,b11,b12,b13) Wherein each component has the meaning of:
for example, the following steps are carried out: the saving form of the electricity stealing fingerprint database can be the form of the following table 2:
TABLE 2
It should be noted that the electricity stealing fingerprint database is continuously updated, and when a new electricity stealing technique is found, an electricity stealing fingerprint vector of the electricity stealing technique is generated and stored in the electricity stealing fingerprint database.
In this embodiment, a front-line staff can carry out on-site forensics on the electricity stealing suspected user according to the detected list of the electricity stealing suspected user and the relevant information of the electricity stealing suspected user. Wherein, the relevant information of the electricity stealing suspicion user comprises the following information: the number of the electricity stealing user, the user name, the unit, the address, the electricity stealing method, the suspicion degree and the like.
In this embodiment, the abnormal electricity utilization index of the user to be identified is calculated, the similarity value between the abnormal electricity utilization index calculation of the user to be identified and the electricity stealing fingerprint vector of each electricity stealing method in the preset electricity stealing fingerprint library is calculated, and if any one obtained similarity value exceeds a preset threshold value, the user to be identified is the suspected electricity stealing user. By the method, not only can the electricity stealing method be automatically identified by the vector similarity matching method, but also the accuracy of electricity stealing identification is improved.
Referring to fig. 2, there is shown a schematic structural diagram of an electricity stealing identification device provided by an embodiment of the present invention, in this embodiment, the device includes:
201: the first acquisition unit is used for acquiring the electricity consumption data of the user to be identified;
202: the first abnormal electricity utilization index calculation unit is used for calculating a preset abnormal electricity utilization index according to the electricity utilization data of the user to be identified;
203: the first generation unit is used for judging whether the user to be identified belongs to an abnormal user or not, and if the user to be identified belongs to the abnormal user, generating a power utilization characteristic vector of the user to be identified according to the abnormal power utilization index;
204: the similarity calculation unit is used for respectively calculating the similarity value of the electricity utilization characteristic vector of the user to be identified and the preset electricity stealing fingerprint vector of each electricity stealing method;
205: and the marking unit is used for indicating that the user to be identified is a suspected electricity stealing user if the calculated value of any one of the similarity degrees exceeds a preset threshold value.
Optionally, the abnormal electricity utilization index includes:
the method comprises the following steps of wiring mode, metering mode, line loss capacity increase, daily electricity quantity sudden drop, A phase undervoltage percentage, B phase undervoltage percentage, C phase undervoltage percentage, current unbalance rate, power over capacity, power factor sudden drop, A phase current sudden drop, B phase current sudden drop and C phase current sudden drop.
Optionally, the generating unit includes:
the first judgment subunit is used for respectively judging whether each abnormal electricity utilization index of the user to be identified is in a corresponding preset normal range;
and the marking subunit is used for determining that the user to be identified is an abnormal user if any abnormal electricity utilization index of the user to be identified is not within a preset normal range.
Optionally, the similarity calculation unit includes:
the acquisition subunit is used for sequentially acquiring the electricity stealing fingerprint vector corresponding to each electricity stealing method from a preset electricity stealing fingerprint library;
and the similarity value calculating subunit is used for sequentially calculating the electricity utilization characteristic vector of the user to be identified and the cosine value of the electricity stealing fingerprint vector corresponding to each electricity stealing method.
Optionally, the method further includes:
the second acquisition unit is used for acquiring the electricity utilization data of the electricity stealing method;
the second abnormal electricity utilization index calculation unit is used for calculating a preset abnormal electricity utilization index according to the electricity utilization data of the electricity stealing method;
and the second generation unit is used for arranging the abnormal electricity utilization indexes according to a preset sequence to generate a feature vector of an electricity stealing method.
Through the device of the embodiment, the similarity value of the power utilization characteristic vector and the electricity stealing fingerprint vector of the user to be identified is calculated, so that the mode of automatically identifying whether the user to be identified belongs to the electricity stealing suspected user is realized, the subjective assumption of the expert on electricity stealing identification is avoided, and the accuracy of electricity stealing identification is improved.
It should be noted that, in the present specification, the embodiments are all described in a progressive manner, each embodiment focuses on differences from other embodiments, and the same and similar parts among the embodiments may be referred to each other.
The previous description of the disclosed embodiments is provided to enable any person skilled in the art to make or use the present invention. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the generic principles defined herein may be applied to other embodiments without departing from the spirit or scope of the invention. Thus, the present invention is not intended to be limited to the embodiments shown herein but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.
Claims (10)
1. A method of identifying theft of electricity, comprising:
acquiring power consumption data of a user to be identified of the special transformer; the electricity consumption data of the user to be identified comprises: at least one of data of a special transformer user, special transformer equipment information, line loss information, voltage information, current information, electric quantity information and historical violation records;
calculating a preset abnormal power utilization index according to the power utilization data of the user to be identified;
judging whether the user to be identified belongs to an abnormal user, if so, generating a power utilization characteristic vector of the user to be identified according to the abnormal power utilization index;
respectively calculating similarity values of the electricity utilization characteristic vector of the user to be identified and preset electricity stealing fingerprint vectors of each electricity stealing method;
if any one of the calculated similarity values exceeds a preset threshold value, the user to be identified is a suspected electricity stealing user;
wherein, the value for calculating the similarity between the electricity utilization characteristic vector of the user to be identified and the preset electricity stealing fingerprint vector of each electricity stealing method is calculated by the following formula:
wherein X is (X)1,x2,x3...xn) Representing a power stealing fingerprint vector; y ═ Y1,y2,y3...yn) Representing a feature vector of a user to be identified;
if any calculated similarity value exceeds a preset threshold value, the step of indicating that the user to be identified is a suspected electricity stealing user includes: when cos (theta) > a, the user to be identified is marked as a suspected electricity stealing user, wherein a is a constant and represents a preset threshold value.
2. The method of claim 1, wherein the abnormal electricity usage indicator comprises:
the method comprises the following steps of wiring mode, metering mode, line loss capacity increase, daily electricity quantity sudden drop, A phase undervoltage percentage, B phase undervoltage percentage, C phase undervoltage percentage, current unbalance rate, power over capacity, power factor sudden drop, A phase current sudden drop, B phase current sudden drop and C phase current sudden drop.
3. The method according to claim 1, wherein the determining whether the user to be identified belongs to an abnormal user comprises:
respectively judging whether each abnormal electricity utilization index of the user to be identified is in a corresponding preset normal range;
and if any abnormal electricity utilization index of the user to be identified is not in a preset normal range, determining that the user to be identified is an abnormal user.
4. The method according to claim 1, wherein the calculating the similarity value of the electricity stealing fingerprint vector of each preset electricity stealing method and the electricity consuming feature vector of the user to be identified respectively comprises:
sequentially acquiring a power stealing fingerprint vector corresponding to each power stealing method from a preset power stealing fingerprint library;
and sequentially calculating the power utilization characteristic vector of the user to be identified and the cosine value of the electricity stealing fingerprint vector corresponding to each electricity stealing method.
5. The method according to claim 4, wherein the method for generating the electricity stealing fingerprint vector of the electricity stealing technique comprises:
acquiring power consumption data of the electricity stealing method;
calculating a preset abnormal power utilization index according to the power utilization data of the power stealing method;
and arranging the abnormal electricity utilization indexes according to a preset sequence to generate a feature vector of an electricity stealing method.
6. An electricity stealing identification device, comprising:
the first acquisition unit is used for acquiring the electricity utilization data of a user to be identified of the special transformer; the electricity consumption data of the user to be identified comprises: at least one of data of a special transformer user, special transformer equipment information, line loss information, voltage information, current information, electric quantity information and historical violation records;
the first abnormal electricity utilization index calculation unit is used for calculating a preset abnormal electricity utilization index according to the electricity utilization data of the user to be identified;
the first generation unit is used for judging whether the user to be identified belongs to an abnormal user or not, and if the user to be identified belongs to the abnormal user, generating a power utilization characteristic vector of the user to be identified according to the abnormal power utilization index;
the similarity calculation unit is used for respectively calculating the similarity value of the electricity utilization characteristic vector of the user to be identified and the preset electricity stealing fingerprint vector of each electricity stealing method;
the marking unit is used for indicating that the user to be identified is a suspected electricity stealing user if the calculated value of any one of the similarity degrees exceeds a preset threshold value;
wherein, the value for calculating the similarity between the electricity utilization characteristic vector of the user to be identified and the preset electricity stealing fingerprint vector of each electricity stealing method is calculated by the following formula:
wherein X is (X)1,x2,x3...xn) Representing a power stealing fingerprint vector; y ═ Y1,y2,y3...yn) Representing a feature vector of a user to be identified;
if any calculated similarity value exceeds a preset threshold value, the step of indicating that the user to be identified is a suspected electricity stealing user includes: when cos (theta) > a, the user to be identified is marked as a suspected electricity stealing user, wherein a is a constant and represents a preset threshold value.
7. The apparatus of claim 6, wherein the abnormal electricity usage indicator comprises:
the method comprises the following steps of wiring mode, metering mode, line loss capacity increase, daily electricity quantity sudden drop, A phase undervoltage percentage, B phase undervoltage percentage, C phase undervoltage percentage, current unbalance rate, power over capacity, power factor sudden drop, A phase current sudden drop, B phase current sudden drop and C phase current sudden drop.
8. The apparatus of claim 6, wherein the generating unit comprises:
the first judgment subunit is used for respectively judging whether each abnormal electricity utilization index of the user to be identified is in a corresponding preset normal range;
and the marking subunit is used for determining that the user to be identified is an abnormal user if any abnormal electricity utilization index of the user to be identified is not within a preset normal range.
9. The apparatus according to claim 6, wherein the similarity calculation unit includes:
the acquisition subunit is used for sequentially acquiring the electricity stealing fingerprint vector corresponding to each electricity stealing method from a preset electricity stealing fingerprint library;
and the similarity value calculating subunit is used for sequentially calculating the electricity utilization characteristic vector of the user to be identified and the cosine value of the electricity stealing fingerprint vector corresponding to each electricity stealing method.
10. The apparatus of claim 9, further comprising:
the second acquisition unit is used for acquiring the electricity utilization data of the electricity stealing method;
the second abnormal electricity utilization index calculation unit is used for calculating a preset abnormal electricity utilization index according to the electricity utilization data of the electricity stealing method;
and the second generation unit is used for arranging the abnormal electricity utilization indexes according to a preset sequence to generate a feature vector of an electricity stealing method.
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| CN109213787B (en) * | 2018-11-07 | 2022-03-08 | 闫福录 | Electricity larceny prevention algorithm chip integrated with feature library and electricity larceny prevention method |
| CN110264015A (en) * | 2019-06-28 | 2019-09-20 | 国网河南省电力公司电力科学研究院 | It opposes electricity-stealing and checks monitoring method and platform |
| CN110988422B (en) * | 2019-12-19 | 2022-04-26 | 北京中电普华信息技术有限公司 | Electricity stealing identification method and device and electronic equipment |
| CN111443237B (en) * | 2020-04-20 | 2022-07-12 | 北京中电普华信息技术有限公司 | Method and system for determining compensation electric quantity |
| CN112649641B (en) * | 2020-12-14 | 2023-05-02 | 北京科东电力控制***有限责任公司 | Electricity stealing user judging method based on electricity stealing characteristics |
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