CN-121978379-A - Smart grid line tool box-based electricity stealing user positioning method and system

CN121978379ACN 121978379 ACN121978379 ACN 121978379ACN-121978379-A

Abstract

The invention relates to a method and a system for locating a power stealing user based on a smart grid line toolbox, wherein the method comprises the steps of collecting line electrical parameters and electric quantity data of the line toolbox, generating a line loss rate reference curve and extracting real-time fluctuation characteristics, judging non-planned destructive power failure and recording a timestamp by combining the real-time fluctuation characteristics and an original waveform of load current before power failure when power failure occurs to a main power, starting a standby battery to enter a theft prevention co-location mode, reporting a geographic position and acquiring line electrical parameter snapshots and associated user load data in a key time window, calculating the suspected intensity of instantaneous behavior deviation and line loss contribution and fusing to generate a suspected index to form a suspected user sorting list, encrypting and binding the sorting list with the geographic position and the timestamp to generate a data packet to be reported and a tamper-proof verification code, periodically reporting the data packet and the verification code in a low power consumption stage, and uploading an event analysis report after the main power is recovered. The invention has the effect of improving the positioning accuracy.

Inventors

WANG CHAOLIANG
YE FANGBIN
SHEN WANGPING
LIU WEI
SHEN HAO
SHI BOWEN
WU YUEBO
WANG JINRONG
SUN JIANQIAO
XU SHIYU
WANG WEIFENG
JIANG QUN

Assignees

国网浙江省电力有限公司营销服务中心

Dates

Publication Date: 20260505
Application Date: 20260130

Claims (10)

1. A smart grid line toolbox-based electricity theft user positioning method, the method comprising: Acquiring line electrical parameters and electric quantity data of a line tool box installation branch, generating a line loss rate reference curve, and determining real-time fluctuation characteristics according to the line loss rate reference curve; When the main power is monitored to be powered down, determining whether an unintended destructive power down occurs or not based on the real-time fluctuation characteristics and the original waveform of the load current before the power down, and recording a corresponding power down time stamp; Under the condition that the unplanned destructive power failure is determined to occur, starting a standby battery to enter an anti-theft co-location mode, reporting the geographic position of a line tool box, and acquiring line electrical parameter snapshots and associated user load data in a key time window; Under the anti-theft co-location mode, calculating instantaneous behavior deviation degree and line loss contribution suspicion intensity based on the line electrical parameter snapshot and the associated user load data, and carrying out weighted fusion on the instantaneous behavior deviation degree and the line loss contribution suspicion intensity to generate a comprehensive suspicion index; generating a suspicion priority list according to the comprehensive suspicion index, and carrying out encryption binding on the suspicion priority list, the geographic position and the power-down time stamp to obtain a data packet to be reported; And generating a tamper-proof verification code for the data packet to be reported, reporting the geographic position in a low-power-consumption reporting stage according to a preset time period, intermittently reporting the data packet to be reported and the tamper-proof verification code corresponding to the data packet to be reported, and generating a power failure event analysis report after the main power is recovered to upload the data packet to be reported to a master station.
2. The smart grid line tool kit-based electricity theft user positioning method according to claim 1, wherein the collecting line electrical parameters and electrical quantity data of a line tool kit installation branch, generating a line loss rate reference curve, and determining real-time fluctuation characteristics according to the line loss rate reference curve, comprises: Acquiring a dynamic line loss rate sequence corresponding to the electric quantity data of the line electric parameters; Performing time sequence decomposition on the dynamic line loss rate sequence to obtain a trend term and a period term, and performing fitting treatment on the trend term and the period term to generate the line loss rate reference curve; acquiring an actual line loss rate under a unified time reference, and performing deviation calculation based on the actual line loss rate and the line loss rate reference curve to obtain a line loss rate relative deviation; And carrying out standardization processing on the relative deviation of the line loss rate to obtain the real-time fluctuation characteristic.
3. The smart grid line toolbox-based electricity theft user positioning method according to claim 2, wherein the performing a normalization process on the line loss rate relative deviation to obtain the real-time fluctuation feature comprises: Counting the deviation mean value and the deviation standard deviation of the line loss rate relative deviation in a preset time window; normalizing the relative deviation of the line loss rate based on the deviation mean value and the deviation standard deviation to obtain a normalized deviation sequence; and outputting the standard deviation sequence as the real-time fluctuation characteristic.
4. The smart grid line toolbox-based power theft user location method of claim 1, wherein the determining whether an unintended destructive power loss occurs based on the real-time fluctuation feature and a pre-power loss load current raw waveform when a main power loss is monitored comprises: Extracting a line loss rate fluctuation sequence corresponding to the real-time fluctuation feature in a preset time period before a main power-down triggering moment; calculating an approximate entropy for the line loss rate fluctuation sequence to obtain a line loss complexity characteristic; Performing wavelet packet transformation on the original waveform of the load current before power failure, extracting at least one characteristic frequency band energy, and calculating a corresponding energy change rate to obtain waveform distortion characteristics; and under the condition that the line loss complexity characteristic and the waveform distortion characteristic meet preset judging conditions, determining that the unplanned destructive power failure occurs.
5. The smart grid line toolbox-based electricity theft user positioning method according to claim 1, wherein reporting the geographic location of the line toolbox and obtaining line electrical parameter snapshots and associated user load data within a critical time window in the case that the unplanned destructive power loss is determined to occur comprises: determining a key time window comprising a first time window before power failure and a second time window after power failure based on the power failure time stamp; collecting line electrical parameters in the key time window and generating a line electrical parameter snapshot; and calling the related user load data in the key time window and performing time alignment processing to obtain the related user load data.
6. The smart grid line toolbox-based electricity theft user positioning method according to claim 1, wherein the calculating the instantaneous behavior deviation degree and the line loss contribution suspicion intensity based on the line electrical parameter snapshot and the associated user load data, and the weighting and fusing the instantaneous behavior deviation degree and the line loss contribution suspicion intensity to generate a comprehensive suspicion index includes: Acquiring a user power curve in the associated user load data, extracting a historical synchronization reference curve, calculating a deviation distance based on the user power curve and the historical synchronization reference curve, and generating the instantaneous behavior deviation degree by combining a mutation association degree; acquiring historical electricity consumption data and branch line loss rate data of an associated user, calculating influence scores based on the historical electricity consumption data and the branch line loss rate data, and generating the line loss contribution suspicion intensity according to the influence scores and the change direction consistency in the key time window; and normalizing the instantaneous behavior deviation degree and the line loss contribution suspicion intensity, and carrying out weighted fusion based on preset dynamic weights to obtain the comprehensive suspicion index.
7. The smart grid line toolbox-based electricity theft user location method of claim 6, wherein the calculating a deviation distance based on the user power curve and the historical contemporaneous reference curve and generating the instantaneous behavioral deviation in combination with a sudden change correlation comprises: Calculating a mahalanobis distance based on the user power curve and the historical synchronization reference curve to obtain a first deviation; Extracting power mutation time of the user power curve and mutation time of the total power of the branch, and calculating mutual information between the power mutation time to obtain a second deviation; and carrying out weighted fusion on the first deviation and the second deviation to obtain the instantaneous behavior deviation degree.
8. The smart grid line toolbox-based electricity theft user positioning method according to claim 6, wherein the calculating an influence score based on the historical electricity consumption data and the branch line loss rate data, and generating the line loss contribution suspicion intensity according to the influence score and the change direction consistency in the key time window, comprises: constructing a vector autoregressive model based on the historical electricity consumption data and the branch line loss rate data, and calculating a Grangel causal statistic based on the vector autoregressive model to obtain the influence score; Calculating a symbol consistency coefficient based on the user power change direction and the line loss rate change direction in the key time window, and carrying out combination operation on the influence score and the symbol consistency coefficient to obtain the suspected line loss contribution strength; And determining the dynamic weight based on an analytic hierarchy process, and carrying out weighted fusion on the normalized instantaneous behavior deviation degree and the line loss contribution suspicion intensity based on the dynamic weight to obtain the comprehensive suspicion index.
9. The method for locating a power stealing user based on a smart grid line kit according to claim 1, wherein reporting the geographical location and intermittently reporting the data packet to be reported according to a preset time period in a low power consumption reporting stage, generating a tamper-proof verification code for the data packet to be reported, and generating a power down event analysis report after recovering the main power, and uploading the report to a host station comprises: extracting a preset number of suspects from the suspects priority ordering list to generate suspects list abstract, and combining the suspects list abstract with a unique identifier of the equipment and the power-down timestamp to obtain abstract data; symmetrically encrypting the abstract data and the geographic position to obtain ciphertext data, and taking the ciphertext data as the data packet to be reported; Generating a message authentication code as a tamper-proof verification code based on the data packet to be reported, and intermittently reporting the tamper-proof verification code and the data packet to be reported together; entering a deep sleep state between adjacent intermittent reporting, monitoring the state of the standby battery in a low-power consumption reporting stage, and reporting a corresponding alarm sign when the state of the standby battery meets an alarm condition; and generating a power failure event analysis report uploading master station after the main power is recovered, wherein the power failure event analysis report at least comprises a judging result of the unplanned destructive power failure, the line electrical parameter snapshot, the comprehensive suspected index, the suspected user priority ordering list and a low-power consumption reporting log.
10. A smart grid line toolbox-based electricity theft user positioning system, the system comprising: the line loss acquisition module is used for acquiring line electrical parameters and electric quantity data of the line tool box installation branch, generating a line loss rate reference curve, and determining real-time fluctuation characteristics according to the line loss rate reference curve; The power-down judging module is used for determining whether an unintended destructive power down occurs or not based on the real-time fluctuation characteristics and the original waveform of the load current before the power down when the power down of the main power is monitored, and recording a corresponding power down time stamp; the co-location module is used for starting the standby battery to enter an anti-theft co-location mode under the condition that the occurrence of the unplanned destructive power failure is determined, reporting the geographic position of the line toolbox, and acquiring line electrical parameter snapshots and associated user load data in a key time window; the suspicion calculation module is used for calculating instantaneous behavior deviation degree and line loss contribution suspicion intensity based on the line electrical parameter snapshot and the associated user load data in the anti-theft co-location mode, and carrying out weighted fusion on the instantaneous behavior deviation degree and the line loss contribution suspicion intensity to generate a comprehensive suspicion index; The ordering and binding module is used for generating a suspicion priority ordering list according to the comprehensive suspicion indexes, and carrying out encryption binding on the suspicion priority ordering list, the geographic position and the power-down timestamp to obtain a data packet to be reported; The low-power consumption reporting module is used for generating a tamper-proof verification code for the data packet to be reported, reporting the geographic position in a low-power consumption reporting stage according to a preset time period, intermittently reporting the data packet to be reported and the tamper-proof verification code corresponding to the data packet to be reported, and generating a power failure event analysis report after the main power is recovered to upload the data packet to be reported and the tamper-proof verification code to the master station.

Description

Smart grid line tool box-based electricity stealing user positioning method and system Technical Field The invention belongs to the technical field of intelligent power grid electricity consumption monitoring, and particularly relates to a method and a system for positioning electricity stealing users based on a intelligent power grid line tool box. Background At present, the electric field scene for the power distribution side has the advantages of large number of users and strong fluctuation of power consumption, the running state of the line side is obviously influenced by factors such as load change, maintenance operation, external disturbance and the like, monitoring equipment such as a line tool box and the like are required to continuously acquire line electric parameters and electric quantity data under the complex power supply condition and keep the consistency of data time sequence, and meanwhile, the traceability of event information and the availability of positioning information are still required to be ensured under the sudden power failure condition. The existing electricity larceny identification and positioning mode generally depends on abnormal characteristic monitoring and event reporting at the line side, and when the main electricity is powered down or external force is destroyed and other abnormal scenes, the problems of inaccurate event property judgment, interruption of an available data link and unstable positioning result easily occur, so that the positioning efficiency of electricity larceny users is low and the misjudgment risk is increased. Disclosure of Invention The invention aims to provide a method and a system for positioning a power stealing user based on a smart grid line tool box, which are used for solving the technical problem that the positioning result is unreliable due to unstable event judgment and data reporting under the abnormal power failure scene in the existing method. In order to achieve the above purpose, the present invention adopts the following technical scheme: The invention provides a method for positioning a power stealing user based on a smart grid line tool box, which comprises the following steps: Acquiring line electrical parameters and electric quantity data of a line tool box installation branch, generating a line loss rate reference curve, and determining real-time fluctuation characteristics according to the line loss rate reference curve; When the main power is monitored to be powered down, determining whether an unintended destructive power down occurs or not based on the real-time fluctuation characteristics and the original waveform of the load current before the power down, and recording a corresponding power down time stamp; Under the condition that the unplanned destructive power failure is determined to occur, starting a standby battery to enter an anti-theft co-location mode, reporting the geographic position of a line tool box, and acquiring line electrical parameter snapshots and associated user load data in a key time window; Under the anti-theft co-location mode, calculating instantaneous behavior deviation degree and line loss contribution suspicion intensity based on the line electrical parameter snapshot and the associated user load data, and carrying out weighted fusion on the instantaneous behavior deviation degree and the line loss contribution suspicion intensity to generate a comprehensive suspicion index; generating a suspicion priority list according to the comprehensive suspicion index, and carrying out encryption binding on the suspicion priority list, the geographic position and the power-down time stamp to obtain a data packet to be reported; And generating a tamper-proof verification code for the data packet to be reported, reporting the geographic position in a low-power-consumption reporting stage according to a preset time period, intermittently reporting the data packet to be reported and the tamper-proof verification code corresponding to the data packet to be reported, and generating a power failure event analysis report after the main power is recovered to upload the data packet to be reported to a master station. By adopting the technical proposal, the line loss reference standard can be formed in a comparison way and the degree of abnormality of the line loss can be quantified by collecting the electrical parameters and the electrical quantity data of the line and generating a line loss rate reference curve and determining the real-time fluctuation characteristic, thereby improving the sensitivity and stability of line loss abnormality identification; by discriminating an unplanned destructive power down based on the real-time fluctuation characteristic and the original waveform of the load current before the power down and recording the power down time stamp, the destructive event and the non-destructive event can be distinguished when the power down occurs, thereby avoiding false triggering and providing