Distributed photovoltaic electricity stealing identification method, system and device

Abstract

The invention discloses a distributed photovoltaic electricity stealing identification method, system and device, and belongs to the field of power systems. The method comprises the steps of obtaining actual data through a three-phase data collector and an illumination collector, obtaining photovoltaic electricity meter data through a photovoltaic electricity meter, judging whether voltage electricity stealing abnormity, current electricity stealing abnormity and power electricity stealing abnormity exist in a line or not based on the actual data and the photovoltaic electricity meter data, and sending alarm information to a user if abnormity exists. Therefore, by implementing the method and the device, the problem that the distributed photovoltaic electricity stealing behavior is difficult to accurately identify in the prior art can be solved.

Description

Technical Field

[0001] The present invention relates to the field of power systems, and in particular, to a method, system and device for identifying distributed photovoltaic power theft. Background Art

[0002] In modern power systems, as an important form of renewable energy, the accuracy of power generation metering of distributed photovoltaic power generation is directly related to the effective implementation of green certificate issuance and subsidy policies. With the rapid growth of the installed capacity of distributed photovoltaics, illegal users use high-tech means such as boost methods, current boost methods, mains conversion methods, and photovoltaic simulation methods to inflate power generation data to defraud subsidies, resulting in abnormal line losses and inaccurate metering.

[0003] Existing technical means are difficult to effectively address the core challenges of distributed photovoltaic power theft monitoring: First, power theft devices are small in size and easy to hide, such as boost devices and voltage regulators, and are difficult to detect by conventional inspection means; second, the intermittency and volatility of photovoltaic power generation make power data monitoring complex, and power theft behavior may be achieved by interfering with metering parameters or data transmission, and traditional power comparison methods cannot accurately identify; due to the superposition of the above factors, existing monitoring methods are difficult to achieve real-time identification and accurate evidence collection of new types of power theft behaviors such as boost methods and current boost methods, resulting in economic losses for power enterprises. Summary of the Invention

[0004] The present invention provides a method, system and device for identifying distributed photovoltaic power theft, which can solve the problem that it is difficult to accurately identify distributed photovoltaic power theft behavior in the prior art.

[0005] In a first aspect, an embodiment of the present invention provides a method for identifying distributed photovoltaic power theft, including:

[0006] Obtain actual data through a three-phase data collector and a light collector, and obtain photovoltaic meter data through a photovoltaic meter; wherein, three split-core current transformers of the three-phase data collector are clamped in sequence at the corresponding phase current incoming lines of the photovoltaic meter, and the three-phase voltage lines of the three-phase data collector are connected in parallel to the voltage lines of the photovoltaic meter;

[0007] Based on the actual data and the photovoltaic meter data, determine whether there is any type of power theft anomaly in the line connected to the photovoltaic meter; wherein, the power theft anomaly includes: voltage power theft anomaly, current power theft anomaly and power power theft anomaly;

[0008] When it is determined that there is any type of power theft anomaly, send a corresponding warning message to the user.

[0009] In the embodiments of the present application, through multi-dimensional data collection and comparative analysis, the ability to identify distributed photovoltaic power theft behavior has been effectively improved. Specifically, in the present application, by obtaining photovoltaic meter data and comparing it with actual monitoring data, three typical power theft behaviors, namely abnormal voltage loop, abnormal current loop, and abnormal photovoltaic power, can be dynamically identified: the comparison of voltage data can detect the virtual voltage increment caused by the boosting device, the comparison of current data can find the current deviation caused by the current boosting device, and the correlation analysis of light intensity and power generation can expose false power generation behaviors such as connecting to the mains instead of photovoltaic power generation or photovoltaic simulation. The method of the present application breaks through the limitations of single-dimensional monitoring and significantly enhances the comprehensiveness and accuracy of power theft identification.

[0010] As a preferred example of the first aspect, based on the actual data and the photovoltaic meter data, it is determined whether there is any type of power theft abnormality in the line connected to the photovoltaic meter; wherein, the power theft abnormalities include: voltage power theft abnormality, current power theft abnormality, and power power theft abnormality; including:

[0011] The actual data includes an actual voltage data set, and the photovoltaic meter data includes a displayed voltage data set;

[0012] Subtract the actual voltage corresponding to each time point in the actual voltage data set from the displayed voltage corresponding to each time point in the displayed voltage data set to obtain the voltage data difference corresponding to each time point;

[0013] Take the ratio of the voltage data difference corresponding to each time point to the actual voltage corresponding to each time point as a judgment value, and sort all the judgment values in chronological order to form a voltage judgment value set;

[0014] Traverse each judgment value in the voltage judgment value set in chronological order. If the number of consecutive first preset judgment times is greater than the first preset threshold, it is determined that there is the voltage power theft abnormality, otherwise it is determined that there is no such voltage power theft abnormality.

[0015] In this preferred example, by calculating the voltage data difference at each time point and further performing threshold judgment through the voltage data differences at multiple consecutive time points, the abnormal voltage change trend can be accurately captured, avoiding misjudgment of a single data point, and power theft behaviors such as the boosting method implemented by changing voltage parameters can be accurately identified.

[0016] As a preferred example of the first aspect, based on the actual data and the photovoltaic meter data, it is determined whether there is any type of power theft abnormality in the line connected to the photovoltaic meter; wherein, the power theft abnormalities include: voltage power theft abnormality, current power theft abnormality, and power power theft abnormality; including:

[0017] The actual data includes an actual current data set, and the photovoltaic meter data includes a displayed current data set;

[0018] Subtract the actual current corresponding to each time point in the actual current dataset from the display current corresponding to each time point in the display current dataset to obtain the current data difference corresponding to each time point;

[0019] Take the ratio of the current data difference corresponding to each time point to the actual current corresponding to each time point as the judgment value, and sort all the judgment values in chronological order to form a current judgment value set;

[0020] Traverse each judgment value in the current judgment value set in chronological order. If the continuous second preset judgment times are greater than the second preset threshold, it is judged that there is the current electricity theft anomaly; otherwise, it is judged that there is no such current electricity theft anomaly.

[0021] As a preferred example of the first aspect, based on the actual data and the photovoltaic meter data, determine whether there is any type of electricity theft anomaly in the line connected to the photovoltaic meter; wherein, the electricity theft anomalies include: voltage electricity theft anomaly, current electricity theft anomaly and power electricity theft anomaly; including:

[0022] The actual data includes a light intensity dataset, and the photovoltaic meter data includes a display power dataset;

[0023] Match the light intensity corresponding to each time point in the light intensity dataset with the display power corresponding to each time point in the display power dataset to obtain the display power and light intensity corresponding to each time point; wherein, the display power corresponding to each time point has a power change amount, and the light intensity corresponding to each time point has a light intensity change amount, and the power change amount and the light intensity change amount are obtained through a preset calculation method;

[0024] Based on the display power and light intensity corresponding to each time point, determine whether there is a power electricity theft anomaly. As a preferred example of the first aspect, the determination of whether there is electricity theft based on the display power and light intensity corresponding to each time point includes:

[0025] For the display power and light intensity corresponding to any time point:

[0026] If the light intensity belongs to a preset time period and the display power is greater than a preset power threshold, it is judged that there is the power electricity theft anomaly;

[0027] If the light intensity is less than a third preset threshold and the display power is greater than a fourth preset threshold, it is judged that there is the power electricity theft anomaly;

[0028] If the ratio of the change in light intensity corresponding to the light intensity to the change in power corresponding to the display power is greater than a third preset threshold, it is determined that there is abnormal power theft;

[0029] Otherwise, there is no such abnormal power theft.

[0030] In this preferred example, by analyzing the relationship between the display power and the light intensity, abnormal power generation behaviors under low light conditions such as at night can be captured; secondly, through the reverse change detection of the decrease in light intensity and the increase in power, power theft behaviors that change the power through methods such as modifying the mains connection can be discovered; finally, through the ratio analysis of the change in power and the change in light, power theft behaviors that change the power measurement logic through methods such as modifying the mains connection are identified from the level of dynamic response characteristics, improving the accuracy of power theft behavior identification.

[0031] In a second aspect, an embodiment of the present application further provides a distributed photovoltaic power theft identification system, including: a data acquisition module, a judgment module, and an alarm module;

[0032] The data acquisition module is used to obtain actual data through a three-phase data collector and a light collector, and obtain photovoltaic meter data through a photovoltaic meter; wherein, three split-core current transformers of the three-phase data collector are sequentially clamped at the corresponding phase current inlets of the photovoltaic meter, and the three-phase voltage lines of the three-phase data collector are connected in parallel to the voltage lines of the photovoltaic meter;

[0033] The judgment module is used to judge whether there is any type of power theft abnormality in the line connected to the photovoltaic meter based on the actual data and the photovoltaic meter data; wherein, the power theft abnormality includes: voltage power theft abnormality, current power theft abnormality, and power power theft abnormality;

[0034] The alarm module is used to send corresponding alarm information to the user when it is determined that there is any type of power theft abnormality.

[0035] As a preferred example of the second aspect, the judgment module includes: a first calculation unit, a first ratio unit, and a first judgment unit;

[0036] The actual data includes an actual voltage data set, and the photovoltaic meter data includes a display voltage data set

[0037] The first calculation unit is used to subtract the actual voltage corresponding to each time point in the actual voltage data set from the display voltage corresponding to each time point in the display voltage data set to obtain the voltage data difference corresponding to each time point;

[0038] The first ratio unit is configured to use the ratio of the voltage data difference corresponding to each time point to the actual voltage corresponding to each time point as a judgment value, and sort all the judgment values in chronological order to form a voltage judgment value set;

[0039] The first judgment unit is configured to sequentially traverse each judgment value in the voltage judgment value set in chronological order. If the consecutive first preset judgment times are greater than the first preset threshold, it is judged that there is the voltage power theft anomaly; otherwise, it is judged that there is no such voltage power theft anomaly.

[0040] As a preferred example of the second aspect, the judgment module further includes: a second calculation unit, a second ratio unit, and a second judgment unit;

[0041] The second calculation unit is configured to subtract the actual current corresponding to each time point in the actual current data set from the displayed current corresponding to each time point in the displayed current data set to obtain the current data difference corresponding to each time point;

[0042] The second ratio unit is configured to use the ratio of the current data difference corresponding to each time point to the actual current corresponding to each time point as a judgment value, and sort all the judgment values in chronological order to form a current judgment value set;

[0043] The second judgment unit is configured to sequentially traverse each judgment value in the current judgment value set in chronological order. If the consecutive second preset judgment times are greater than the second preset threshold, it is judged that there is the current power theft anomaly; otherwise, it is judged that there is no such current power theft anomaly.

[0044] As a preferred example of the second aspect, the judgment module further includes: a matching unit and a judgment unit;

[0045] The actual data includes a light intensity data set, and the photovoltaic electricity meter data includes a displayed power data set;

[0046] The matching unit is configured to match the light intensity corresponding to each time point in the light intensity data set with the displayed power corresponding to each time point in the displayed power data set to obtain the displayed power and light intensity corresponding to each time point; wherein, the displayed power corresponding to each time point has a power change amount, and the light intensity corresponding to each time point has a light intensity change amount, and the power change amount and the light intensity change amount are obtained through a preset calculation method;

[0047] The judgment unit is configured to judge whether there is a power theft anomaly based on the displayed power and light intensity corresponding to each time point.

[0048] In summary, through multi-dimensional data collection and comparative analysis, the embodiments of the present application effectively improve the ability to identify distributed photovoltaic electricity theft behavior. Specifically, by comparing the photovoltaic electricity meter data with the actual monitoring data, the present application can dynamically identify three typical electricity theft behaviors: abnormal voltage loop, abnormal current loop, and abnormal photovoltaic power. The comparison of voltage data can detect the virtual voltage increment caused by the boost device, the comparison of current data can find the current deviation caused by the current boosting device, and the correlation analysis of light intensity and power generation can expose false power generation behaviors such as connecting to the mains instead of the photovoltaic power generation or photovoltaic simulation. The method of the present application breaks through the limitations of single-dimensional monitoring and significantly enhances the comprehensiveness and accuracy of electricity theft identification.

[0049] In a third aspect, the present application also provides a distributed photovoltaic electricity theft identification device, which is used to implement the distributed photovoltaic electricity theft identification method described in the present application. The distributed photovoltaic electricity theft identification device includes:

[0050] A monitoring host, the photovoltaic electricity meter, the three-phase data collector, the light collector, the solar panel, and the grid busbar;

[0051] The photovoltaic electricity meter and the monitoring host are directly connected to the grid busbar, and the monitoring host and the photovoltaic electricity meter are connected by a bus.

[0052] The three-phase data collector is connected to the grid busbar through the photovoltaic electricity meter, and the monitoring host and the three-phase data collector are connected by a bus.

[0053] The light collector is installed on the solar panel and is connected to the monitoring host by wireless communication. Description of the Drawings

[0054] In order to more clearly illustrate the technical solutions of the present application, the drawings required for implementation will be briefly introduced below. Obviously, the drawings in the following description are only some embodiments of the present application. For those of ordinary skill in the art, other drawings can be obtained based on these drawings without creative efforts.

[0055] Figure 1 is a flowchart of a distributed photovoltaic electricity theft identification method provided by some embodiments of the present application;

[0056] Figure 2 is a voltage anomaly alarm data diagram of a distributed photovoltaic electricity theft identification method provided by some embodiments of the present application;

[0057] Figure 3 is a current anomaly alarm data diagram of a distributed photovoltaic electricity theft identification method provided by some embodiments of the present application;

[0058] Figure 4 It is a power anomaly alarm data diagram of a distributed photovoltaic power theft identification method provided by some embodiments of the present application;

[0059] Figure 5 It is a schematic structural diagram of a distributed photovoltaic power theft identification device provided by some embodiments of the present application;

[0060] Figure 6 It is a schematic structural diagram of a distributed photovoltaic power theft identification system provided by some embodiments of the present application. Detailed implementation manners

[0061] To make the objectives, technical solutions, and advantages of the present application clearer, the technical solutions in the present application will be clearly and completely described below in conjunction with the accompanying drawings in the embodiments of the present application. Obviously, the described embodiments are some, but not all, of the embodiments of the present application. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present application without making creative efforts fall within the scope of protection of the present application.

[0062] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by those of ordinary skill in the technical field to which this application belongs; the terms used herein are only for the purpose of describing specific embodiments and are not intended to limit this application; the terms "including" and "having" and any variations thereof in the specification and claims of this application and the above drawings are intended to cover non-exclusive inclusion.

[0063] In the description of the embodiments of the present application, technical terms such as "first" and "second" are only used to distinguish different objects and cannot be understood as indicating or implying relative importance or implicitly indicating the quantity, specific order, or primary-secondary relationship of the indicated technical features. In the description of the embodiments of the present application, "a plurality of" means two or more unless otherwise specifically defined.

[0064] Referring to "embodiments" herein means that a specific feature, structure, or characteristic described in connection with the embodiments can be included in at least one embodiment of the present application. The phrase appears in various places in the specification and does not necessarily refer to the same embodiment, nor is it an independent or alternative embodiment mutually exclusive with other embodiments. Those skilled in the art explicitly and implicitly understand that the embodiments described herein can be combined with other embodiments.

[0065] In the description of the embodiments of the present application, the term "and / or" is merely an association relationship describing associated objects, indicating that there can be three relationships. For example, A and / or B can mean: A exists alone, A and B exist simultaneously, and B exists alone. In addition, the character " / " in this article generally indicates that the associated objects before and after are in an "or" relationship.

[0066] In the description of the embodiments of the present application, the term "plurality" refers to two or more (including two). Similarly, "multiple groups" refers to two or more groups (including two groups), and "multiple pieces" refers to two or more pieces (including two pieces).

[0067] In the description of the embodiments of the present application, unless otherwise clearly specified and limited, technical terms such as "installation", "connection", "connection", "fixation", etc. should be understood in a broad sense. For example, it can be a fixed connection, a detachable connection, or integrated; it can also be a mechanical connection or an electrical connection; it can be directly connected or indirectly connected through an intermediate medium, and it can be the communication inside two components or the interaction relationship between two components. For those of ordinary skill in the art, the specific meanings of the above terms in the embodiments of the present application can be understood according to specific situations.

[0068] With the continuous rise of the distributed energy photovoltaic power generation industry, some illegal users use various methods such as boosting method, current boosting method, and mains power conversion method to pose as photovoltaic power generation, illegally defrauding subsidies for profit. In addition, new high-tech electricity theft methods such as injecting DC electricity theft, rectifier electricity theft, and replacing sampling resistors inside the meter through the metering circuit are increasing day by day, and conventional inspection means are difficult to detect. Based on the electrical energy calculation formula W = Pt = UIt, where P is power, under the condition that the phase angle is determined, P is equal to the product of voltage U and current I. Different from ordinary electricity theft, distributed photovoltaic electricity theft users try to artificially increase the electrical energy measurement value. According to the formula, changing the voltage U or current I can affect the electrical energy measurement. Therefore, there are the following several typical electricity theft methods:

[0069] (1) Boosting method

[0070] The principle is an illegal process of introducing a boosting device into the circuit to generate virtual voltage and finally obtaining government compensation by boosting the electrical energy of the meter. Illegal users usually target both ends of the gateway metering device and deliberately increase the voltage difference on both sides, thereby increasing the meter reading of the electricity meter and making the gateway meter show a higher electricity measurement value.

[0071] (2) Current boosting method

[0072] The principle is to illegally adjust the line voltage using a voltage regulator. By attaching a smaller voltage value to the primary side, a corresponding increased current value can be obtained on the secondary side, thereby reducing the measurement of the mains electricity. Illegal users usually adjust the ratio of voltage and current to achieve the effect of reducing the meter reading.

[0073] (3) Mains power connection method

[0074] The principle is that electricity users control the electricity metering by adjusting the wiring in the system, and by comparing the load power consumption with the photovoltaic power generation power, when the load power is higher than the photovoltaic power generation power, they try to transmit the electricity to the gateway meter in an alternating manner, illegally confusing the photovoltaic power supply power with the city power generation, and make the current flowing through the gateway metering equipment higher by rewiring, creating the illusion of photovoltaic power generation in order to defraud electricity subsidies. Illegal users usually change the distribution wiring to make the meter malfunction, and increase the meter current by rewiring the line to achieve the purpose of stealing electricity.

[0075] (4) Photovoltaic simulation method

[0076] Photovoltaic simulation method of stealing electricity users directly use power electronic rectifiers to rectify the city power into DC, connect it in parallel to the DC side of the photovoltaic power generation system, and convert it into AC power through the photovoltaic inverter to connect to the grid. Using this method of stealing electricity, users do not even need to install photovoltaic panels, and can directly use rectifiers to impersonate photovoltaic panels. Illegal users usually use DC signals to connect to the DC side of the photovoltaic power generation system to falsely increase power generation.

[0077] In order to solve the above problems, the technical solutions in the embodiments of the present application will be clearly and completely described below in conjunction with the drawings in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of this application.

[0078] Embodiment 1

[0079] See also Figure 1 In order to solve the problem that it is difficult to accurately identify distributed photovoltaic power theft in the prior art, an embodiment of the present invention provides a distributed photovoltaic power theft identification method, including:

[0080] S1, obtaining actual data through a three-phase data collector and a light collector, and obtaining photovoltaic meter data through a photovoltaic meter; wherein the three open-type current transformers of the three-phase data collector are clamped in sequence at the phase current input lines corresponding to the photovoltaic meter, and the three-phase voltage lines of the three-phase data collector are connected in parallel to the voltage lines of the photovoltaic meter;

[0081] Specifically, the three split-core current transformers of the three-phase data collector are clamped in sequence at the corresponding phase current inlet of the photovoltaic meter. The three-phase voltage lines are connected in parallel to the voltage lines of the photovoltaic meter and are connected in parallel to the device host through the RS485 port to collect and store voltage and current data in real time, and calculate real-time electric energy in combination with the phase angle collector. The illuminance collector is installed at the solar panel and transmits the illuminance intensity to the host through LoRa long-distance wireless communication.

[0082] S2. Based on the actual data and the photovoltaic meter data, determine whether there is any type of electricity theft anomaly in the line connected to the photovoltaic meter; wherein, the electricity theft anomalies include: voltage electricity theft anomaly, current electricity theft anomaly, and power electricity theft anomaly;

[0083] Further, in some embodiments of the present application, the determining whether there is any type of electricity theft anomaly in the line connected to the photovoltaic meter based on the actual data and the photovoltaic meter data; wherein, the electricity theft anomalies include: voltage electricity theft anomaly, current electricity theft anomaly, and power electricity theft anomaly; includes:

[0084] The actual data includes an actual voltage data set, and the photovoltaic meter data includes a displayed voltage data set;

[0085] Subtract the actual voltage corresponding to each time point in the actual voltage data set from the displayed voltage corresponding to each time point in the displayed voltage data set to obtain the voltage data difference corresponding to each time point;

[0086] Take the ratio of the voltage data difference corresponding to each time point to the actual voltage corresponding to each time point as a judgment value, and sort all judgment values in chronological order to form a voltage judgment value set;

[0087] Traverse each judgment value in the voltage judgment value set in chronological order. If the continuous first preset judgment times are greater than the first preset threshold, it is determined that there is the voltage electricity theft anomaly, otherwise it is determined that there is no such voltage electricity theft anomaly.

[0088] Specifically, as Figure 2 shown, it is a data graph of voltage anomaly alarm. The first preset judgment times can be 3 times, and the first preset threshold is an allowable deviation threshold value set according to historical data experience to avoid normal fluctuations and can be set to 5%. When it is determined as voltage electricity theft, the alarm event is stored in the host, and the alarm report can be retrieved by the tablet computer or the remote master station.

[0089] Further, in some embodiments of the present application, the determining whether there is any type of electricity theft anomaly in the line connected to the photovoltaic meter based on the actual data and the photovoltaic meter data; wherein, the electricity theft anomalies include: voltage electricity theft anomaly, current electricity theft anomaly, and power electricity theft anomaly; includes:

[0090] The actual data includes an actual current data set, and the photovoltaic electricity meter data includes a displayed current data set;

[0091] Subtract the actual current corresponding to each time point in the actual current data set from the displayed current corresponding to each time point in the displayed current data set to obtain the current data difference corresponding to each time point;

[0092] Take the ratio of the current data difference corresponding to each time point to the actual current corresponding to each time point as a judgment value, and sort all the judgment values in chronological order to form a current judgment value set;

[0093] Traverse each judgment value in the current judgment value set in chronological order. If the continuous second preset judgment times is greater than the second preset threshold, it is judged that there is the current electricity theft anomaly; otherwise, it is judged that there is no such current electricity theft anomaly.

[0094] Specifically, as Figure 3 shown, it is a data graph of current anomaly alarm. The first preset judgment times can be 4 times, and the first preset threshold is an allowable deviation threshold value set according to historical data experience to avoid normal fluctuations, which can be set to 5%. When it is judged as current electricity theft, store the alarm event in the host, and the alarm report can be retrieved by the tablet computer or the remote master station.

[0095] Further, in some embodiments of the present application, based on the actual data and the photovoltaic electricity meter data, it is judged whether there is any type of electricity theft anomaly in the line connected to the photovoltaic electricity meter; wherein, the electricity theft anomaly includes: voltage electricity theft anomaly, current electricity theft anomaly and power electricity theft anomaly; including:

[0096] The actual data includes a light intensity data set, and the photovoltaic electricity meter data includes a displayed power data set;

[0097] Match the light intensity corresponding to each time point in the light intensity data set with the displayed power corresponding to each time point in the displayed power data set to obtain the displayed power and the light intensity corresponding to each time point; wherein, the displayed power corresponding to each time point has a power change amount, and the light intensity corresponding to each time point has a light intensity change amount, and the power change amount and the light intensity change amount are obtained through a preset calculation method;

[0098] Based on the displayed power and the light intensity corresponding to each time point, judge whether there is a power electricity theft anomaly.

[0099] Further, in some embodiments of the present application, the judging whether there is electricity theft based on the displayed power and the light intensity corresponding to each time point includes:

[0100] For the display power and light intensity corresponding to any time point:

[0101] If the light intensity belongs to a preset time period and the display power is greater than a preset power threshold, it is determined that there is an abnormal power theft;

[0102] If the light intensity is less than a third preset threshold and the display power is greater than a fourth preset threshold, it is determined that there is an abnormal power theft;

[0103] If the ratio of the change amount of the light intensity corresponding to the light intensity to the change amount of the power corresponding to the display power is greater than a third preset threshold, it is determined that there is an abnormal power theft;

[0104] Otherwise, there is no abnormal power theft.

[0105] Specifically, as Figure 4 shown, it is a data graph of power anomaly alarm. The preset time period can be the night time period, and the preset power threshold can be 10% of the set rated power of the photovoltaic. When it is determined as power theft, the alarm event is stored in the host, and the alarm report can be retrieved by a tablet computer or a remote master station.

[0106] S3. When it is determined that there is any type of abnormal power theft, send a corresponding alarm message to the user.

[0107] In summary, the embodiments of the present application effectively improve the recognition ability of distributed photovoltaic power theft behaviors through multi-dimensional data acquisition and comparative analysis. Specifically, the present application compares the photovoltaic meter data with the actual monitoring data to dynamically identify three typical power theft behaviors: abnormal voltage circuit, abnormal current circuit, and abnormal photovoltaic power. The comparison of voltage data can detect the virtual voltage increment caused by the booster device, the comparison of current data can find the current deviation caused by the current boosting device, and the correlation analysis of light intensity and power generation power can expose false power generation behaviors such as changing the mains power connection or photovoltaic simulation. The method of the present application breaks through the limitations of single-dimensional monitoring and significantly enhances the comprehensiveness and accuracy of power theft recognition.

[0108] Embodiment 2

[0109] As Figure 5 shown, on the basis of the above method item embodiments, corresponding system item embodiments are provided;

[0110] An embodiment of the present invention provides a distributed photovoltaic power theft recognition system, including: a data acquisition module 11, a judgment module 12, and an alarm module 13;

[0111] Further, in some embodiments of the present application, the data acquisition module 11 is configured to acquire actual data through a three-phase data collector and a light collector, and acquire photovoltaic meter data through a photovoltaic meter; wherein, three split-core current transformers of the three-phase data collector are sequentially clamped at the corresponding phase current inlets of the photovoltaic meter, and three-phase voltage lines of the three-phase data collector are connected in parallel to the voltage lines of the photovoltaic meter; the judgment module 12 is configured to judge whether there is any type of power theft anomaly in the line connected to the photovoltaic meter based on the actual data and the photovoltaic meter data; wherein, the power theft anomalies include: voltage power theft anomaly, current power theft anomaly, and power power theft anomaly; the alarm module 13 is configured to send a corresponding alarm message to the user when it is determined that there is any type of power theft anomaly.

[0112] Further, in some embodiments of the present application, the judgment module 12 includes: a first calculation unit, a first ratio unit, and a first judgment unit; the actual data includes an actual voltage data set, and the photovoltaic meter data includes a displayed voltage data set; the first calculation unit is configured to subtract the actual voltage corresponding to each time point in the actual voltage data set from the displayed voltage corresponding to each time point in the displayed voltage data set to obtain a voltage data difference corresponding to each time point; the first ratio unit is configured to use the ratio of the voltage data difference corresponding to each time point to the actual voltage corresponding to each time point as a judgment value, and sort all judgment values in chronological order to form a voltage judgment value set; the first judgment unit is configured to sequentially traverse each judgment value in the voltage judgment value set in chronological order, and if the continuous first preset judgment times are greater than the first preset threshold, judge that there is the voltage power theft anomaly, otherwise judge that there is no such voltage power theft anomaly.

[0113] Further, in some embodiments of the present application, the judgment module 12 further includes: a second calculation unit, a second ratio unit, and a second judgment unit; the actual data includes an actual current data set, and the photovoltaic meter data includes a displayed current data set; the second calculation unit is configured to subtract the actual current corresponding to each time point in the actual current data set from the displayed current corresponding to each time point in the displayed current data set to obtain a current data difference corresponding to each time point; the second ratio unit is configured to use the ratio of the current data difference corresponding to each time point to the actual current corresponding to each time point as a judgment value, and sort all judgment values in chronological order to form a current judgment value set; the second judgment unit is configured to sequentially traverse each judgment value in the current judgment value set in chronological order, and if the continuous second preset judgment times are greater than the second preset threshold, judge that there is the current power theft anomaly, otherwise judge that there is no such current power theft anomaly.

[0114] Further, in some embodiments of the present application, the determination module 12 further includes: a matching unit and a determination unit; the actual data includes a light intensity data set, and the photovoltaic electricity meter data includes a displayed power data set; the matching unit is configured to match the light intensity corresponding to each time point in the light intensity data set with the displayed power corresponding to each time point in the displayed power data set to obtain the displayed power and the light intensity corresponding to each time point; wherein, a power change amount corresponds to the displayed power corresponding to each time point, and a light intensity change amount corresponds to the light intensity corresponding to each time point, and the power change amount and the light intensity change amount are obtained by a preset calculation method; the determination unit is configured to determine whether there is an abnormal power theft based on the displayed power and the light intensity corresponding to each time point.

[0115] It can be understood that the above system item embodiments correspond to the method item embodiments of the present invention, and can implement the distributed photovoltaic power theft identification method provided by any one of the above method item embodiments of the present invention.

[0116] It should be noted that the device embodiments described above are merely illustrative, and some or all of the modules can be selected according to actual needs to achieve the purpose of the solution of this embodiment. In addition, in the attached drawings of the device embodiments provided by the present invention, the connection relationship between the modules indicates that there is a communication connection between them, which can be specifically implemented as one or more communication buses or signal lines. Those of ordinary skill in the art can understand and implement without creative work.

[0117] In summary, the embodiments of the present application effectively improve the identification ability of distributed photovoltaic power theft behaviors through multi-dimensional data collection and comparative analysis. Specifically, by comparing the photovoltaic electricity meter data with the actual monitoring data, the present application can dynamically identify three typical power theft behaviors: abnormal voltage loop, abnormal current loop, and abnormal photovoltaic power. The comparison of voltage data can detect the virtual voltage increment caused by the booster device, the comparison of current data can find the current deviation caused by the current boosting device, and the correlation analysis of light intensity and power generation can expose false power generation behaviors such as mains power conversion or photovoltaic simulation. The method of the present application breaks through the limitations of single-dimensional monitoring and significantly enhances the comprehensiveness and accuracy of power theft identification.

[0118] Embodiment III

[0119] As Figure 6 shown, based on the above method item embodiments, corresponding entity device item embodiments are provided;

[0120] An embodiment of the present invention provides a distributed photovoltaic power theft identification device, which is used to implement a distributed photovoltaic power theft identification method according to any one of the present invention. The distributed photovoltaic power theft identification device includes:

[0121] The host, the photovoltaic electricity meter, the three-phase data collector, the light collector, the solar panel and the grid busbar;

[0122] The photovoltaic electricity meter and the monitoring host are connected to the grid busbar, and the monitoring host is connected to the photovoltaic electricity meter through a bus;

[0123] The three-phase data collector is connected to the grid busbar through the photovoltaic electricity meter, and the monitoring host is connected to the three-phase data collector through a bus;

[0124] The light collector is installed on the solar panel and is connected to the monitoring host by wireless communication.

[0125] Specifically, the three open-type current transformers of the three-phase data collector are sequentially clamped at the corresponding phase current inlet of the photovoltaic meter, the three-phase voltage lines are connected in parallel to the voltage lines of the photovoltaic meter, and are connected in parallel with the device host through the RS485 port to collect and store voltage and current data in real time, and calculate the real-time electric energy in combination with the phase angle collector. The illuminance collector is installed at the solar panel and transmits the illuminance intensity to the host through LoRa long-distance wireless communication.

[0126] The above is the preferred embodiment of the present invention. It should be noted that for those of ordinary skill in the art, without departing from the principle of the present invention, several improvements and modifications can be made, and these improvements and modifications are also regarded as the protection scope of the present invention.

Claims

1. A distributed photovoltaic electricity theft identification method, characterized in that, Including: Obtain actual data through a three-phase data collector and a light collector, and obtain photovoltaic meter data through a photovoltaic meter; wherein, three split-core current transformers of the three-phase data collector are clamped in sequence at the corresponding phase current inlets of the photovoltaic meter, and the three-phase voltage lines of the three-phase data collector are connected in parallel to the voltage lines of the photovoltaic meter; Based on the actual data and the photovoltaic meter data, determine whether there is any type of electricity theft anomaly in the line connected to the photovoltaic meter; wherein, the electricity theft anomalies include: voltage electricity theft anomaly, current electricity theft anomaly, and power electricity theft anomaly; When it is determined that there is any type of electricity theft anomaly, send a corresponding warning message to the user.

2. The distributed photovoltaic electricity theft identification method according to claim 1, characterized in that, The step of determining whether there is any type of electricity theft anomaly in the line connected to the photovoltaic meter based on the actual data and the photovoltaic meter data; wherein, the electricity theft anomalies include: voltage electricity theft anomaly, current electricity theft anomaly, and power electricity theft anomaly; includes: The actual data includes an actual voltage data set, and the photovoltaic meter data includes a displayed voltage data set; Subtract the actual voltage corresponding to each time point in the actual voltage data set from the displayed voltage corresponding to each time point in the displayed voltage data set to obtain the voltage data difference corresponding to each time point; Use the ratio of the voltage data difference corresponding to each time point to the actual voltage corresponding to each time point as a judgment value, and sort all the judgment values in chronological order to form a voltage judgment value set; Traverse each judgment value in the voltage judgment value set in chronological order. If the continuous first preset judgment times are greater than the first preset threshold, it is determined that there is the voltage electricity theft anomaly; otherwise, it is determined that there is no such voltage electricity theft anomaly.

3. The distributed photovoltaic electricity theft identification method according to claim 1, characterized in that, The step of determining whether there is any type of electricity theft anomaly in the line connected to the photovoltaic meter based on the actual data and the photovoltaic meter data; wherein, the electricity theft anomalies include: voltage electricity theft anomaly, current electricity theft anomaly, and power electricity theft anomaly; includes: The actual data includes an actual current data set, and the photovoltaic meter data includes a displayed current data set; Subtract the actual current corresponding to each time point in the actual current data set from the displayed current corresponding to each time point in the displayed current data set to obtain the current data difference corresponding to each time point; Use the ratio of the current data difference corresponding to each time point to the actual current corresponding to each time point as a judgment value, and sort all the judgment values in chronological order to form a current judgment value set; Traverse each judgment value in the current judgment value set in chronological order. If the continuous second preset judgment times are greater than the second preset threshold, it is determined that there is the current electricity theft anomaly; otherwise, it is determined that there is no such current electricity theft anomaly.

4. The distributed photovoltaic power theft identification method according to claim 1, characterized in that The step of determining whether there is any type of electricity theft anomaly in the line connected to the photovoltaic meter based on the actual data and the photovoltaic meter data; wherein, the electricity theft anomalies include: voltage electricity theft anomaly, current electricity theft anomaly, and power electricity theft anomaly; includes: The actual data includes a light intensity data set, and the photovoltaic meter data includes a displayed power data set; Match the light intensity corresponding to each time point in the light intensity dataset with the display power corresponding to each time point in the display power dataset to obtain the display power and light intensity corresponding to each time point; wherein, there is a power change amount corresponding to the display power corresponding to each time point, and there is a light intensity change amount corresponding to the light intensity corresponding to each time point, and the power change amount and the light intensity change amount are obtained through a preset calculation method; Based on the display power and light intensity corresponding to each time point, determine whether there is an abnormal power theft.

5. The distributed photovoltaic power theft identification method according to claim 4, wherein The determination of whether there is power theft based on the display power and light intensity corresponding to each time point includes: For the display power and light intensity corresponding to any time point: If the light intensity belongs to a preset time period and the display power is greater than a preset power threshold, it is determined that there is an abnormal power theft; If the light intensity is less than a third preset threshold and the display power is greater than a fourth preset threshold, it is determined that there is an abnormal power theft; If the ratio of the light intensity change amount corresponding to the light intensity to the power change amount corresponding to the display power is greater than a third preset threshold, it is determined that there is an abnormal power theft; Otherwise, there is no abnormal power theft.

6. A distributed photovoltaic power theft identification system, characterized in that It includes: A data acquisition module, a judgment module, and an alarm module; The data acquisition module is used to obtain actual data through a three-phase data collector and a light collector, and obtain photovoltaic meter data through a photovoltaic meter; wherein, the three split-core current transformers of the three-phase data collector are clamped in sequence at the corresponding phase current inlets of the photovoltaic meter, and the three-phase voltage lines of the three-phase data collector are connected in parallel to the voltage lines of the photovoltaic meter; The judgment module is used to judge whether there is any type of abnormal power theft in the line connected to the photovoltaic meter based on the actual data and the photovoltaic meter data; wherein, the abnormal power theft includes: voltage abnormal power theft, current abnormal power theft, and power abnormal power theft; The alarm module is used to send a corresponding alarm message to the user when it is determined that there is any type of abnormal power theft.

7. The distributed photovoltaic power theft identification system according to claim 6, characterized in that, The judgment module includes: a first calculation unit, a first ratio unit, and a first judgment unit; The actual data includes an actual voltage dataset, and the photovoltaic meter data includes a display voltage dataset; The first calculation unit is used to subtract the actual voltage corresponding to each time point in the actual voltage dataset from the display voltage corresponding to each time point in the display voltage dataset to obtain the voltage data difference corresponding to each time point; The first ratio unit is used to use the ratio of the voltage data difference corresponding to each time point to the actual voltage corresponding to each time point as a judgment value, and sort all judgment values in chronological order to form a voltage judgment value set; The first judgment unit is used to sequentially traverse each judgment value in the voltage judgment value set in chronological order. If the continuous first preset judgment times are greater than the first preset threshold, it is judged that there is an abnormal voltage theft, otherwise it is judged that there is no abnormal voltage theft.

8. The distributed photovoltaic electricity theft identification system according to claim 6, wherein, The judgment module further includes: a second calculation unit, a second ratio unit, and a second judgment unit; The actual data includes an actual current data set, and the photovoltaic meter data includes a displayed current data set; The second calculation unit is configured to subtract the actual current corresponding to each time point in the actual current data set from the displayed current corresponding to each time point in the displayed current data set, to obtain a current data difference corresponding to each time point; The second ratio unit is configured to use the ratio of the current data difference corresponding to each time point to the actual current corresponding to each time point as a judgment value, and sort all the judgment values in chronological order to form a current judgment value set; The second judgment unit is configured to sequentially traverse each judgment value in the current judgment value set in chronological order. If the continuous second preset judgment times is greater than the second preset threshold, it is determined that there is the current power theft anomaly; otherwise, it is determined that there is no such current power theft anomaly.

9. The distributed photovoltaic power theft identification system according to claim 6, characterized in that, The judgment module further includes: a matching unit and a judgment unit; The actual data includes an illumination intensity data set, and the photovoltaic meter data includes a displayed power data set; The matching unit is configured to match the illumination intensity corresponding to each time point in the illumination intensity data set with the displayed power corresponding to each time point in the displayed power data set, to obtain the displayed power and the illumination intensity corresponding to each time point; wherein, a power change amount corresponds to the displayed power corresponding to each time point, and an illumination intensity change amount corresponds to the illumination intensity corresponding to each time point, and the power change amount and the illumination intensity change amount are obtained by a preset calculation method; The judgment unit is configured to judge whether there is a power theft anomaly based on the displayed power and the illumination intensity corresponding to each time point.

10. A distributed photovoltaic power theft identification device, characterized in that, The distributed photovoltaic power theft identification device is used to implement a distributed photovoltaic power theft identification method according to any one of claims 1-5. The distributed photovoltaic power theft identification device includes: A monitoring host, the photovoltaic meter, the three-phase data collector, the illumination collector, a solar panel, and a grid busbar; The photovoltaic meter and the monitoring host are connected to the grid busbar, and the monitoring host is connected to the photovoltaic meter through a bus; The three-phase data collector is connected to the grid busbar through the photovoltaic meter, and the monitoring host is connected to the three-phase data collector through a bus; The illumination collector is installed on the solar panel and is connected to the monitoring host through a wireless communication method.

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