Photovoltaic power consumption simulation and testing systems, methods, equipment and storage media

Abstract

This invention relates to the field of photovoltaic power consumption detection technology, and discloses a photovoltaic power consumption simulation and detection system, method, equipment, and storage medium. The system includes: an abnormal power consumption mode generator that simulates and generates current signals for abnormal power consumption; a solar thermal irradiance simulator that simulates and generates solar thermal irradiance data under different weather conditions and / or time periods; a smart meter data acquisition unit that collects current signals and solar thermal irradiance data; a power anomaly simulator that acts on a simulated inverter, causing a sudden change in output power; an inverter power data monitoring unit that collects power parameters; and an abnormal mode detection unit that comprehensively analyzes whether abnormal power consumption has occurred based on the current signals and solar thermal irradiance data, as well as based on the solar thermal irradiance data and power parameters. Through the above methods, this invention can simulate the diversity and complexity of photovoltaic power consumption behavior scenarios and detect abnormal power consumption behavior on the user side, helping to effectively and accurately identify abnormal power consumption situations and reduce false alarm rates.

Description

Technical Field

[0001] The embodiments of the present invention relate to the field of photovoltaic power consumption detection technology, specifically to a photovoltaic power consumption simulation and detection system, method, equipment and storage medium. Background Technology

[0002] Distributed photovoltaic (PV) power generation systems are becoming increasingly widespread in households. However, in practice, there are instances of other users illegally connecting to loads or stealing electricity, which not only affects the standardization of power grid management but may also lead to safety hazards for the PV system.

[0003] Existing photovoltaic (PV) power generation monitoring systems primarily focus on equipment fault diagnosis and power generation efficiency monitoring, with limited ability to detect abnormal electricity consumption behavior on the user side. Traditional abnormal electricity consumption detection methods rely on empirical rules or simple statistical models. For example, judging abnormal situations based on single electricity consumption data recorded by smart meters is difficult to adapt to the diversity and complexity of PV electricity consumption behavior. They cannot accurately identify abnormal electricity consumption behavior on the user side, nor can they accurately determine whether power changes are caused by natural factors or human intervention. Especially under conditions of no sunlight at night or sudden changes in daylight intensity, traditional monitoring systems struggle to effectively identify abnormal electricity consumption behavior, resulting in low detection accuracy and high false alarm rates. Summary of the Invention

[0004] In view of the above problems, embodiments of the present invention provide a photovoltaic power consumption simulation and testing system, method, device and storage medium to solve the problems existing in the prior art.

[0005] According to one aspect of the present invention, a photovoltaic power consumption simulation and detection system is provided, the system comprising an abnormal power consumption mode generator, a solar thermal irradiation simulator, a smart meter data acquisition unit, a simulated inverter, a power anomaly simulator, an inverter power data monitoring unit, and an abnormal mode detection unit;

[0006] The abnormal power consumption mode generator is used to simulate and generate abnormal power consumption current signals based on pre-configured current parameters.

[0007] The solar thermal irradiance simulator is used to simulate and generate solar thermal irradiance data under different weather conditions and / or time periods based on pre-configured solar thermal irradiance parameters. The solar thermal irradiance data includes irradiance and irradiance curves.

[0008] The smart meter data acquisition unit is used to acquire the current signal of the abnormal electricity consumption mode generator and the photothermal irradiation data of the photothermal irradiation simulator.

[0009] The simulated inverter is used to convert AC power to DC power, and the AC power is simulated based on the photothermal irradiation data;

[0010] The power anomaly simulator is used to apply a preset interference mechanism to the simulated inverter under the condition that the irradiance is stable, so that the output power of the simulated inverter will suddenly change.

[0011] The inverter power data monitoring unit is used to monitor and collect the power parameters output by the analog inverter.

[0012] The abnormal mode detection unit is used to comprehensively analyze whether an abnormal power consumption situation has occurred based on the current signal and the photothermal irradiation data, as well as based on the photothermal irradiation data and the power parameters.

[0013] In one alternative embodiment, the abnormal power consumption pattern generator includes a controller and a controllable current source connected together. The controller is configured to trigger the controllable current source periodically or intermittently according to a preset time period, causing the controllable current source to generate a reverse current signal Isim(t) with a predetermined amplitude and waveform.

[0014] Isim(t)=Ibase+Asin(2πft)+ε(t),

[0015] Where Ibase is the basic reverse current value, A is the fluctuation amplitude of the current signal, f is the fluctuation frequency of the current signal, and ε(t) is the random noise component that varies with time t.

[0016] In one optional embodiment, the photothermal irradiance simulator is used to output standard photothermal irradiance data based on a preset nighttime period and a preset nighttime irradiance model, wherein the nighttime irradiance model Gnight(t) is:

[0017] Gnight(t)=Gmoon*fmoon(t)+Gambient+δ(t),

[0018] Where Gmoon is the maximum lunar irradiance, fmoon(t) is the lunar phase function with a value range of [0,1], Gambient is the ambient light irradiance, and δ(t) is a random perturbation term that varies with time t.

[0019] The photothermal irradiation simulator is also used to output photothermal irradiation data under conditions of sufficient and stable light, based on preset daytime periods.

[0020] In one optional embodiment, the abnormal mode detection unit is specifically configured to determine an abnormal power consumption situation when it detects that the irradiance is equal to zero during the nighttime period, and detects a reverse current, wherein the amplitude of the reverse current is greater than a preset amplitude for a duration greater than a preset time; and,

[0021] After the photothermal irradiation simulator outputs photothermal irradiation data under sufficient and stable light conditions, the power change rate is determined according to the power parameter, and the irradiance change rate is determined according to the irradiance.

[0022] Analyze whether the power change rate matches the irradiance change rate;

[0023] If the power change rate does not match the irradiance change rate, then an abnormal power consumption situation is determined.

[0024] In one optional embodiment, the abnormal mode detection unit is further configured to: if the power change rate does not match the irradiance change rate, determine a power deviation rate based on the power parameters, analyze whether the power deviation rate is less than a preset power deviation rate threshold, whether the duration of the power deviation rate being less than the power deviation rate threshold is greater than a preset time threshold, and whether the irradiance change rate is greater than a preset change rate threshold; if the analysis results are all yes, then determine that a power drop anomaly has occurred, and the power deviation rate threshold is negative.

[0025] In one alternative embodiment, the abnormal mode detection unit is further configured to comprehensively analyze whether an abnormal power consumption situation has occurred based on the current signal, the photothermal irradiation data, and the power parameters.

[0026] In one alternative embodiment, the system further includes an interference factor simulation unit and a performance evaluation unit, wherein the interference factor simulation unit is used to add interference factors to the system, the interference factors including at least one of power grid fluctuations, communication delays, and sensor errors;

[0027] The performance evaluation unit is used to determine the system's performance indicators based on the interference factors, including accuracy, recall, F1 score, and response time.

[0028] A test report is generated based on the aforementioned interference factors and performance indicators.

[0029] According to another aspect of the present invention, a method for simulating and detecting photovoltaic power consumption is provided. The method is performed based on the aforementioned photovoltaic power consumption simulation and detection device, and includes:

[0030] The abnormal power consumption pattern generator simulates and generates abnormal power consumption current signals based on pre-configured current parameters;

[0031] The solar thermal irradiance simulator generates solar thermal irradiance data under different weather conditions and / or time periods based on pre-configured solar thermal irradiance parameters. The solar thermal irradiance data includes irradiance and irradiance curves.

[0032] The smart meter data acquisition unit acquires the current signal from the abnormal electricity consumption pattern generator and the photothermal irradiation data from the photothermal irradiation simulator;

[0033] The simulated inverter converts AC power to DC power, and the AC power is simulated based on the photothermal irradiation data.

[0034] The power anomaly simulator, under the condition of stable irradiance, applies a preset interference mechanism to the simulated inverter, causing a sudden change in the output power of the simulated inverter;

[0035] The inverter power data monitoring unit monitors and collects the power parameters output by the analog inverter;

[0036] The abnormal mode detection unit comprehensively analyzes whether an abnormal power consumption situation has occurred based on the current signal, the photothermal irradiation data, the photothermal irradiation data, and the power parameters.

[0037] According to another aspect of the present invention, a computer device is provided, comprising: a processor, a memory, a communication interface, and a communication bus, wherein the processor, the memory, and the communication interface communicate with each other via the communication bus; the memory is used to store at least one executable instruction, wherein the executable instruction causes the processor to perform the method described above.

[0038] According to another aspect of the present invention, a computer-readable storage medium is provided, the storage medium storing at least one executable instruction, which, when executed on a computer device, causes the computer device to perform the method described above.

[0039] This invention simulates abnormal power consumption by generating current signals through an abnormal power consumption mode generator and generating solar thermal irradiance data under different weather conditions and / or time periods through a solar thermal irradiance simulator. The solar thermal irradiance data includes irradiance and irradiance curves. Under stable irradiance conditions, a power anomaly simulator acts on a simulated inverter according to a preset interference mechanism, causing a sudden change in the output power of the simulated inverter. Subsequently, the current signal and solar thermal irradiance data are collected by a smart meter data acquisition unit, and the power parameters of the simulated inverter are collected by an inverter power data monitoring unit. Finally, the abnormal mode detection unit comprehensively analyzes whether an abnormal power consumption situation has occurred based on the current signal, solar thermal irradiance data, and power parameters. This invention can simulate the diversity and complexity of photovoltaic power consumption behavior scenarios. By comprehensively analyzing the current signal, solar thermal irradiance data, and power parameters, it can detect abnormal power consumption behavior on the user side, which helps to effectively and accurately identify abnormal power consumption situations and reduce false alarm rates.

[0040] The above description is merely an overview of the technical solutions of the embodiments of the present invention. In order to better understand the technical means of the embodiments of the present invention and to implement them in accordance with the contents of the specification, and to make the above and other objects, features and advantages of the embodiments of the present invention more apparent and understandable, specific embodiments of the present invention are described below. Attached Figure Description

[0041] The accompanying drawings are for illustrative purposes only and are not intended to limit the invention. Furthermore, the same reference numerals denote the same parts throughout the drawings. In the drawings:

[0042] Figure 1 A schematic diagram of the structure of the photovoltaic power consumption simulation and detection system provided in an embodiment of the present invention is shown;

[0043] Figure 2 A flowchart illustrating the photovoltaic power consumption simulation and testing method provided in an embodiment of the present invention is shown;

[0044] Figure 3 A schematic diagram of the structure of a computer device provided in an embodiment of the present invention is shown. Detailed Implementation

[0045] Exemplary embodiments of the invention will now be described in more detail with reference to the accompanying drawings. While exemplary embodiments of the invention are shown in the drawings, it should be understood that the invention can be implemented in various forms and should not be limited to the embodiments set forth herein.

[0046] Figure 1 A schematic diagram of the structure of the photovoltaic power consumption simulation and testing system provided in an embodiment of the present invention is shown, as follows: Figure 1 As shown, the system includes an abnormal power consumption mode generator, a solar thermal irradiation simulator, a smart meter data acquisition unit, a simulated inverter, a power anomaly simulator, an inverter power data monitoring unit, and an abnormal mode detection unit. The abnormal power consumption mode generator and the solar thermal irradiation simulator are connected to the smart meter data acquisition unit. The solar thermal irradiation simulator is also connected to the simulated inverter. The simulated inverter is connected to the power anomaly simulator and the inverter power data monitoring unit. The abnormal mode detection unit is connected to the inverter power data monitoring unit and the smart meter data acquisition unit.

[0047] The abnormal power consumption pattern generator is used to simulate and generate abnormal power consumption current signals based on pre-configured current parameters. These current parameters include the direction of the current, fluctuation amplitude, duration, fluctuation frequency, and random noise components. The abnormal power consumption pattern generator generates a reverse current signal with a specific amplitude and waveform during a preset time period (e.g., nighttime 20:00-06:00) to simulate users illegally connecting loads or stealing electricity at night. Specifically, the abnormal power consumption pattern generator includes a connected controller and a controllable current source. The controller triggers the controllable current source at preset times or irregular intervals according to a preset program, causing the controllable current source to generate a reverse current signal Isim(t) with a predetermined amplitude and waveform.

[0048] Isim(t)=Ibase+Asin(2πft)+ε(t),

[0049] Wherein, Ibase is the basic reverse current value, which is a constant component; A is the fluctuation amplitude of the current signal, which can be set in the range of 0.5A-5A; the duration is adjustable; f is the fluctuation frequency of the current signal; and ε(t) is the random noise component that changes with time t, simulating current fluctuations in the actual environment.

[0050] The solar thermal irradiance simulator is used to simulate and generate solar thermal irradiance data under different weather conditions and / or time periods based on pre-configured solar thermal irradiance parameters. The solar thermal irradiance data includes irradiance and irradiance curves.

[0051] The solar thermal irradiance simulator outputs standard solar thermal irradiance data based on a preset nighttime period and a preset nighttime irradiance model. The terms in the nighttime irradiance model are solar thermal irradiance parameters, and the nighttime irradiance model Gnight(t) is:

[0052] Gnight(t)=Gmoon*fmoon(t)+Gambient+δ(t),

[0053] Wherein, Gmoon is the maximum lunar irradiance, typically about 0.2 W / m², fmoon(t) is the lunar phase function, with a value range of [0,1], Gambient is the ambient light irradiance, such as urban light pollution, and δ(t) is the random disturbance term that varies with time t.

[0054] The solar thermal irradiance simulator also outputs solar thermal irradiance data under conditions of sufficient and stable sunlight, based on preset daytime periods. The corresponding solar thermal irradiance parameters include solar irradiance, photovoltaic panel temperature, etc.

[0055] In other implementations, the solar thermal irradiance simulator can also generate standard daytime irradiance curves to simulate irradiance changes under different weather conditions such as sunny, cloudy, and overcast days. The simulator can also generate anomalous curves of sharp increases or decreases in irradiance at specific points in time, simulating irradiance changes caused by natural factors such as cloud cover changes and shading.

[0056] This embodiment uses a photothermal irradiance simulator to simulate daytime and nighttime photothermal irradiance, thereby obtaining all-weather photothermal irradiance data.

[0057] The smart meter data acquisition unit is used to acquire current signals from the abnormal electricity consumption pattern generator and photothermal irradiation data from the photothermal irradiation simulator.

[0058] The smart meter data acquisition unit records in real time current signals such as nighttime current flow and voltage changes, as well as photothermal irradiation data from the photothermal irradiation simulator. The sampling frequency can be set from 1 time / minute to 1 time / second to meet different accuracy requirements. The smart meter data acquisition unit is compatible with standard smart meter interfaces, allowing direct reading of actual meter data or direct injection of simulated data. The energy measurement accuracy of the smart meter data acquisition unit meets the following requirements:

[0059] ΔE≤±0.5%×Erated,

[0060] Where ΔE is the electrical energy measurement error and Erated is the rated electrical energy value.

[0061] A simulated inverter is used to convert alternating current (AC) to direct current (DC). The AC power is simulated based on solar thermal irradiation data.

[0062] In practical photovoltaic (PV) systems, solar thermal irradiance during the day or night acts on PV panels to generate electricity. This electricity is transmitted in alternating current (AC), and then converted to direct current (DC) in an inverter for user consumption. The analog inverter in this embodiment can integrate and simulate these functions, obtaining the corresponding electrical energy based on solar thermal irradiance data and achieving AC-DC conversion. In practical PV systems, the DC output power is directly proportional to the irradiance, and their trends should be highly consistent. The theoretical output power calculation formula for a PV system is:

[0063] Ptheory(t)=η*A*G(t)*[1−βT*(T(t)−Tref)],

[0064] Where Ptheory(t) is the theoretical output power of the inverter, η is the system photoelectric conversion efficiency, A is the total area of ​​the photovoltaic panel, G(t) is the solar irradiance at time t, βT is the temperature coefficient, T(t) is the panel temperature at time t, and Tref is the reference temperature, which is 25℃ under standard testing conditions.

[0065] The power anomaly simulator is used to simulate an inverter under stable irradiance conditions, causing a sudden change in the output power of the simulated inverter according to a preset interference mechanism.

[0066] The power anomaly simulator, under stable irradiance conditions, simulates sudden changes in the output power of the inverter by adjusting the load impedance or triggering protection mechanisms, thereby mimicking power anomalies caused by unauthorized load connections or improper operation. Specifically, this can be achieved by setting variable loads and electronic switches in the system, and changing the system load characteristics according to a preset program at specific time periods to simulate sudden changes in the inverter's output power.

[0067] The inverter power data monitoring unit is used to monitor and collect the power parameters and their variation curves output by the analog inverter. For example, the acquisition frequency can reach 1 time / second to ensure that power fluctuations in a short period of time can be captured.

[0068] The abnormal mode detection unit is used to comprehensively analyze whether there is an abnormal power consumption situation based on current signals and photothermal irradiation data, as well as photothermal irradiation data and power parameters.

[0069] The abnormal mode detection unit comprehensively analyzes current signals and photothermal irradiance data to determine if any abnormal power consumption has occurred. An abnormal power consumption situation is identified when the irradiance is zero and a reverse current is detected. Specifically, if zero irradiance is detected during nighttime hours, and a reverse current is detected with an amplitude greater than a preset value for a duration exceeding a preset time, an abnormal power consumption situation is determined. For example, if zero irradiance is detected between 8:00 PM and 6:00 AM during nighttime hours, and a reverse current is detected with an amplitude greater than 0.8A for more than 5 minutes, an abnormal power consumption situation is determined. This abnormal power consumption situation may be due to unauthorized connection of loads or electricity theft.

[0070] It is understandable that an irradiance close to zero can also be considered as an irradiance equal to zero.

[0071] This embodiment provides a simulation and detection system for abnormal reverse current behavior at night. The system is primarily used to simulate and detect situations where users illegally use electricity at night in the absence of light by altering line connections (e.g., unauthorized load connections).

[0072] Nighttime reverse current detection is based on the following physical principle: Under normal circumstances, photovoltaic systems do not generate current output at night when there is no sunlight, and the system is in a dormant state. The current direction should be from the photovoltaic system grid to the user side, i.e., forward current. When current flows from the user side to the grid at night, i.e., reverse current, and the amplitude exceeds the system's own loss current threshold, for example, 0.8A, it can be determined as an abnormal power consumption situation.

[0073] This embodiment can set up a nighttime abnormal power consumption detection model to detect abnormal power consumption at night. The nighttime abnormal power consumption detection model Fnight is:

[0074] Fnight=(G(t) <Gth)∧(I(t)<−Ith)∧(tstart≤t≤tend)∧(Δt> T),

[0075] Where Fnight is the nighttime power consumption anomaly detection function, 1 indicates anomaly and 0 indicates normal, I(t) is the current value measured at time t, a negative value indicates reverse current, G(t) is the irradiance value measured at time t, Gth is the irradiance threshold, usually set to 10W / m², Ith is the current threshold, set according to the system scale, usually 0.5A, tstart and tend are the start and end times of the nighttime period, respectively, Δt is the duration for which the amplitude of the reverse current is greater than the preset amplitude, and T is the preset time.

[0076] The abnormal mode detection unit comprehensively analyzes whether there is an abnormal power consumption situation based on the solar thermal irradiance data and power parameters. In this embodiment, under sufficient daytime sunlight conditions, the abnormal power situation caused by the user's unauthorized connection of loads or improper operation is simulated through the intervention of the power abnormality simulator.

[0077] As mentioned above, the output power of the analog inverter is directly proportional to the irradiance, and their trends should maintain a high degree of consistency. When the simulator intervenes due to abnormal power (simulating unauthorized load connections or improper operation by the user), it determines whether there is abnormal power consumption based on the mismatch between the output power and irradiance. When the change in output power does not match the change in irradiance, it is judged as an abnormal power consumption situation.

[0078] Specifically, after the photothermal irradiation simulator outputs photothermal irradiation data under sufficient and stable lighting conditions, the abnormal mode detection unit determines the power change rate based on the power parameters and the irradiance change rate based on the irradiance; it analyzes whether the power change rate and the irradiance change rate match; if the power change rate and the irradiance change rate do not match, it determines that there is an abnormal power consumption situation.

[0079] The power change rate ΔP = (P1-P2) / Δt, where P1 is the power calculated from the power parameters collected by the inverter power data monitoring unit at the current moment, P2 is the power calculated from the power parameters collected by the inverter power data monitoring unit at the previous moment, and Δt is the time interval.

[0080] The rate of change of irradiance ΔG = (G1 - G2) / Δt, where G1 is the irradiance collected by the smart meter data acquisition unit at the current moment, and G2 is the irradiance collected by the smart meter data acquisition unit at the previous moment.

[0081] If the power change rate ΔP matches the irradiance change rate ΔG, that is, when the irradiance change rate ΔG increases, the power change rate ΔP also increases, and when the irradiance change rate ΔG decreases, the power change rate ΔP also decreases, then they are considered to match. If the irradiance change rate ΔG increases, and the power change rate ΔP also decreases, then an abnormal power consumption situation is considered to exist.

[0082] Furthermore, the abnormal mode detection unit is specifically used to determine the power deviation rate based on the power parameter if the power change rate does not match the irradiance change rate, analyze whether the power deviation rate is less than a preset power deviation rate threshold, whether the duration of the power deviation rate being less than the power deviation rate threshold is greater than a preset time threshold, and whether the irradiance change rate is greater than a preset change rate threshold. If the analysis results are all yes, then it is determined that a power drop anomaly has occurred, and the power deviation rate threshold is negative.

[0083] The deviation rate between the actual power collected and the theoretical output power is defined as:

[0084] ΔPa(t)=(Pactual(t)−Ptheory(t)) / Ptheory(t)×100%

[0085] Where ΔPa(t) is the power deviation rate, and Pactual(t) is the actual power collected by the inverter power data monitoring unit. If the actual collected power differs greatly from the theoretical output power, the power deviation rate is large; if the actual collected power differs very little from the theoretical output power, the power deviation rate is small, close to 0.

[0086] This embodiment can establish a model for determining daytime power drop anomalies. This model is...

[0087] Fday=((ΔPa(t) / Δt)<-α)∧((ΔG(t) / Δt)>-β)∧(t∈[tday_start,tday_end]),

[0088] Where Fday is the daytime electricity consumption anomaly detection function, 1 indicates anomaly, and 0 indicates normal. ΔPa(t) is the power deviation rate, ΔG(t) is the irradiance change, Δt is the time interval, α is the power deviation rate threshold (negative value, indicating a sharp drop), β is the irradiance change rate threshold, and tday_start and tday_end are the start and end times of the daytime period, respectively.

[0089] Furthermore, this embodiment can also be based on deep learning algorithms, such as a hybrid structure of convolutional neural networks (CNN) and long short-term memory networks (LSTM), to analyze the correlation between irradiance and power curves. When the change in power curve does not match the change in secondary irradiance, it is determined to be an abnormal power consumption situation, which can effectively identify abnormal power consumption patterns in time series data.

[0090] This invention simulates abnormal power consumption by generating current signals through an abnormal power consumption mode generator and generating solar thermal irradiance data under different weather conditions and / or time periods through a solar thermal irradiance simulator. The solar thermal irradiance data includes irradiance and irradiance curves. Under stable irradiance conditions, a power anomaly simulator acts on a simulated inverter according to a preset interference mechanism, causing a sudden change in the output power of the simulated inverter. Subsequently, the current signal and solar thermal irradiance data are collected by a smart meter data acquisition unit, and the power parameters of the simulated inverter are collected by an inverter power data monitoring unit. Finally, the abnormal mode detection unit comprehensively analyzes whether an abnormal power consumption situation has occurred based on the current signal, solar thermal irradiance data, and power parameters. This invention can simulate the diversity and complexity of photovoltaic power consumption behavior scenarios. By comprehensively analyzing the current signal, solar thermal irradiance data, and power parameters, it can detect abnormal power consumption behavior on the user side, which helps to effectively and accurately identify abnormal power consumption situations and reduce false alarm rates.

[0091] In a preferred embodiment, the abnormal mode detection unit is further configured to comprehensively analyze whether an abnormal power consumption situation has occurred based on the current signal, the photothermal irradiation data, and the power parameters.

[0092] This embodiment combines multiple abnormal factors to generate complex detection scenarios. For example, it simultaneously simulates irradiance fluctuations and load changes, or triggers different types of abnormal events according to a specific time sequence within a day. The scenario generation follows a Markov process. By simulating complex abnormal power consumption conditions, the system's detection capability under various abnormal power consumption scenarios is verified.

[0093] In a preferred embodiment, the system further includes an interference factor simulation unit and a performance evaluation unit. The interference factor simulation unit is used to add interference factors to the system, and the interference factors include at least one of power grid fluctuations, communication delays, and sensor errors.

[0094] The performance evaluation unit is used to determine the system's performance indicators based on the interference factors, including accuracy, recall, F1 score, and response time.

[0095] A test report is generated based on the aforementioned interference factors and performance indicators.

[0096] The interference simulation unit simulates various interference factors that may affect the detection accuracy, testing the robustness of the system under suboptimal conditions. Power grid fluctuations, communication delays, and sensor errors are simulated based on power grid fluctuation models, communication delay models, and sensor error models, respectively.

[0097] Power grid fluctuation model: Vgrid(t) = Vnominal * [1 + ΔV * sin(2πfvt) + ϵV(t)],

[0098] Where Vgrid(t) is the instantaneous voltage, which changes over time; Vnominal is the rated voltage, the standard voltage of the power grid under ideal conditions; ΔV is the voltage fluctuation amplitude, representing the maximum relative change in voltage fluctuation; fv is the frequency of voltage fluctuation; and εV(t) is the random noise term, representing unpredictable random fluctuations or disturbances in the voltage.

[0099] Communication delay model: ΔTcomm = Tbase + Trandom*e − λ*x;

[0100] Where ΔTcomm is the total communication delay, Tbase is the base delay, which refers to the constant delay portion generated by signal processing, fixed queuing, etc., Trandom is the amplitude or reference value of the random delay, λ is the attenuation coefficient, which controls the rate at which the delay decreases with distance, and x is the communication distance.

[0101] Sensor error model: Esensor(t) = Ebias + Edrift*t + Enoise(t);

[0102] Where Esensor(t) is the total error of the sensor at time t, Ebias is the fixed bias, the inherent and constant systematic error of the sensor (such as zero-point offset), Edrift is the drift coefficient, the part of the error that accumulates linearly over time (such as due to component aging), and Enoise(t) is random noise.

[0103] The performance evaluation unit comprehensively evaluates the performance metrics of simulation and detection algorithms in various scenarios, including accuracy, recall, F1 score, response time, etc., and generates detailed evaluation reports.

[0104] Furthermore, parameters are optimized based on performance indicators to improve detection accuracy, effectively identify most abnormal electricity usage behaviors, and keep the false alarm rate below an acceptable range of 5%.

[0105] Figure 2 A flowchart of the photovoltaic power consumption simulation and detection method according to an embodiment of the present invention is shown, as follows: Figure 2 As shown, the method includes the following steps:

[0106] Step 10: The abnormal power consumption pattern generator simulates and generates an abnormal power consumption current signal based on the pre-configured current parameters.

[0107] Step 20: The solar thermal irradiance simulator generates solar thermal irradiance data under different weather conditions and / or time periods based on pre-configured solar thermal irradiance parameters. The solar thermal irradiance data includes irradiance and irradiance curve.

[0108] Step 30: The smart meter data acquisition unit acquires the current signal of the abnormal electricity consumption mode generator and the photothermal irradiation data of the photothermal irradiation simulator.

[0109] Step 40: Simulate the inverter to convert AC power to DC power, wherein the AC power is simulated based on the photothermal irradiation data;

[0110] Step 50: Under the condition that the irradiance is stable, the power anomaly simulator applies a preset interference mechanism to the simulated inverter, causing a sudden change in the output power of the simulated inverter.

[0111] Step 60: The inverter power data monitoring unit monitors and collects the power parameters output by the analog inverter;

[0112] Step 70: The abnormal mode detection unit analyzes whether an abnormal power consumption situation has occurred based on the current signal and the photothermal irradiation data, as well as the photothermal irradiation data and the power parameters.

[0113] The embodiments of the photovoltaic power consumption simulation and testing method are basically the same as those of the photovoltaic power consumption simulation and testing system described above, and can be referred to the above embodiments.

[0114] Figure 3 The diagram shows a structural schematic of an embodiment of the computer device of the present invention. The specific embodiments of the present invention do not limit the specific implementation of the computer device.

[0115] like Figure 3 As shown, the computer device may include: a processor 402, a communications interface 404, a memory 406, and a communications bus 408.

[0116] The processor 402, communication interface 404, and memory 406 communicate with each other via communication bus 408. Communication interface 404 is used to communicate with other computer devices, such as clients or other server network elements. The processor 402 executes program 410, specifically performing the relevant steps described above in the computer device embodiment.

[0117] Specifically, program 410 may include program code, which includes computer-executable instructions.

[0118] Processor 402 may be a central processing unit (CPU), an application-specific integrated circuit (ASIC), or one or more integrated circuits configured to implement embodiments of the present invention. The computer device includes one or more processors, which may be processors of the same type, such as one or more CPUs; or processors of different types, such as one or more CPUs and one or more ASICs.

[0119] Memory 406 is used to store program 410. Memory 406 may include high-speed RAM memory, and may also include non-volatile memory, such as at least one disk storage device.

[0120] Specifically, program 410 can be called by processor 402 to cause the computer device to perform the steps of the method shown above.

[0121] This invention provides a computer-readable storage medium storing at least one executable instruction that, when executed on a computer device, causes the computer device to perform the method embodiments described above.

[0122] This invention provides a computer program that can be called by a processor to cause a computer device to execute the above-described method embodiments.

[0123] This invention provides a computer program product, which includes a computer program stored on a computer-readable storage medium. The computer program includes program instructions that, when executed on a computer, cause the computer to perform any of the above-described method embodiments.

[0124] The algorithms or displays provided herein are not inherently related to any particular computer, virtual system, or other device. Various general-purpose systems can also be used in conjunction with the teachings herein. The required structure for constructing such systems is apparent from the above description. Furthermore, the embodiments of the present invention are not directed to any particular programming language. It should be understood that the content of the invention described herein can be implemented using various programming languages, and the above description of specific languages ​​is for the purpose of disclosing the best mode of implementation of the invention.

[0125] Numerous specific details are set forth in the specification provided herein. However, it will be understood that embodiments of the invention may be practiced without these specific details. In some instances, well-known methods, structures, and techniques have not been shown in detail so as not to obscure the understanding of this specification.

[0126] Similarly, it should be understood that, in order to streamline the invention and aid in understanding one or more of the various aspects of the invention, features of the embodiments of the invention are sometimes grouped together in a single embodiment, figure, or description thereof in the above description of exemplary embodiments of the invention. However, this disclosure should not be construed as reflecting an intention that the claimed invention requires more features than are expressly recited in each claim.

[0127] Those skilled in the art will understand that modules in the computer device of the embodiments can be adaptively modified and placed in one or more computer devices different from that embodiment. Modules, units, or components in the embodiments can be combined into a single module, unit, or component, and can be divided into multiple sub-modules, sub-units, or sub-components. Except where at least some of such features and / or processes or units are mutually exclusive, any combination can be used to combine all features disclosed in this specification (including the accompanying claims, abstract, and drawings) and all processes or units of any method or computer device so disclosed. Unless expressly stated otherwise, each feature disclosed in this specification (including the accompanying claims, abstract, and drawings) may be replaced by an alternative feature that serves the same, equivalent, or similar purpose.

[0128] It should be noted that the above embodiments are illustrative of the invention and not restrictive, and that those skilled in the art can devise alternative embodiments without departing from the scope of the appended claims. In the claims, any reference signs placed between parentheses should not be construed as limiting the claims. The word "comprising" does not exclude the presence of elements or steps not listed in the claims. The word "a" or "an" preceding an element does not exclude the presence of a plurality of such elements. The invention can be implemented by means of hardware comprising several different elements and by means of a suitably programmed computer. In the unit claims enumerating several means, several of these means may be embodied by the same item of hardware. The use of the words first, second, and third, etc., does not indicate any order. These words can be interpreted as names. The steps in the above embodiments, unless otherwise specified, should not be construed as limiting the order of execution.

Claims

1. A photovoltaic power consumption simulation and detection system, characterized in that, The system includes an abnormal power consumption mode generator, a solar thermal irradiation simulator, a smart meter data acquisition unit, a simulated inverter, a power anomaly simulator, an inverter power data monitoring unit, and an abnormal mode detection unit. The abnormal power consumption mode generator is used to simulate and generate abnormal power consumption current signals based on pre-configured current parameters. The solar thermal irradiance simulator is used to simulate and generate solar thermal irradiance data under different weather conditions and / or time periods based on pre-configured solar thermal irradiance parameters. The solar thermal irradiance data includes irradiance and irradiance curves. The smart meter data acquisition unit is used to acquire the current signal of the abnormal electricity consumption mode generator and the photothermal irradiation data of the photothermal irradiation simulator. The simulated inverter is used to convert AC power to DC power, and the AC power is simulated based on the photothermal irradiation data; The power anomaly simulator is used to apply a preset interference mechanism to the simulated inverter under the condition that the irradiance is stable, so that the output power of the simulated inverter will suddenly change. The inverter power data monitoring unit is used to monitor and collect the power parameters output by the analog inverter. The abnormal mode detection unit is used to comprehensively analyze whether an abnormal power consumption situation has occurred based on the current signal and the photothermal irradiation data, as well as based on the photothermal irradiation data and the power parameters.

2. The photovoltaic power consumption simulation and detection system according to claim 1, characterized in that, The abnormal power consumption pattern generator includes a controller and a controllable current source connected together. The controller is used to trigger the controllable current source at preset time intervals or at random time intervals, so that the controllable current source generates a reverse current signal Isim(t) with a predetermined amplitude and waveform. Isim(t)=Ibase+Asin(2πft)+ε(t), Where Ibase is the basic reverse current value, A is the fluctuation amplitude of the current signal, f is the fluctuation frequency of the current signal, and ε(t) is the random noise component that varies with time t.

3. The photovoltaic power consumption simulation and detection system according to claim 1, characterized in that, The solar thermal irradiance simulator is used to output standard solar thermal irradiance data based on a preset nighttime period and a preset nighttime irradiance model, wherein the nighttime irradiance model Gnight(t) is: Gnight(t)=Gmoon*fmoon(t)+Gambient+δ(t), Where Gmoon is the maximum lunar irradiance, fmoon(t) is the lunar phase function with a value range of [0,1], Gambient is the ambient light irradiance, and δ(t) is a random perturbation term that varies with time t. The photothermal irradiation simulator is also used to output photothermal irradiation data under conditions of sufficient and stable light, based on preset daytime periods.

4. The photovoltaic power consumption simulation and testing system according to any one of claims 1 to 3, characterized in that, The abnormal mode detection unit is specifically used to determine that there is an abnormal power consumption situation when it detects that the irradiance is equal to zero during the nighttime period, and detects a reverse current, and the amplitude of the reverse current is greater than a preset amplitude for a duration greater than a preset time. as well as, After the photothermal irradiation simulator outputs photothermal irradiation data under sufficient and stable light conditions, the power change rate is determined according to the power parameter, and the irradiance change rate is determined according to the irradiance. Analyze whether the power change rate matches the irradiance change rate; If the power change rate does not match the irradiance change rate, then an abnormal power consumption situation is determined.

5. The photovoltaic power consumption simulation and detection system according to claim 4, characterized in that, The abnormal mode detection unit is further configured to, if the power change rate does not match the irradiance change rate, determine the power deviation rate based on the power parameters, analyze whether the power deviation rate is less than a preset power deviation rate threshold, whether the duration of the power deviation rate being less than the power deviation rate threshold is greater than a preset time threshold, and whether the irradiance change rate is greater than a preset change rate threshold. If the analysis results are all yes, then it is determined that a power drop anomaly has occurred, and the power deviation rate threshold is negative.

6. The photovoltaic power consumption simulation and detection system according to claim 1, characterized in that, The abnormal mode detection unit is also used to comprehensively analyze whether an abnormal power consumption situation has occurred based on the current signal, the photothermal irradiation data, and the power parameters.

7. The photovoltaic power consumption simulation and detection system according to claim 1, characterized in that, The system also includes an interference factor simulation unit and a performance evaluation unit. The interference factor simulation unit is used to add interference factors to the system. The interference factors include at least one of power grid fluctuations, communication delays, and sensor errors. The performance evaluation unit is used to determine the system's performance indicators based on the interference factors, including accuracy, recall, F1 score, and response time. A test report is generated based on the aforementioned interference factors and performance indicators.

8. A method for simulating and detecting photovoltaic power consumption, characterized in that, The photovoltaic power consumption simulation and testing method is performed based on the photovoltaic power consumption simulation and testing system according to any one of claims 1-7, and the method includes: The abnormal power consumption pattern generator simulates and generates abnormal power consumption current signals based on pre-configured current parameters; The solar thermal irradiance simulator generates solar thermal irradiance data under different weather conditions and / or time periods based on pre-configured solar thermal irradiance parameters. The solar thermal irradiance data includes irradiance and irradiance curves. The smart meter data acquisition unit acquires the current signal from the abnormal electricity consumption pattern generator and the photothermal irradiation data from the photothermal irradiation simulator; The simulated inverter converts AC power to DC power, and the AC power is simulated based on the photothermal irradiation data. The power anomaly simulator, under the condition of stable irradiance, applies a preset interference mechanism to the simulated inverter, causing a sudden change in the output power of the simulated inverter; The inverter power data monitoring unit monitors and collects the power parameters output by the analog inverter; The abnormal mode detection unit comprehensively analyzes whether an abnormal power consumption situation has occurred based on the current signal, the photothermal irradiation data, the photothermal irradiation data, and the power parameters.

9. A computer device, characterized in that, include: The processor, memory, communication interface, and communication bus are provided, wherein the processor, memory, and communication interface communicate with each other via the communication bus. The memory is used to store at least one executable instruction that causes the processor to perform the method as described in claim 8.

10. A computer-readable storage medium, characterized in that, The storage medium stores at least one executable instruction, which, when executed on a computer device, causes the computer device to perform the method as described in claim 8.

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