BIPV photovoltaic isolation wall energy storage control method, system, device and medium

Abstract

The invention relates to a BIPV photovoltaic isolation wall energy storage control method, system and device and a medium, and belongs to the technical field of photovoltaic isolation wall energy storage, and the energy storage control method comprises the steps: obtaining the generating capacity data of a photovoltaic module and the charging and discharging state data of an energy storage device; obtaining an energy storage priority index based on the generating capacity data and the charging and discharging state data; acquiring operation state monitoring data of the high-voltage power grid; obtaining a power grid load pressure index based on the operation state monitoring data; inputting the power grid load pressure index and the energy storage priority index into a pre-constructed power supply scheduling model, and generating a scheduling control strategy according to an output result of the power supply scheduling model; and performing scheduling control on the photovoltaic isolation wall system according to the scheduling control strategy, and adjusting the charging and discharging operation of the energy storage device. According to the invention, the discontinuity of photovoltaic power generation and the dynamic change of the power grid load are fully considered, and the safety, stability and reliability of the whole safety protection system are improved through intelligent regulation and control.

Description

Technical Field

[0001] The present application relates to the field of photovoltaic isolation wall energy storage technology, and in particular to a BIPV photovoltaic isolation wall energy storage control method, system, equipment and medium. Background Art

[0002] As the global energy crisis intensifies and environmental pollution becomes increasingly prominent, the use of clean and renewable energy has become an important way to solve energy shortages and reduce carbon emissions. Photovoltaic power generation, as one of the representatives of renewable energy technologies, has been widely used due to its high efficiency and environmental protection. In this context, the application of integrated photovoltaic building materials (Building Integrated Photovoltaics, BIPV) continues to expand. BIPV is a technology that combines photovoltaic power generation functions with building components. By directly integrating photovoltaic modules into building roofs, walls, windows and other parts, it achieves a deep integration of energy production and building structures, improves energy utilization, and reduces building energy consumption.

[0003] As a typical application of BIPV technology, photovoltaic isolation walls not only have the functions of heat insulation and sound insulation of traditional isolation walls, but also can use photovoltaic modules to convert solar energy into electricity to supply power to the grid or provide green electricity for electrical equipment in the building. Therefore, photovoltaic isolation walls play a positive role in improving the energy self-sufficiency rate of buildings, relieving the pressure of power load, and reducing carbon dioxide emissions.

[0004] At present, the construction of fence systems suitable for military facilities, borders, important material storage depots and other places that require independent power supply, security protection and concealment has also attracted attention to BIPV technology. These places usually need to set up isolation walls with special security functions to effectively prevent illegal intrusion and sabotage. In order to further improve the safety performance of the system and avoid illegal climbing and touching, a high-voltage power grid is often installed on the top of the isolation wall. The high-voltage power grid provides safety protection by stunning without harming life. In order to achieve self-sufficiency in electricity demand, in this isolation wall system, a self-sufficient power supply system is formed by connecting the high-voltage power grid with photovoltaic power generation devices and energy storage batteries. Therefore, whether in remote areas or in emergencies, the system can operate autonomously without relying on external power supply networks, thereby improving the independence and safety of the system.

[0005] However, common energy storage control methods do not fully consider the discontinuity of photovoltaic power generation and the dynamic changes in grid load, which may lead to insufficient optimization of energy management of energy storage devices, making it difficult to adapt to the complex and changeable system operating environment, and unable to fully guarantee safety protection functions, thereby reducing the stability and reliability of the entire safety protection system. Summary of the invention

[0006] In order to improve the stability and reliability of the entire safety protection system, the present application provides a BIPV photovoltaic isolation wall energy storage control method, system, equipment and medium.

[0007] In the first aspect, the present application provides a BIPV photovoltaic isolation wall energy storage control method, which adopts the following technical solution: A BIPV photovoltaic isolation wall energy storage control method is applied to a photovoltaic isolation wall system, the photovoltaic isolation wall system includes a photovoltaic isolation wall and a photovoltaic module installed on the photovoltaic isolation wall, an energy storage device and a high-voltage power grid, the photovoltaic module is used to provide the energy storage device with photovoltaic converted electric energy, the energy storage device is used to store electric energy and supply power to the high-voltage power grid, and the high-voltage power grid is used to perform power-on protection; The energy storage control method comprises: Acquiring power generation data of the photovoltaic module and charging and discharging status data of the energy storage device; Based on the power generation data and the charge and discharge status data, an energy storage priority index is obtained; the energy storage priority index is used to determine the priority of charging the energy storage device or the energy storage device supplying power to the high-voltage power grid; Acquiring operating status monitoring data of the high-voltage power grid; Based on the operation status monitoring data, a power grid load pressure index is obtained; Inputting the power grid load pressure index and the energy storage priority index into a pre-built power supply scheduling model, and generating a scheduling control strategy according to the output result of the power supply scheduling model; The photovoltaic isolation wall system is dispatched and controlled according to the dispatching control strategy to adjust the charging and discharging operations of the energy storage device.

[0008] By adopting the above technical solution and building a power supply scheduling model based on comprehensive energy storage priority indicators and grid load pressure indicators, it is possible to achieve the goal of simultaneously optimizing photovoltaic power generation, energy storage management and grid load. By fully considering the discontinuity of photovoltaic power generation and the dynamic changes of grid load, the system's ability to respond to changes in external environment and internal demand is enhanced. Through intelligent regulation, the safety, stability and reliability of the entire safety protection system are improved.

[0009] Optionally, the step of obtaining a power grid load pressure index based on the operation status monitoring data includes: Performing data preprocessing on the operating status monitoring data; Calculate power parameters based on preprocessed status monitoring data and extract dynamic changes; Calculating a voltage stability index, a frequency stability index and a load factor index respectively according to the power parameter and the dynamic change amount; The voltage stability index, frequency stability index and load rate index are weightedly calculated to obtain the power grid load pressure index.

[0010] By adopting the above technical solutions, we conduct multi-dimensional analysis on the grid operation status monitoring data, gradually extract the important operation indicators of the grid (voltage stability, frequency stability and load rate), and form an indicator that comprehensively reflects the current load pressure of the grid by weighted fusion of these indicators. This indicator not only improves the monitoring accuracy of the grid pressure, but also provides a scientific basis for the regulation and early warning of the grid, thereby effectively improving the safety and stability of the grid operation.

[0011] Optionally, after the step of obtaining the power grid load pressure index based on the operation status monitoring data, the step further includes: Based on a preset pressure mapping table, the load pressure interval is determined according to the load pressure index of the power grid, and the corresponding load pressure level is determined according to the load pressure interval; wherein the preset pressure mapping table includes a mapping relationship between multiple groups of load pressure intervals and load pressure levels; Determining whether the load pressure level exceeds a preset level threshold; If so, it is determined that the high-voltage power grid is in an abnormal load state, and load abnormality warning information is generated and sent to the operation and maintenance terminal.

[0012] By adopting the above technical solutions, continuous load anomaly monitoring helps to optimize the overall energy management of the photovoltaic isolation wall and the high-voltage power grid, ensure operation under appropriate load conditions, and prevent potential safety hazards that may occur in the power grid under high load by timely identifying potential abnormal load conditions, thereby improving the management and control efficiency of power grid operation safety.

[0013] Optionally, the method further includes a training step of the power supply scheduling model, wherein the training step includes: Acquire a sample data set and perform data preprocessing; wherein the sample data set includes historical power grid load pressure data, historical energy storage priority data, and corresponding historical dispatch control strategies; Dividing the sample data set into a training set, a validation set and a test set; Inputting the training set into a pre-built neural network model for iterative training, optimizing the model parameters and calculating the cross entropy loss function of the model until the cross entropy loss function meets the preset conditions, thereby obtaining a trained neural network model; Validating the neural network model based on the validation set, evaluating the performance of the neural network model and adjusting the hyperparameters of the model according to the validation results; The prediction capability of the adjusted neural network model is tested based on the test set to obtain a power supply scheduling model.

[0014] By adopting the above technical solution, a power supply dispatching model is constructed and trained. The model can automatically output reasonable dispatching strategies under different load pressure and energy storage status conditions, and realizes the effective mapping from power grid load pressure indicators and energy storage priority indicators to dispatching control strategies. In addition, through a rigorous verification and testing process, it is ensured that the model has good generalization ability and practicality, can play a key role in actual dispatching control, and effectively improve operational efficiency and reliability.

[0015] Optionally, the energy storage control method further includes: Collect current solar radiation intensity information; Acquiring photovoltaic parameter information of the photovoltaic module; wherein the photovoltaic parameter information includes photovoltaic area, photovoltaic energy storage efficiency and temperature correction coefficient; Determine a corresponding photovoltaic power generation prediction value according to the current solar radiation intensity information and the photovoltaic parameter information; Determining whether the power generation data of the photovoltaic module exceeds the photovoltaic power generation prediction value; If not, a photovoltaic control instruction is sent to the photovoltaic isolation wall system to control and adjust the photovoltaic panels of the photovoltaic components to maintain the best light receiving angle.

[0016] By adopting the above technical solution, the power generation of photovoltaic modules is monitored in real time and compared with the predicted value. When the power generation does not reach the expectation, the angle of the photovoltaic panels is automatically adjusted to ensure that the photovoltaic panels are always in the best light-receiving state, thereby improving the photovoltaic power generation efficiency and ensuring the efficient operation of the photovoltaic power generation system. This not only helps to improve energy utilization, but also reduces energy costs, which is of great significance for promoting the development and application of clean energy.

[0017] Optionally, after sending a photovoltaic control instruction to the photovoltaic isolation wall system to control and adjust the photovoltaic panel of the photovoltaic assembly to maintain an optimal light receiving angle, the step further includes: Determining whether the power generation data of the photovoltaic assembly exceeds the photovoltaic power generation prediction value after a preset time period; If not, it is determined that the photovoltaic component is in an abnormal state, and photovoltaic power generation abnormality warning information is generated and sent to the operation and maintenance terminal.

[0018] By adopting the above technical solution, it is determined whether the actual power generation of the photovoltaic module meets the predicted value, and an early warning message is issued when an abnormality occurs. This technical solution can effectively monitor the operating status of the photovoltaic module. It can not only detect potential problems of the module in time, reduce energy waste, and improve system reliability, but also reduce the huge losses that may be caused by delayed maintenance due to failure to be discovered in time.

[0019] In the second aspect, the present application provides a BIPV photovoltaic isolation wall energy storage control system, which adopts the following technical solution: A BIPV photovoltaic isolation wall energy storage control system is applied to a photovoltaic isolation wall system, the photovoltaic isolation wall system includes a photovoltaic isolation wall and a photovoltaic module, an energy storage device and a high-voltage power grid installed on the photovoltaic isolation wall, the photovoltaic module is used to provide the energy storage device with photovoltaic converted electric energy, the energy storage device is used to store electric energy and supply power to the high-voltage power grid, and the high-voltage power grid is used to perform power-on protection; The energy storage control system comprises: A first acquisition module is used to acquire the power generation data of the photovoltaic module and the charge and discharge status data of the energy storage device; An energy storage priority determination module, used to obtain an energy storage priority index based on the power generation data and the charge and discharge status data; the energy storage priority index is used to determine the priority of charging the energy storage device or the energy storage device supplying power to the high-voltage power grid; A second acquisition module is used to acquire the operating status monitoring data of the high-voltage power grid; A load pressure determination module, used to obtain a power grid load pressure index based on the operation status monitoring data; A strategy generation module, used to input the power grid load pressure index and the energy storage priority index into a pre-built power supply scheduling model, and generate a scheduling control strategy according to the output result of the power supply scheduling model; A scheduling control module is used to schedule and control the photovoltaic isolation wall system according to the scheduling control strategy and adjust the charging and discharging operations of the energy storage device.

[0020] Optionally, the energy storage control system further includes: A load pressure level determination module, for determining the load pressure interval according to the load pressure index of the power grid based on a preset pressure mapping table, and determining the corresponding load pressure level according to the load pressure interval; wherein the preset pressure mapping table includes a mapping relationship between multiple groups of load pressure intervals and load pressure levels; A judgment module, used to judge whether the load pressure level exceeds a preset level threshold, and if so, output an abnormal judgment result; The abnormal warning module is used to respond to the abnormal judgment result, determine that the high-voltage power grid is in an abnormal load state, generate load abnormality warning information and send it to the operation and maintenance terminal.

[0021] In a third aspect, the present application provides a computer device, which adopts the following technical solution: A computer device comprises a memory, a processor and a computer program stored in the memory, wherein the processor executes the computer program to implement the steps of the method as described in the first aspect.

[0022] In a fourth aspect, the present application provides a computer-readable storage medium, which adopts the following technical solution: A computer-readable storage medium stores a computer program that can be loaded by a processor and execute any one of the methods in the first aspect.

[0023] To summarize, the present application includes at least one of the following beneficial technical effects: by optimizing the management of photovoltaic power generation and energy storage devices, it can adapt to the discontinuity of photovoltaic power generation and the dynamic changes of the high-voltage power grid load in real time, thereby stably and efficiently supplying power to the high-voltage power grid. It not only improves the energy self-sufficiency and independence of the isolation wall system, but also effectively enhances the safety protection capabilities of related facilities, which has important practical application significance for ensuring independent operation in remote areas or emergency situations. BRIEF DESCRIPTION OF THE DRAWINGS

[0024] Figure 1 This is a first flow chart of a BIPV photovoltaic isolation wall energy storage control method according to one of the embodiments of the present application.

[0025] Figure 2 It is a second flow chart of a BIPV photovoltaic isolation wall energy storage control method according to one of the embodiments of the present application.

[0026] Figure 3 It is a third flow chart of a BIPV photovoltaic isolation wall energy storage control method according to one of the embodiments of the present application.

[0027] Figure 4 It is the fourth process diagram of a BIPV photovoltaic isolation wall energy storage control method of one of the embodiments of the present application.

[0028] Figure 5 It is the fifth flow chart of a BIPV photovoltaic isolation wall energy storage control method of one of the embodiments of the present application. DETAILED DESCRIPTION

[0029] In order to make the purpose, technical solutions and advantages of this application more clear, the following Figure 1-5 It should be understood that the specific embodiments described herein are only used to explain the present application and are not used to limit the present application.

[0030] At present, how to effectively manage the power supply of photovoltaic isolation walls and high-voltage power grids in military, border and reserve wall systems remains a major challenge. Due to the discontinuity of photovoltaic power generation and the limited capacity of energy storage devices, it may not be possible to provide enough electricity to maintain the normal operation of the high-voltage power grid at critical moments, thus affecting the reliability of the entire security protection system.

[0031] Based on this, an embodiment of the present application discloses a BIPV photovoltaic isolation wall energy storage control method.

[0032] A BIPV photovoltaic isolation wall energy storage control method is applied to a photovoltaic isolation wall system. The photovoltaic isolation wall system includes a photovoltaic isolation wall and photovoltaic components, an energy storage device and a high-voltage power grid installed on the photovoltaic isolation wall. The photovoltaic components are used to provide the energy storage device with photovoltaic converted electrical energy. The energy storage device is used to store electrical energy and supply power to the high-voltage power grid. The high-voltage power grid is used for power-on protection.

[0033] As an implementation method of the photovoltaic isolation wall system, the photovoltaic isolation wall body can be made of high-strength materials, which can not only resist physical attacks, but also have bulletproof and anti-climbing functions to ensure its reliability in safety protection; photovoltaic components can use photovoltaic panels, and the installation position can be selected on the surface or top of the wall. It is designed to be hidden and flush with the surface of the isolation wall, so that it does not take up additional space and improves concealment. The photovoltaic panels convert solar energy into electrical energy to provide power support for the entire system; the energy storage device can use energy storage batteries, which are connected to photovoltaic components to store the converted photovoltaic electricity. It can be designed and installed in a special chamber inside the wall, which not only improves the safety of the battery, but also enhances its concealment; the high-voltage power grid can be set on the top of the isolation wall, and through the connection with the photovoltaic components and the energy storage device, a self-sufficient power supply can be achieved. This design can not only prevent illegal intrusion, but also provide a lasting safety alert in an emergency.

[0034] Reference Figure 1 , the energy storage control method includes: Step S101, obtaining power generation data of the photovoltaic module and charge and discharge status data of the energy storage device; Among them, since the power generated by photovoltaic modules may vary in different time periods and is affected by various factors such as weather, sunshine intensity, temperature, etc., in order to accurately manage the efficiency of energy use, it is first necessary to monitor the power generated by photovoltaic modules in real time. In addition, in order to effectively manage the status of energy storage devices (including charging and discharging), it is also necessary to obtain its charging and discharging status data regularly or in real time, which can be collected through sensors or data acquisition equipment.

[0035] Exemplarily, the power generation data may include the real-time power of the photovoltaic components, the accumulated historical power generation, the total power generation of the day, etc.; the charge and discharge status data may include the current battery energy storage status SOC, the charge and discharge rate, and the remaining rechargeable capacity, etc.

[0036] Step S102, based on the power generation data and the charge and discharge status data, an energy storage priority index is obtained; the energy storage priority index is used to determine the priority of charging the energy storage device or the energy storage device supplying power to the high-voltage power grid; Among them, the power generation data reflects the currently available energy resources, while the charging and discharging status of the energy storage device reflects the system margin.

[0037] In some embodiments, the energy storage priority index can be obtained based on preset logical rules; for example, if the photovoltaic power generation is high (for example, the photovoltaic power generation is higher than the preset upper limit threshold) and the energy storage device is in an idle or low charge state, the energy storage device is preferably charged; conversely, when the photovoltaic power generation is low (for example, the photovoltaic power generation is lower than the preset lower limit threshold) and the energy storage device is currently in a sufficient power state, the high-voltage grid is preferably supplied with power; in addition, if the photovoltaic power generation is at a medium level and can partially meet the grid demand, and the energy storage device is in an intermediate state, the charging and discharging priority should be flexibly selected according to the forecasting strategy and the current load. Based on this information, the distribution and use order of electric energy can be dynamically adjusted by determining the energy storage priority index.

[0038] It is understandable that the introduction of energy storage priority indicators can promote the system to manage the flow of electric energy more intelligently, ensuring that energy can be used most fully and reasonably under different working conditions. This indicator helps to prioritize critical needs when resources are tight, and to perform appropriate energy storage when resources are sufficient.

[0039] Step S103, obtaining the operating status monitoring data of the high voltage power grid; Among them, obtaining the operating status monitoring data of the high-voltage power grid (such as voltage, current, frequency fluctuation data, power factor, etc.) is an important prerequisite for formulating dispatching strategies; based on the operating status monitoring data, changes in the power grid load can be identified in real time, and it can be judged whether the health status of the power grid is within the normal range. Once abnormal conditions such as overload occur, timely measures can be taken to avoid large-scale power outages or power waste.

[0040] Step S104, obtaining a power grid load pressure index based on the operation status monitoring data; Specifically, by analyzing the operating status monitoring data of the high-voltage power grid, the load pressure index of the power grid can be calculated and obtained, such as the current load rate of the power grid, the degree of power shortage or surplus, etc.; this indicator reflects the current pressure faced by the power grid, which helps to predict the potential risks of the power grid and make early predictions.

[0041] Step S105, inputting the grid load pressure index and the energy storage priority index into a pre-built power supply scheduling model, and generating a scheduling control strategy according to the output result of the power supply scheduling model; Among them, the power supply scheduling model can combine the priority level of energy storage devices with the load status of the high-voltage power grid, so that the scheduling strategy can not only take into account the optimal use of the energy storage system, but also provide support when the power grid needs it; in some embodiments, the model can be implemented using a rule engine, machine learning algorithm or other optimization methods.

[0042] Specifically, based on the output of the power supply dispatch model, the dispatch control strategy will clearly specify the next operation, such as giving priority to charging or discharging the energy storage device, or temporarily adjusting the photovoltaic power output according to the grid load status, so as to meet the actual power demand and grid conditions.

[0043] Step S106, dispatching and controlling the photovoltaic isolation wall system according to the dispatching and control strategy, and adjusting the charging and discharging operations of the energy storage device.

[0044] Among them, the photovoltaic isolation wall system is dispatched and controlled through the generated dispatching control strategy, and the specific control signal will trigger the energy storage device to charge and discharge, so as to further optimize the synergistic effect of the photovoltaic system and the energy storage system.

[0045] In the above implementation mode, a power supply scheduling model is constructed by integrating energy storage priority index and grid load pressure index, which can achieve the goal of optimizing photovoltaic power generation, energy storage management and grid load at the same time. By fully considering the discontinuity of photovoltaic power generation and the dynamic changes of grid load, the system's ability to respond to changes in external environment and internal demand is enhanced. Through intelligent regulation, the safety, stability and reliability of the entire safety protection system are improved.

[0046] Reference Figure 2 As an implementation method of step S104, the step of obtaining the power grid load pressure index based on the operation status monitoring data includes: Step S201, preprocessing the operation status monitoring data; Among them, various operating status monitoring data such as voltage data, current data, frequency fluctuation data, power factor, etc. are obtained in real time from multiple sensor nodes or monitoring systems on the high-voltage power grid.

[0047] In addition, the data preprocessing steps may include denoising, timing alignment and missing value processing; specifically, denoising the data, using filters (such as low-pass filters) to filter out high-frequency noise in the signal, and eliminating instantaneous interference that may be caused by the measuring equipment; through timing alignment, ensure that the timestamps of all data are consistent for subsequent joint analysis, because the time synchronization of multi-source monitoring data is crucial to accuracy; for some incomplete or missing data, interpolation, previous value continuation and other methods are used to fill in the missing information.

[0048] Step S202, calculating power parameters based on the preprocessed state monitoring data and extracting dynamic changes; Specifically, key power parameters such as active power, reactive power, apparent power, load rate, etc. can be derived from the existing pre-processed data; dynamic change extraction can extract key dynamic change quantities such as voltage deviation, frequency deviation, etc. by analyzing the data changes at each moment.

[0049] Step S203, calculating the voltage stability index, the frequency stability index and the load factor index respectively according to the power parameters and the dynamic change amount; Among them, the voltage stability index indicates the degree of voltage deviation. If the value is larger, it means that the voltage pressure on the power grid is greater; the frequency stability index indicates the amplitude of frequency fluctuation, reflecting the robustness of the power grid frequency. The larger the value is, the greater the power grid frequency pressure is; the load rate index indicates the current load rate. If it exceeds 1, it means overload and attention should be paid.

[0050] Step S204, performing weighted calculation on the voltage stability index, the frequency stability index and the load rate index to obtain a grid load pressure index.

[0051] Among them, multiple single pressure indicators can be combined into an overall load pressure indicator through weighted calculation, and the weight of each pressure indicator can be set and adjusted according to actual conditions to reflect the relative importance of different pressure sources.

[0052] In the above implementation, by performing multi-dimensional analysis on the grid operation status monitoring data, the important grid operation indicators (voltage stability, frequency stability and load rate) are gradually extracted, and these indicators are weighted and integrated to form an indicator that comprehensively reflects the current load pressure of the grid. This indicator not only improves the monitoring accuracy of the grid pressure, but also provides a scientific basis for the regulation and early warning of the grid, thereby effectively improving the safety and stability of the grid operation.

[0053] Reference Figure 3 As a further implementation of the energy storage control method, after the step of obtaining the grid load pressure index based on the operation status monitoring data, the method further includes: Step S301, based on a preset pressure mapping table, determine the load pressure interval according to the power grid load pressure index, and determine the corresponding load pressure level according to the load pressure interval; wherein the preset pressure mapping table includes a mapping relationship between multiple groups of load pressure intervals and load pressure levels; Specifically, the preset pressure mapping table contains multiple different load pressure intervals, each interval represents a different level of load pressure, and this level can be represented by numbers or other identifiers (such as 0-5, AE, etc.). The interval range corresponding to each level can be set in advance based on operating experience or historical data. The obtained power grid load pressure index will fall within a specific interval. The system can determine its load pressure interval and corresponding load pressure level based on this index.

[0054] It can be understood that, through this grading interval method, the quantified load pressure can be quickly mapped to a more intuitive and easy-to-understand grade interval range, thereby simplifying subsequent processing steps and facilitating management and control.

[0055] Step S302, determining whether the load pressure level exceeds a preset level threshold; if so, jumping to step S303; if not, not performing any operation; Specifically, in order to ensure the safe operation of the power grid, it is usually necessary to set one or more load pressure level thresholds (for example, level 3 or above is defined as a potentially dangerous interval). The system will automatically check the current load pressure level to determine whether it exceeds this preset threshold. If it exceeds the preset level threshold, it means that the load pressure of the power grid may have reached the edge of danger and measures need to be taken.

[0056] Step S303, determining that the high-voltage power grid is in an abnormal load state, generating load abnormality warning information and sending it to the operation and maintenance terminal.

[0057] Specifically, when it is detected that the load pressure level exceeds the preset safety level threshold, it is considered that there may be an abnormality in the high-voltage power grid. At this time, the system will generate a load abnormality warning message and send it to the operation and maintenance terminal responsible for monitoring, indicating that the current load condition has reached a dangerous state so that the staff can take timely measures to reduce the load or conduct troubleshooting.

[0058] It is understandable that abnormal load conditions such as short circuit or overload may lead to unstable grid voltage, thus bringing unexpected dangers to contacts. By detecting the load status, these hidden dangers can be discovered and eliminated in time to prevent accidental injuries. In addition, load status detection can also help identify potential faults in the grid, such as damage, aging or incorrect connection. By monitoring the load of the grid in real time, the system can issue an alarm in advance to indicate the need for maintenance or repair, preventing further damage and risk spread.

[0059] In the above implementation mode, continuous load anomaly monitoring helps to optimize the overall energy management of the photovoltaic isolation wall and the high-voltage power grid, ensure operation under appropriate load conditions, and prevent potential safety hazards that may occur in the power grid under high load by timely identifying potential abnormal load conditions, thereby improving the management and control efficiency of the safety of power grid operation.

[0060] Reference Figure 4 As a further implementation of the energy storage control method, a training step of a power supply scheduling model is also included, and the training step includes: Step S401, obtaining a sample data set and performing data preprocessing; wherein the sample data set includes historical power grid load pressure data, historical energy storage priority data, and corresponding historical dispatch control strategies; Specifically, relevant power grid operation data is collected from the historical database, including but not limited to historical power grid load pressure data, historical energy storage priority data and corresponding historical dispatch control strategies; the historical power grid load pressure data and historical energy storage priority data are used as input variables, and the corresponding historical dispatch control strategies are used as target variables of the model; Among them, the historical grid load pressure data is used to reflect the load pressure conditions of the high-voltage grid at different time points. The historical energy storage priority data reflects the different charging and discharging priorities set according to system requirements. The historical dispatching control strategy includes the dispatching measures taken under specific load pressure and energy storage priority conditions in the past, such as adjusting the working mode of the energy storage device.

[0061] As an implementation method of data preprocessing, the preprocessing steps include missing value processing (missing values ​​can be filled by interpolation methods), outlier processing (using statistical methods to identify and process outliers), data standardization, and feature extraction. The preprocessed data has higher quality and helps the model better learn the potential patterns in the data.

[0062] Step S402, dividing the sample data set into a training set, a validation set and a test set; Among them, by dividing the data set, the effectiveness of model training can be ensured, and the generalization ability of the model can be objectively evaluated. The existence of the validation set and the test set helps prevent the model from overfitting and ensures that the model can perform well on unknown data.

[0063] Step S403, inputting the training set into a pre-built neural network model for iterative training, optimizing the model parameters and calculating the cross entropy loss function of the model until the cross entropy loss function meets the preset conditions, thereby obtaining a trained neural network model; In one of the embodiments of the present application, the pre-built neural network model adopts a long short-term memory network (LSTM) model, which is good at processing time series data and is suitable for predicting and scheduling dynamic changes in energy systems; in this embodiment, the model architecture content specifically includes: an input layer for receiving multi-dimensional time series data; an LSTM layer, which can increase the complexity of the model by stacking multiple layers of LSTM; a Dropout layer, which is used to prevent the model from overfitting; and an output layer, which is used to output a scheduling control strategy.

[0064] Specifically, since the output is a dispatch control strategy, the cross-entropy loss function (Cross-EntropyLoss) can be used as the optimization target. This function measures the difference between the probability distribution predicted by the model and the actual label. The Adam optimizer or other appropriate gradient descent algorithm can be selected to update the model parameters so that the loss function gradually decreases. The trained model can learn the mapping relationship between the grid load pressure and energy storage priority and the dispatch control strategy, so that a reasonable dispatch strategy can be predicted based on the input data.

[0065] Step S404, verifying the neural network model based on the verification set, evaluating the performance of the neural network model and adjusting the hyperparameters of the model according to the verification results; Among them, the model performance is evaluated based on the performance on the validation set, and the model structure or hyperparameters (such as learning rate, batch size, number of LSTM layers, etc.) are adjusted.

[0066] Step S405, testing the prediction capability of the adjusted neural network model based on the test set to obtain a power supply scheduling model.

[0067] Specifically, the performance of the model on the test set is recorded, including indicators such as MSE and MAE, and the final adjusted model is comprehensively evaluated using the test set to ensure that it also has good performance on unseen data.

[0068] In the above implementation, a power supply dispatching model is constructed and trained, which can automatically output a reasonable dispatching strategy under different load pressure and energy storage status conditions, and realizes the effective mapping from the grid load pressure index and energy storage priority index to the dispatching control strategy. In addition, through a rigorous verification and testing process, it is ensured that the model has good generalization ability and practicality, can play a key role in actual dispatching control, and effectively improves operating efficiency and reliability.

[0069] In addition, during the actual application of the model, the power supply scheduling model can be continuously trained and adjusted based on the reinforcement learning method by obtaining real-time feedback data after the photovoltaic isolation wall system executes the scheduling strategy, so as to obtain an updated scheduling strategy to reduce the waste of power resources and improve the overall efficiency of the system.

[0070] Reference Figure 5 As a further implementation of the energy storage control method, the energy storage control method further includes: Step S501, collecting current solar radiation intensity information; Among them, the current solar radiation intensity can be monitored and recorded in real time through sensors such as solar radiometers installed near photovoltaic modules.

[0071] Step S502, obtaining photovoltaic parameter information of the photovoltaic module; Among them, photovoltaic parameter information includes photovoltaic area, photovoltaic energy storage efficiency and temperature correction coefficient; Specifically, the photovoltaic area is the area of ​​the photovoltaic panel, which can be measured by the area of ​​the photovoltaic panel of the photovoltaic energy storage device. If the photovoltaic panel is installed at an angle, the influence of the tilt angle on the area needs to be considered. The photovoltaic energy storage efficiency refers to the efficiency of the photovoltaic energy storage device in converting solar energy into electrical energy. This value is usually provided by the manufacturer of the photovoltaic energy storage device or obtained through experimental measurements. In addition, since the power generation efficiency will be affected by temperature, the temperature correction coefficient needs to be considered. The temperature correction coefficient can be calculated based on the performance parameters of the photovoltaic panel, which is provided by the manufacturer or obtained through experimental measurements.

[0072] It can be understood that obtaining these parameter information of PV modules can ensure that the system has a comprehensive understanding of the status of PV modules, thereby providing a basis for accurate prediction of power generation and research on matching strategies; Step S503, determining a corresponding photovoltaic power generation prediction value according to current solar radiation intensity information and photovoltaic parameter information; Exemplarily, the calculation formula for the predicted value of photovoltaic power generation is: photovoltaic power generation (E) = photovoltaic area (A) * photovoltaic energy storage efficiency (η1) * temperature correction coefficient (η2) * predicted solar radiation intensity (I).

[0073] In the above formula, E is the photovoltaic power generation, the unit is kilowatt-hour (KWh); A is the photovoltaic area, the unit is square meter (m2); η1 is the photovoltaic energy storage efficiency, no unit; η2 is the temperature correction coefficient, no unit.

[0074] Step S504, determining whether the power generation data of the photovoltaic module exceeds the photovoltaic power generation prediction value; If not, jump to step S505; if yes, do not perform any operation and keep the current state; Step S505, sending a photovoltaic control instruction to the photovoltaic isolation wall system to control and adjust the photovoltaic panels of the photovoltaic components to maintain an optimal light receiving angle.

[0075] It is understandable that when the power generation exceeds the predicted value, it means that the photovoltaic system is operating efficiently, and the scheduling strategy can be adjusted accordingly, such as increasing the power supply to the high-voltage power grid or adjusting the charging and discharging strategy of the energy storage system; when the power generation is lower than the predicted value, there may be adverse factors affecting the power generation efficiency. At this time, the power generation efficiency can be improved by adjusting the angle of the photovoltaic panels.

[0076] In one embodiment of the present application, when calculating the optimal light receiving angle of a photovoltaic panel, real-time illumination information can be obtained, and a model capable of estimating the energy collection efficiency of the photovoltaic panel at different angles is established based on the real-time illumination intensity and real-time illumination direction, combined with the characteristics and performance parameters of the photovoltaic panel itself, and the angle that maximizes the light receiving area of ​​the photovoltaic panel is found by analyzing the relationship between the light receiving area and the energy collection efficiency at different angles. When determining the optimal light receiving angle, factors such as the installation location of the photovoltaic panel, physical limitations (such as the maximum tilt angle), and surrounding environment (such as building shading) must also be considered.

[0077] In the above implementation mode, the power generation of the photovoltaic components is monitored in real time and compared with the predicted value. When the power generation does not reach the expected value, the angle of the photovoltaic panel is automatically adjusted to ensure that the photovoltaic panel is always in the best light receiving state, thereby improving the photovoltaic power generation efficiency and ensuring the efficient operation of the photovoltaic power generation system. This not only helps to improve energy utilization, but also reduces energy costs, which is of great significance for promoting the development and application of clean energy.

[0078] Reference Figure 5 As a further implementation of the energy storage control method, after sending a photovoltaic control instruction to the photovoltaic isolation wall system in step S505 to control and adjust the photovoltaic panels of the photovoltaic assembly to maintain the best light receiving angle, the method further includes: Step S506, determining whether the power generation data of the photovoltaic module exceeds the photovoltaic power generation prediction value after the preset time; if not, jumping to step S507; if yes, no operation is performed and the current state is maintained; Among them, when the power generation in actual circumstances is always lower than the theoretically calculated predicted value for a period of time (i.e. the preset duration), there may be a photovoltaic module failure or other adverse factors affecting the power generation efficiency. At this time, it is necessary to check the working status of the photovoltaic module, for example, check whether the surface of the photovoltaic panel is blocked by dirt, the wiring is loose, the shadow is blocked, or the photovoltaic panel itself has a fault.

[0079] Step S507, determining that the photovoltaic component is in an abnormal state, generating photovoltaic power generation abnormal warning information and sending it to the operation and maintenance terminal.

[0080] Specifically, by sending abnormal warnings to the operation and maintenance terminal, it can ensure that the operation and maintenance team is aware of the abnormal status of the system in the shortest time possible, so that they can quickly take troubleshooting and repair actions.

[0081] In the above implementation, it is determined whether the actual power generation of the photovoltaic module meets the predicted value, and an early warning message is issued when an abnormality occurs. This technical solution can effectively monitor the operating status of the photovoltaic module. It can not only detect potential problems of the module in a timely manner, reduce energy waste, and improve system reliability, but also reduce the huge losses that may be caused by delayed maintenance due to failure to be discovered in time.

[0082] A BIPV photovoltaic isolation wall energy storage control method of the present application can adapt to the discontinuity of photovoltaic power generation and the dynamic changes of high-voltage power grid load in real time by optimizing the management of photovoltaic power generation and energy storage devices, thereby stably and efficiently supplying power to the high-voltage power grid. In practical applications, it is particularly suitable for places with independent power supply and high security protection requirements, such as military facilities, border protection lines, and important material storage depots. By ensuring the safety and reliability of the power supply system through intelligent scheduling, the present application not only improves the energy self-sufficiency and independence of the isolation wall system, but also effectively strengthens the safety protection capabilities of related facilities, which has important practical application significance for ensuring independent operation in remote areas or emergency situations.

[0083] The embodiment of the present application also discloses a BIPV photovoltaic isolation wall energy storage control system.

[0084] A BIPV photovoltaic isolation wall energy storage control system is applied to a photovoltaic isolation wall system, the photovoltaic isolation wall system includes a photovoltaic isolation wall and photovoltaic components, an energy storage device and a high-voltage power grid installed on the photovoltaic isolation wall, the photovoltaic components are used to provide the energy storage device with photovoltaic converted electric energy, the energy storage device is used to store electric energy and supply power to the high-voltage power grid, and the high-voltage power grid is used to perform power-on protection; The energy storage control system includes: A first acquisition module is used to acquire power generation data of the photovoltaic module and charge and discharge status data of the energy storage device; An energy storage priority determination module is used to obtain an energy storage priority index based on power generation data and charge and discharge status data; the energy storage priority index is used to determine the priority of charging the energy storage device or the energy storage device supplying power to the high-voltage power grid; The second acquisition module is used to acquire the operation status monitoring data of the high-voltage power grid; A load pressure determination module is used to obtain a power grid load pressure index based on operation status monitoring data; A strategy generation module is used to input the grid load pressure index and the energy storage priority index into a pre-built power supply scheduling model, and generate a scheduling control strategy according to the output results of the power supply scheduling model; The dispatching control module is used to dispatch and control the photovoltaic isolation wall system according to the dispatching control strategy and adjust the charging and discharging operations of the energy storage device.

[0085] In the above implementation, by establishing an intelligent energy storage control system, the optimized dispatching control of the energy storage device in the photovoltaic isolation wall system is realized. By obtaining the power generation of the photovoltaic components, the charging and discharging status of the energy storage device and the operating status of the high-voltage power grid in real time, the system can dynamically determine the energy storage priority and optimize the charging and discharging operation of the energy storage device under the premise of meeting the load requirements of the power grid. This intelligent control method not only improves the utilization efficiency of the energy storage device and enhances the stability of the power grid, but also effectively prolongs the life of the energy storage device and improves the safety of the entire safety protection system.

[0086] As a further implementation of the energy storage control system, the energy storage control system further includes: A load pressure level determination module is used to determine the load pressure interval according to the load pressure index of the power grid based on a preset pressure mapping table, and determine the corresponding load pressure level according to the load pressure interval; wherein the preset pressure mapping table includes a mapping relationship between multiple groups of load pressure intervals and load pressure levels; A judgment module is used to judge whether the load pressure level exceeds a preset level threshold, and if so, output an abnormal judgment result; The abnormal warning module is used to respond to the abnormal judgment result, determine that the high-voltage power grid is in an abnormal load state, generate load abnormality warning information and send it to the operation and maintenance terminal.

[0087] In the above implementation, by timely identifying potential abnormal load states, potential safety hazards that may occur in the power grid under high load are prevented, thereby improving the management and control efficiency of the safety of power grid operation.

[0088] A BIPV photovoltaic isolation wall energy storage control system of an embodiment of the present application can implement any of the above-mentioned energy storage control methods, and the specific working process of each module in the energy storage control system can refer to the corresponding process in the above-mentioned method embodiment.

[0089] In the several embodiments provided in this application, it should be understood that the provided methods and systems can be implemented in other ways. For example, the system embodiments described above are only illustrative; for example, the division of a certain module is only a logical function division, and there may be other division methods in actual implementation, such as multiple modules can be combined or integrated into another system, or some features can be ignored or not executed.

[0090] The embodiment of the present application also discloses a computer device.

[0091] A computer device includes a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, a BIPV photovoltaic isolation wall energy storage control method as described above is implemented.

[0092] The embodiment of the present application also discloses a computer-readable storage medium.

[0093] A computer-readable storage medium stores a computer program that can be loaded by a processor and executed by any one of the above-mentioned BIPV photovoltaic isolation wall energy storage control methods.

[0094] Among them, computer-readable storage media can be any tangible medium that contains or stores a program, which can be used by or in conjunction with an instruction execution system, apparatus or device; the program code contained on the computer-readable medium can be transmitted using any appropriate medium, including but not limited to wireless, wire, optical cable, RF, etc., or any suitable combination of the above.

[0095] It should be noted that in the above embodiments, the description of each embodiment has different emphases, and for the parts that are not described in detail in a certain embodiment, reference can be made to the relevant descriptions of other embodiments.

[0096] The above are all preferred embodiments of the present application, and are not intended to limit the protection scope of the present application. Any feature disclosed in this specification (including the abstract and drawings), unless otherwise stated, can be replaced by other equivalent or alternative features with similar purposes. That is, unless otherwise stated, each feature is only an example of a series of equivalent or similar features.

Claims

1. A BIPV photovoltaic isolation wall energy storage control method, characterized in that: Applied to a photovoltaic isolation wall system, the photovoltaic isolation wall system includes a photovoltaic isolation wall and a photovoltaic module, an energy storage device and a high-voltage power grid installed on the photovoltaic isolation wall, the photovoltaic module is used to provide the energy storage device with photovoltaic converted electric energy, the energy storage device is used to store electric energy and supply power to the high-voltage power grid, and the high-voltage power grid is used to perform power-on protection; The energy storage control method comprises: Acquiring power generation data of the photovoltaic module and charging and discharging status data of the energy storage device; Based on the power generation data and the charge and discharge status data, an energy storage priority index is obtained; the energy storage priority index is used to determine the priority of charging the energy storage device or the energy storage device supplying power to the high-voltage power grid; Acquiring operating status monitoring data of the high-voltage power grid; Based on the operation status monitoring data, a power grid load pressure index is obtained; Inputting the power grid load pressure index and the energy storage priority index into a pre-built power supply scheduling model, and generating a scheduling control strategy according to the output result of the power supply scheduling model; The photovoltaic isolation wall system is dispatched and controlled according to the dispatching control strategy to adjust the charging and discharging operations of the energy storage device.

2. A BIPV photovoltaic isolation wall energy storage control method according to claim 1, characterized in that: Based on the operation status monitoring data, the step of obtaining the power grid load pressure index comprises: Performing data preprocessing on the operating status monitoring data; Calculate power parameters based on preprocessed status monitoring data and extract dynamic changes; Calculating a voltage stability index, a frequency stability index and a load factor index respectively according to the power parameter and the dynamic change amount; The voltage stability index, frequency stability index and load rate index are weightedly calculated to obtain the power grid load pressure index.

3. A BIPV photovoltaic isolation wall energy storage control method according to claim 2, characterized in that: After the step of obtaining the power grid load pressure index based on the operation status monitoring data, the step further includes: Based on a preset pressure mapping table, the load pressure interval is determined according to the load pressure index of the power grid, and the corresponding load pressure level is determined according to the load pressure interval; wherein the preset pressure mapping table includes a mapping relationship between multiple groups of load pressure intervals and load pressure levels; Determining whether the load pressure level exceeds a preset level threshold; If so, it is determined that the high-voltage power grid is in an abnormal load state, and load abnormality warning information is generated and sent to the operation and maintenance terminal.

4. A BIPV photovoltaic isolation wall energy storage control method according to claim 1, characterized in that: The method further includes a training step of the power supply scheduling model, wherein the training step includes: Acquire a sample data set and perform data preprocessing; wherein the sample data set includes historical power grid load pressure data, historical energy storage priority data, and corresponding historical dispatch control strategies; Dividing the sample data set into a training set, a validation set and a test set; Inputting the training set into a pre-built neural network model for iterative training, optimizing the model parameters and calculating the cross entropy loss function of the model until the cross entropy loss function meets the preset conditions, thereby obtaining a trained neural network model; Validating the neural network model based on the validation set, evaluating the performance of the neural network model and adjusting the hyperparameters of the model according to the validation results; The prediction capability of the adjusted neural network model is tested based on the test set to obtain a power supply scheduling model.

5. A BIPV photovoltaic isolation wall energy storage control method according to claim 1, characterized in that: The energy storage control method further includes: Collect current solar radiation intensity information; Acquiring photovoltaic parameter information of the photovoltaic module; wherein the photovoltaic parameter information includes photovoltaic area, photovoltaic energy storage efficiency and temperature correction coefficient; Determine a corresponding photovoltaic power generation prediction value according to the current solar radiation intensity information and the photovoltaic parameter information; Determining whether the power generation data of the photovoltaic module exceeds the photovoltaic power generation prediction value; If not, a photovoltaic control instruction is sent to the photovoltaic isolation wall system to control and adjust the photovoltaic panels of the photovoltaic components to maintain the best light receiving angle.

6. A BIPV photovoltaic isolation wall energy storage control method according to claim 5, characterized in that: After sending a photovoltaic control instruction to the photovoltaic isolation wall system to control and adjust the photovoltaic panel of the photovoltaic assembly to maintain the best light receiving angle, the step further includes: Determining whether the power generation data of the photovoltaic assembly exceeds the photovoltaic power generation prediction value after a preset time period; If not, it is determined that the photovoltaic component is in an abnormal state, and photovoltaic power generation abnormality warning information is generated and sent to the operation and maintenance terminal.

7. A BIPV photovoltaic isolation wall energy storage control system, characterized in that: Applied to a photovoltaic isolation wall system, the photovoltaic isolation wall system includes a photovoltaic isolation wall and a photovoltaic module, an energy storage device and a high-voltage power grid installed on the photovoltaic isolation wall, the photovoltaic module is used to provide the energy storage device with photovoltaic converted electric energy, the energy storage device is used to store electric energy and supply power to the high-voltage power grid, and the high-voltage power grid is used to perform power-on protection; The energy storage control system comprises: A first acquisition module is used to acquire the power generation data of the photovoltaic module and the charge and discharge status data of the energy storage device; An energy storage priority determination module, used to obtain an energy storage priority index based on the power generation data and the charge and discharge status data; the energy storage priority index is used to determine the priority of charging the energy storage device or the energy storage device supplying power to the high-voltage power grid; A second acquisition module is used to acquire the operating status monitoring data of the high-voltage power grid; A load pressure determination module, used to obtain a power grid load pressure index based on the operation status monitoring data; A strategy generation module, used to input the power grid load pressure index and the energy storage priority index into a pre-built power supply scheduling model, and generate a scheduling control strategy according to the output result of the power supply scheduling model; A scheduling control module is used to schedule and control the photovoltaic isolation wall system according to the scheduling control strategy and adjust the charging and discharging operations of the energy storage device.

8. A BIPV photovoltaic isolation wall energy storage control system according to claim 7, characterized in that: The energy storage control system further includes: A load pressure level determination module, for determining the load pressure interval according to the load pressure index of the power grid based on a preset pressure mapping table, and determining the corresponding load pressure level according to the load pressure interval; wherein the preset pressure mapping table includes a mapping relationship between multiple groups of load pressure intervals and load pressure levels; A judgment module, used to judge whether the load pressure level exceeds a preset level threshold, and if so, output an abnormal judgment result; The abnormal warning module is used to respond to the abnormal judgment result, determine that the high-voltage power grid is in an abnormal load state, generate load abnormality warning information and send it to the operation and maintenance terminal.

9. A computer device, characterized in that: The method comprises a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein when the processor executes the program, the method according to any one of claims 1 to 6 is implemented.

10. A computer-readable storage medium, characterized in that: A computer program is stored which can be loaded by a processor and execute the method according to any one of claims 1 to 6.

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