Distributed photovoltaic group dispatching and group control method and system

Abstract

The invention discloses a distributed photovoltaic group scheduling and group control method and system, and the method comprises the steps: collecting the operation data and environment data of each photovoltaic unit in a distributed photovoltaic cluster, the distributed photovoltaic cluster being distributed in a plurality of geographic regions, each geographic region comprising a plurality of photovoltaic units; according to the operation data and the environment data, calculating a state stability index of each photovoltaic unit, wherein the state stability index represents the stability degree of a photovoltaic operation state; and according to the state stability index, determining a regulation and control level of each geographic area, so that a control center of the distributed photovoltaic cluster implements a group regulation and control strategy corresponding to the regulation and control level of each geographic area. According to the embodiment of the invention, effective management and quick response of different geographic areas can be realized, so that the operation efficiency of a photovoltaic system is improved, the failure rate is reduced, and the safety and stability of a power grid are guaranteed.

Description

Technical Field

[0001] The present invention belongs to the technical field of photovoltaic technology, and particularly relates to a method and system for coordinated control of distributed photovoltaic clusters. Background Art

[0002] With the increasing global demand for renewable energy, photovoltaic power generation, as a clean and efficient form of energy, has developed rapidly. In particular, the popularization of distributed photovoltaic systems has enabled their flexible deployment in various small spaces such as rooftops and buildings. However, distributed photovoltaic systems face many challenges during operation, including difficulties in monitoring, slow risk assessment, and lack of targeted regulation strategies. Existing photovoltaic regulation systems often rely on local data and lack the ability to comprehensively monitor and dynamically manage the entire photovoltaic cluster, resulting in impaired system stability under high load or extreme weather conditions. Summary of the Invention

[0003] The object of the present invention is to provide a method and system for coordinated control of distributed photovoltaic clusters to address the deficiencies in the prior art, enabling effective management and rapid response in different geographical regions, thereby improving the operating efficiency of the photovoltaic system, reducing the failure rate, and ensuring the safety and stability of the power grid.

[0004] An embodiment of the present application provides a method for coordinated control of distributed photovoltaic clusters, the method comprising:

[0005] Collecting the operating data and environmental data of each photovoltaic unit in the distributed photovoltaic cluster, wherein the distributed photovoltaic cluster is distributed in multiple geographical regions, and each geographical region includes multiple photovoltaic units;

[0006] Calculating a state stability index representing the stability degree of the photovoltaic operation state of each photovoltaic unit according to the operating data and the environmental data;

[0007] Determining the regulation level of each geographical region according to the state stability index, so that the control center of the distributed photovoltaic cluster implements the coordinated control strategy corresponding to the regulation level of each geographical region.

[0008] Optionally, the calculation formula of the state stability index is:

[0009]

[0010] Among them, the SSI_i is the state stability index of the i-th photovoltaic unit, P_i(t) is the actual power generation of the i-th photovoltaic unit at time point t, P_{max,i} is the designed maximum power generation of the i-th photovoltaic unit, G_i(t) is the light intensity of the i-th photovoltaic unit at time point t, G_{max,i} is the historical maximum light intensity in the geographical area where the i-th photovoltaic unit is located, T_i(t) is the operating temperature of the i-th photovoltaic unit at time point t, T_{ideal,i} is the ideal operating temperature of the i-th photovoltaic unit, T_{max,i} is the historical maximum value of the ambient temperature of the i-th photovoltaic unit, T_{min,i} is the historical minimum value of the ambient temperature of the i-th photovoltaic unit, H_i is the historical failure times of the i-th photovoltaic unit, H_{ideal,i} is the ideal failure times of the i-th photovoltaic unit, epsilon is a preset small positive number, and w_1, w_2, w_3, and w_4 are corresponding weight coefficients.

[0011] Optionally, determining the regulation level of each geographical area according to the state stability index includes:

[0012] For each geographical area, find the photovoltaic units with state stability indices less than the preset stability threshold in this geographical area as risk photovoltaic units;

[0013] According to the state stability indices of all risk photovoltaic units in this geographical area, calculate the overall risk index representing the risk degree of all risk photovoltaic units in this geographical area;

[0014] According to the pre-constructed mapping relationship table between the overall risk index and the regulation level, determine the regulation level corresponding to the overall risk index of this geographical area.

[0015] Optionally, the regulation levels include: high risk level, medium risk level, and low risk level;

[0016] Implementing the group regulation and control strategy corresponding to the regulation level of each geographical area includes:

[0017] Implement the first regulation strategy for the risk photovoltaic units in each geographical area with a high risk level;

[0018] Implement the second regulation strategy for the risk photovoltaic units in each geographical area with a medium risk level;

[0019] Implement the third regulation strategy for the risk photovoltaic units in each geographical area with a low risk level.

[0020] Another embodiment of the present application provides a distributed photovoltaic group regulation and control system, which includes:

[0021] An acquisition module, configured to acquire the operation data and environmental data of each photovoltaic unit in the distributed photovoltaic cluster, wherein the distributed photovoltaic cluster is distributed in multiple geographical regions, and each geographical region includes multiple photovoltaic units;

[0022] A calculation module, configured to calculate, according to the operation data and the environmental data, a state stability index representing the stability degree of the photovoltaic operation state of each photovoltaic unit;

[0023] A regulation and control module, configured to determine the regulation level of each geographical region according to the state stability index, so that the control center of the distributed photovoltaic cluster implements the group regulation and control strategy corresponding to the regulation level of each geographical region.

[0024] Another embodiment of the present application provides a storage medium, in which a computer program is stored, and the computer program is configured to execute the method described in any one of the above when running.

[0025] Another embodiment of the present application provides an electronic device, including a memory and a processor, wherein a computer program is stored in the memory, and the processor is configured to run the computer program to execute the method described in any one of the above.

[0026] Compared with the prior art, a distributed photovoltaic group regulation and control method provided by the present invention acquires the operation data and environmental data of each photovoltaic unit in the distributed photovoltaic cluster, wherein the distributed photovoltaic cluster is distributed in multiple geographical regions, and each geographical region includes multiple photovoltaic units; calculates, according to the operation data and the environmental data, a state stability index representing the stability degree of the photovoltaic operation state of each photovoltaic unit; determines the regulation level of each geographical region according to the state stability index, so that the control center of the distributed photovoltaic cluster implements the group regulation and control strategy corresponding to the regulation level of each geographical region, thereby enabling effective management and rapid response of different geographical regions, improving the operation efficiency of the photovoltaic system, reducing the failure rate, and ensuring the safety and stability of the power grid. BRIEF DESCRIPTION OF THE DRAWINGS

[0027] Figure 1 It is a hardware structure block diagram of a computer terminal for a distributed photovoltaic group regulation and control method provided by an embodiment of the present invention;

[0028] Figure 2 It is a flowchart of a distributed photovoltaic group regulation and control method provided by an embodiment of the present invention;

[0029] Figure 3Schematic structural diagram of a distributed photovoltaic group regulation and control system provided by an embodiment of the present invention. Detailed implementation manners

[0030] The embodiments described below with reference to the accompanying drawings are exemplary and are only used to explain the present invention, and should not be construed as limiting the present invention.

[0031] An embodiment of the present invention first provides a distributed photovoltaic group regulation and control method, which can be applied to an electronic device, such as a computer terminal, specifically, a general computer, etc.

[0032] The following takes running on a computer terminal as an example to describe it in detail. Figure 1 Hardware structure block diagram of a computer terminal for a distributed photovoltaic group regulation and control method provided by an embodiment of the present invention. As Figure 1 shown, the computer device includes a processor, a memory, and a network interface connected through a system bus. Among them, the memory may include a non-volatile storage medium and an internal memory.

[0033] The non-volatile storage medium can store an operating system and a computer program. The computer program includes program instructions, and when the program instructions are executed, the processor can execute any distributed photovoltaic group regulation and control method.

[0034] The processor is used to provide computing and control capabilities to support the operation of the entire computer device.

[0035] The internal memory provides an environment for the operation of the computer program in the non-volatile storage medium. When the computer program is executed by the processor, the processor can execute any distributed photovoltaic group regulation and control method.

[0036] The network interface is used for network communication, such as sending assigned tasks, etc. Those skilled in the art can understand that Figure 1 the structure shown in is only a block diagram of a part of the structure related to the solution of the present application, and does not constitute a limitation on the computer device to which the solution of the present application is applied. The specific computer device may include more or fewer components than those shown in the figure, or combine some components, or have different component arrangements.

[0037] It should be understood that the processor can be a Central Processing Unit (CPU), and the processor can also be other general-purpose processors, Digital Signal Processors (DSPs), Application Specific Integrated Circuits (ASICs), Field-Programmable Gate Arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. Among them, the general-purpose processor can be a microprocessor or the processor can also be any conventional processor, etc.

[0038] See Figure 2 , embodiments of the present invention provide a distributed photovoltaic group regulation and control method, which may include the following steps:

[0039] S201, collect the operation data and environmental data of each photovoltaic unit in the distributed photovoltaic cluster, where the distributed photovoltaic cluster is distributed in multiple geographical regions, and each geographical region includes multiple photovoltaic units;

[0040] In the distributed photovoltaic group regulation and control method, the first step involves comprehensively collecting the operation data and environmental data of each photovoltaic unit in the distributed photovoltaic cluster. This process not only covers the real-time power generation power and working temperature of each photovoltaic unit, but also includes light intensity, wind speed, humidity, and other environmental factors. The acquisition of these data can be achieved through sensors and monitoring devices installed on each photovoltaic unit, and these devices can transmit data to the control center in real time for analysis. The distributed photovoltaic cluster is usually distributed in different geographical regions, and each region may have different weather conditions and environmental characteristics. Therefore, comprehensively collecting these data is the basis for ensuring the efficient operation of photovoltaic units.

[0041] By collecting the operation data and environmental data of each photovoltaic unit in the distributed photovoltaic cluster, a reliable basis can be provided for the subsequent calculation of the state stability index. Accurate operation and environmental data can help the system evaluate the actual power generation capacity and operation status of each photovoltaic unit, thereby identifying potential risk photovoltaic units. This process not only improves the intelligent management level of the photovoltaic system, but also lays a foundation for implementing more efficient group regulation and control strategies, promotes the stability and efficiency of photovoltaic power generation, improves the overall energy utilization rate, and further realizes the sustainable development of renewable energy.

[0042] In the specific implementation process, first, a variety of sensors are equipped for each photovoltaic unit to facilitate real-time monitoring of its operating status and environmental conditions. The types of these sensors may include power sensors, temperature sensors, light sensors, etc. These sensors will collect operating data and environmental data in real time and transmit the data to the cloud control system through a wireless communication network. The control system will process and store the received data to establish an operating database for each photovoltaic unit. The data collection frequency can be optimized according to the operating characteristics of the photovoltaic unit. For example, the collection frequency can be increased during high-light periods to obtain more real-time data. In the data processing stage, the control center will clean and analyze the data, identify data anomalies and mark them to ensure the accuracy of subsequent calculations. Finally, the collected data will be used to calculate the state stability index of each photovoltaic unit, providing basic support for determining the regulation level of each geographical area and effectively improving the overall operating efficiency and safety of the photovoltaic cluster through the group regulation and control strategy.

[0043] S202, calculate the state stability index representing the stability degree of the photovoltaic operation for each photovoltaic unit according to the operating data and the environmental data;

[0044] Calculating the state stability index (SSI) of each photovoltaic unit according to the operating data and environmental data is an important process. By comprehensively evaluating the actual power generation capacity, environmental adaptability, and failure risk of the photovoltaic unit, it provides data support for subsequent regulation decisions. This process first requires collecting historical data on the actual power generation, light intensity, working temperature, and environmental temperature of each photovoltaic unit at specific time points. Then, through the analysis and processing of these data, the operating effect of the photovoltaic unit under the current environmental conditions can be quantified. The state stability index not only reflects the current operating state of the photovoltaic unit but also judges its stability by comparing with historical records, thus providing a basis for formulating the regulation strategy of the overall photovoltaic cluster. The calculation of this part not only enhances the intelligent level of the system but also ensures the sustainability and efficiency of photovoltaic power generation.

[0045] Calculating the state stability index (SSI) of each photovoltaic unit has important practical significance. This index provides a quantitative basis for judging the operating health status of the photovoltaic unit, can timely identify abnormal operating units, and thus take appropriate regulation measures to reduce the failure risk. In addition, the calculation of SSI helps to optimize the overall scheduling of the distributed photovoltaic cluster, improve the power generation efficiency, and maximize the resource utilization rate. By evaluating the state stability of each unit, the control center can achieve more accurate group regulation and control, reduce the failure rate and losses, and ultimately improve the economy and reliability of the photovoltaic power generation system, thereby contributing to the development of sustainable energy.

[0046] In the specific implementation process, it is first necessary to construct an intelligent monitoring system, which consists of a variety of sensors that can continuously obtain the operating data and environmental data of each photovoltaic unit. Data such as the actual power generation (P_i(t)), light intensity (G_i(t)), and operating temperature (T_i(t)) of the photovoltaic unit will be continuously collected and transmitted to the data processing center. In the data processing stage, the system will clean and preprocess the acquired data, removing outliers and noise data to ensure data accuracy. Then, the system will calculate the state stability index (SSI) of each photovoltaic unit according to the designed calculation formula, comprehensively considering the actual output of the photovoltaic unit, its adaptability to the designed capacity, light conditions, and the deviation degree of the operating temperature. At the same time, the historical failure times of each photovoltaic unit are statistically analyzed using historical data to ensure the comprehensiveness and accuracy of the calculation. After the calculation is completed, the system will analyze the SSI results, identify the photovoltaic units with a state stability index lower than the preset threshold, and mark these units as risk photovoltaic units. Finally, based on the state stability index of these risk units, the control center can better formulate a group regulation and control strategy, thereby optimizing the operating efficiency of the entire photovoltaic cluster. Through this process, by combining real-time data and historical data, it is possible to provide a scientific basis for the regulation and control decisions of distributed photovoltaic clusters.

[0047] Specifically, a calculation formula for the state stability index can be:

[0048]

[0049] Among them, SSI_i is the state stability index of the i-th photovoltaic unit, P_i(t) is the actual power generation of the i-th photovoltaic unit at time point t, P_{max,i} is the designed maximum power generation of the i-th photovoltaic unit, G_i(t) is the light intensity of the i-th photovoltaic unit at time point t, G_{max,i} is the historical maximum light intensity in the geographical area where the i-th photovoltaic unit is located, T_i(t) is the operating temperature of the i-th photovoltaic unit at time point t, T_{ideal,i} is the ideal operating temperature of the i-th photovoltaic unit, T_{max,i} is the historical maximum value of the environmental temperature of the i-th photovoltaic unit, T_{min,i} is the historical minimum value of the environmental temperature of the i-th photovoltaic unit, H_i is the historical failure times of the i-th photovoltaic unit, H_{ideal,i} is the ideal failure times of the i-th photovoltaic unit, epsilon is a preset small positive number, and w_1, w_2, w_3, w_4 are corresponding weight coefficients.

[0050] The design formula of the State Stability Index (SSI) reflects the comprehensive performance of photovoltaic units under various environmental and operating conditions, and its constituent elements each have their own significance. Each part of the formula plays a different role, ensuring a comprehensive assessment of the state of photovoltaic units:

[0051] This term reflects the ratio between the actual power generation of the i-th photovoltaic unit at a specific time t and its designed maximum power generation, directly measuring the power generation efficiency of the photovoltaic unit. If the power generation is close to its designed maximum value, it indicates that the unit is operating well.

[0052] This item represents the ratio of the light intensity of the i-th photovoltaic unit at time t to the historical maximum light intensity in this area, reflecting the impact of light conditions on the power generation capacity. Appropriate light intensity helps to improve the power generation efficiency of photovoltaic units.

[0053] This term calculates the deviation degree between the current operating temperature and the ideal operating temperature. The closer it is to the ideal operating temperature, the closer this value is to 1, indicating that the photovoltaic unit has better adaptability to the ambient temperature. Too high or too low temperature will affect the performance of the photovoltaic unit.

[0054] This term measures the ratio of the historical failure times of the i-th photovoltaic unit to the ideal failure times, reflecting the historical stability of the photovoltaic unit. By adding a small positive number epsilon, the calculation instability when the number of failure times is zero is avoided.

[0055] w_1, w_2, w_3, w_4: These weight coefficients are used to reflect the importance of each parameter in the calculation of the state stability index and can be adjusted according to the needs of the actual scenario to highlight the impact of different operating conditions on the system stability.

[0056] In summary, the calculation formula of SSI comprehensively integrates the power generation capacity, environmental adaptability, and historical operating stability of photovoltaic units, providing a basis for quantitative assessment, making the subsequent regulation strategies more targeted and effective.

[0057] S203. According to the state stability index, determine the regulation level of each geographical area, so that the control center of the distributed photovoltaic cluster can implement the group regulation and control strategy corresponding to the regulation level of each geographical area.

[0058] Determining the regulation level for each geographical area based on the State Stability Index (SSI) is a crucial step in the overall distributed PV group regulation and control method. By analyzing the SSI of each PV unit, the control center can accurately evaluate the stability and health status of PV units within each geographical area, and further classify these areas into different regulation levels. The regulation levels are divided into high-risk, medium-risk, and low-risk levels according to the operating status of PV units and environmental impacts. Using these regulation levels, the control center can implement corresponding group regulation and control strategies targeted to ensure the operating efficiency and safety of the PV cluster.

[0059] The significance of this step is that it ensures real-time monitoring and analysis of the operating conditions of PV units within each geographical area, providing decision-making support for the intelligent management of the PV cluster. Through the clear classification of the regulation levels of geographical areas, the control center can effectively allocate resources, focus on key monitoring and regulation of high-risk areas, thereby reducing the risk of failures, improving the safety and reliability of overall PV power generation, and promoting the stable development of renewable energy.

[0060] Specifically, to determine the regulation level for each geographical area according to the State Stability Index, for each geographical area, PV units with a State Stability Index less than a preset stability threshold within this geographical area can be found as risk PV units;

[0061] This step aims to conduct a detailed analysis of PV units within each geographical area to identify those with poor operating conditions. The State Stability Index (SSI) of these PV units is lower than the preset threshold, indicating that their power generation capacity is affected by environmental factors or internal failures. Through this method, the control center can quickly locate potential risk PV units for subsequent regulation measures.

[0062] The implementation of this step has an important early warning effect. By detecting problem PV units early, the control center can intervene in a timely manner before the problems spread, avoid the occurrence of serious failures, and thus ensure the overall power generation efficiency and safety of the PV cluster.

[0063] The control center first screens and classifies the PV units in each geographical area based on the State Stability Index data obtained from the real-time monitoring system. By setting an appropriate threshold, the system automatically marks PV units with an SSI lower than this threshold as risk units. For this purpose, the control center can use data visualization tools to display the status of each PV unit, helping operators quickly identify the location and quantity of risk PV units and providing basic data for subsequent analysis.

[0064] Calculate the overall risk index representing the risk levels of all risky PV units within the geographical area based on the status stability indices of all risky PV units within the geographical area;

[0065] After identifying the risky PV units, the next step is to quantify the overall risk levels of these units. By calculating the status stability indices of all risky PV units within the area, the control center can derive an index representing the overall risk level within the geographical area. This overall risk index will provide an important basis for determining the regulation levels. By calculating the overall risk index, the control center can comprehensively evaluate the operating risk level of a specific geographical area. This not only helps in formulating targeted regulation strategies but also provides a scientific basis for subsequent resource allocation to ensure the stable operation of the PV cluster.

[0066] Statistical analysis can be performed on the SSI values of all PV units marked as risky. For example, methods such as weighted summation, weighted averaging, or direct averaging can be used to calculate the overall risk index, and the calculation results will be recorded in the database as the basic data for subsequent decision-making.

[0067] Determine the regulation level corresponding to the overall risk index of the geographical area according to the pre-constructed mapping relationship table between the overall risk index and the regulation levels.

[0068] After obtaining the overall risk index for each area, the control center will use the pre-set mapping relationship table to determine the corresponding regulation levels. This mapping table correlates the overall risk index with high, medium, and low risk levels. Through this mechanism, the control center can effectively classify the risk situations of each area and thus decide on the regulation measures to be taken.

[0069] The implementation of this mapping mechanism ensures that the regulation measures are adjusted according to the actual risk levels, enabling differential management. By reasonably dividing the regulation levels, resources can be utilized more efficiently, concentrating efforts on high-risk areas and optimizing the operating efficiency and safety of the overall PV cluster.

[0070] The control center can construct a mapping relationship table associating different intervals of the overall risk index with the corresponding regulation levels (such as high risk, medium risk, low risk). By comparing the calculation results of the risk index, the control center can quickly classify each geographical area into the corresponding regulation level. This information will be transmitted to the dispatching system for implementing the corresponding group regulation and control strategies. For example, high-risk areas may require immediate technical inspections and maintenance, while low-risk areas can maintain normal operation.

[0071] Among them, the regulation levels can include: high-risk level, medium-risk level, and low-risk level. The regulation levels include high-risk level, medium-risk level, and low-risk level. These three risk levels are determined by evaluating the state stability index of all risk photovoltaic units within each geographical area. A risk photovoltaic unit refers to a photovoltaic unit whose state stability index (SSI) is less than a preset stability threshold. Photovoltaic units with a low-risk level, although relatively low in risk assessment, still have certain risks and cannot be considered to have good operating conditions. A risk-free photovoltaic unit refers to a unit whose state stability index is higher than the preset threshold, indicating that these photovoltaic units have good operating states, no obvious risks, and can operate safely and stably.

[0072] By classifying the risk levels of photovoltaic units, more refined management and resource allocation can be achieved. The identification of the high-risk level enables the control center to prioritize the processing of those photovoltaic units that may cause major failures or safety hazards; the medium-risk level photovoltaic units need to be regularly monitored and maintained to prevent the risk from increasing; the low-risk level photovoltaic units need to be continuously monitored to avoid potential problems. Risk-free photovoltaic units can operate with confidence, and the system can concentrate resources on the maintenance of high- and medium-risk photovoltaic units, thereby improving the operation efficiency and safety of the overall photovoltaic cluster.

[0073] Implementing the group regulation and control strategy corresponding to the regulation level of each geographical area can implement the first regulation strategy for the risk photovoltaic units in each geographical area with a high-risk level;

[0074] The first regulation strategy mainly targets those photovoltaic units evaluated as having a high-risk level. These units have a relatively high probability of failure and may affect the operation safety of the entire photovoltaic cluster. When implementing this strategy, the control center needs to respond quickly and reduce the probability of failure by increasing the monitoring and maintenance frequency of these high-risk photovoltaic units. This includes conducting emergency inspections, troubleshooting, and necessary repairs to ensure that these risk photovoltaic units can return to the normal operating state in the shortest possible time.

[0075] By implementing the first regulation strategy, the control center can effectively reduce the failure rate of high-risk photovoltaic units, avoid potential safety hazards and economic losses. This timely intervention measure not only protects the equipment and investment but also ensures the overall stability and reliability of the photovoltaic cluster, thereby improving the operation efficiency of the system.

[0076] Once the control center identifies high-risk photovoltaic units, it will immediately arrange for technicians to conduct a comprehensive on-site inspection of these units. The inspection content includes the physical state of the equipment, connections, and electrical performance, etc. At the same time, technicians will use online monitoring tools to track the operation data of the photovoltaic units and evaluate their actual power generation situation. Once a device failure is detected, the control center will immediately initiate a repair procedure, which may include replacing faulty components, updating the software system, or performing other necessary technical interventions. Throughout the process, managers need to record every step of the inspection and maintenance in a timely manner for subsequent analysis and evaluation of the strategy's effectiveness.

[0077] Implement the second control strategy for risk photovoltaic units in each geographical area with a medium-risk level of regulation;

[0078] The second control strategy is specifically for those photovoltaic units evaluated to be at a medium-risk level. The status of these units is relatively good, but there is still room for improvement due to certain factors. The implementation of this strategy mainly focuses on regular monitoring and maintenance to ensure that the performance of these photovoltaic units does not deteriorate further. The control center will formulate an updated monitoring plan, and by analyzing the operation data of the photovoltaic units, potential problems can be detected in a timely manner to prevent the escalation of risks.

[0079] By implementing the second control strategy, the control center can effectively reduce the failure probability of medium-risk photovoltaic units. This preventive maintenance measure can identify problems existing in the equipment in a timely manner and repair them before an actual failure occurs, thereby extending the service life of the photovoltaic units and improving the overall performance of the system.

[0080] The control center will regularly collect the operation data of medium-risk photovoltaic units, including information such as power generation, temperature, and light intensity, and conduct data analysis. Data analysts will judge the operation status of the photovoltaic units based on the analysis results and update the maintenance plan accordingly. If anomalies are found in the operation data of certain photovoltaic units, technicians will arrange on-site inspections for fault troubleshooting and maintenance. In addition, the control center will also implement an early warning mechanism to ensure that when the operation parameters deviate from the normal range, actions can be taken promptly to adjust or repair the equipment.

[0081] Implement the third control strategy for risk photovoltaic units in each geographical area with a low-risk level of regulation.

[0082] The third control strategy is mainly applicable to photovoltaic units evaluated to be at a low-risk level. The operation conditions of these units are usually relatively stable, but a certain degree of monitoring is still required to prevent potential problems from occurring. The core of this strategy lies in continuous monitoring and optimized management, aiming to explore methods and measures to further improve the operation efficiency while ensuring the normal operation of each photovoltaic unit.

[0083] By implementing the third regulation strategy, the control center can effectively maintain the good operation state of low-risk photovoltaic units and identify opportunities for optimization in daily management. This strategy ensures the reliability of the system and provides the possibility to achieve higher power generation efficiency and economic benefits.

[0084] The control center will set a schedule for regular audits, analyze the historical operation data of low-risk photovoltaic units and conduct performance evaluations. Management personnel will focus on the power generation efficiency and fault records of photovoltaic units and formulate optimization measures, such as updating equipment, adjusting operation parameters or improving maintenance processes. Through the data monitoring system, the control center maintains comprehensive monitoring of photovoltaic units and can adjust strategies in a timely manner when any data anomalies occur. In addition, the control center will organize regular review meetings to discuss the operation performance of photovoltaic units and optimization suggestions, so as to ensure continuous improvement and enhancement of the system efficiency during operation.

[0085] Exemplarily, the first regulation strategy: the regulation strategy for high-risk levels

[0086] Specific strategy content: 1. Emergency fault inspection: Immediately dispatch a technical team to conduct on-site fault inspections on all photovoltaic units evaluated as high-risk. The inspection content includes the integrity of inverters, cable connections, photovoltaic panels and brackets to ensure there are no obvious signs of damage or aging.

[0087] 2. Real-time data monitoring: Implement real-time data monitoring of high-risk photovoltaic units, establish a direct connection with the monitoring system, and receive the power generation power, working temperature and environmental parameters of photovoltaic units in real time. The monitoring system should be configured with an alarm mechanism, and once the data exceeds the normal range, immediately notify technical personnel for intervention.

[0088] 3. Priority repair and replacement: If faults are found in high-risk photovoltaic units during inspections, give priority to repairing or replacing damaged components. Ensure that all replacement components are original products during repair to guarantee the long-term stability of photovoltaic units.

[0089] 4. Develop an emergency response plan: For high-risk photovoltaic units, develop an emergency response plan, including the handling process, responsible persons, time expectations and required resources after a fault occurs, to ensure a quick and effective response when problems occur.

[0090] 5. Regular evaluation and adjustment: Regularly evaluate the status and repair records of high-risk units and adjust the corresponding monitoring and maintenance strategies in a timely manner to improve management efficiency.

[0091] The second regulation strategy: the regulation strategy for medium-risk levels

[0092] Specific strategy content: 1. Regular data analysis: Implement weekly data collection and analysis for medium-risk photovoltaic units, including power generation, temperature, and ambient light intensity, to ensure potential fault signs can be detected.

[0093] 2. Preventive maintenance: Conduct preventive maintenance on medium-risk photovoltaic units, including regular cleaning of photovoltaic panels, replacement of vulnerable parts (such as cable connectors), and detection of the electrical performance of inverters to ensure they operate in an efficient state.

[0094] 3. Establish a warning mechanism: Set up a threshold warning mechanism through the monitoring system. When the operating parameters of photovoltaic units are abnormal, the system will automatically alert relevant technicians and trigger a preset inspection procedure.

[0095] 4. Training and technical support: Regularly provide technical training to on-site operators to improve their professional skills and troubleshooting abilities, ensuring they can detect and handle problems in a timely manner.

[0096] 5. Conduct mild inspections: In addition to regular maintenance, conduct mild inspections (such as visual inspections and simple performance tests) on medium-risk photovoltaic units to ensure small problems can be detected in a timely manner without disturbing normal operation.

[0097] The third regulation strategy: Regulation strategy for low-risk levels

[0098] Specific strategy content: 1. Set up a regular audit plan: For low-risk photovoltaic units, formulate a monthly status audit plan, and the audit content includes the power generation efficiency of equipment, environmental data, and fault records.

[0099] 2. Optimize management processes: Continuously review the operation of photovoltaic units, explore and implement management optimization measures, such as adjusting the tilt angle of photovoltaic panels or optimizing their positions to maximize light utilization.

[0100] 3. Data trend analysis: Through trend analysis of the historical data of photovoltaic units, identify which photovoltaic units show obvious trend changes for more detailed monitoring.

[0101] 4. Improve power generation efficiency: Regularly explore new technologies or new equipment, such as higher-efficiency photovoltaic panels and more intelligent inverters, and gradually replace existing equipment to further enhance the power generation capacity of photovoltaic units.

[0102] 5. User feedback and usage suggestions: Establish a communication mechanism with users to obtain feedback on photovoltaic units and provide targeted optimization suggestions based on users' usage conditions to ensure that photovoltaic units can always meet usage requirements.

[0103] Through these specific strategic contents, the first, second, and third regulation strategies can be effectively distinguished and implemented in actual operation, ensuring that photovoltaic units with different risk levels can obtain appropriate management and maintenance according to their characteristics.

[0104] It can be seen that the operation data and environmental data of each photovoltaic unit in the distributed photovoltaic cluster are collected, where the distributed photovoltaic cluster is distributed in multiple geographical regions, and each geographical region includes multiple photovoltaic units; according to the operation data and the environmental data, the state stability index representing the stability degree of the photovoltaic operation state of each photovoltaic unit is calculated; according to the state stability index, the regulation level of each geographical region is determined, so that the control center of the distributed photovoltaic cluster can implement the group regulation and control strategy corresponding to the regulation level of each geographical region, thereby enabling effective management and rapid response in different geographical regions, improving the operation efficiency of the photovoltaic system, reducing the failure rate, and ensuring the safety and stability of the power grid.

[0105] Another embodiment of the present invention provides a distributed photovoltaic group regulation and control system. Refer to Figure 3 , the system may include:

[0106] A collection module 301 for collecting the operation data and environmental data of each photovoltaic unit in the distributed photovoltaic cluster, where the distributed photovoltaic cluster is distributed in multiple geographical regions, and each geographical region includes multiple photovoltaic units;

[0107] A calculation module 302 for calculating the state stability index representing the stability degree of the photovoltaic operation state of each photovoltaic unit according to the operation data and the environmental data;

[0108] A regulation module 303 for determining the regulation level of each geographical region according to the state stability index, so that the control center of the distributed photovoltaic cluster can implement the group regulation and control strategy corresponding to the regulation level of each geographical region.

[0109] It can be seen that the operation data and environmental data of each photovoltaic unit in the distributed photovoltaic cluster are collected, where the distributed photovoltaic cluster is distributed in multiple geographical regions, and each geographical region includes multiple photovoltaic units; according to the operation data and the environmental data, the state stability index representing the stability degree of the photovoltaic operation state of each photovoltaic unit is calculated; according to the state stability index, the regulation level of each geographical region is determined, so that the control center of the distributed photovoltaic cluster can implement the group regulation and control strategy corresponding to the regulation level of each geographical region, thereby enabling effective management and rapid response in different geographical regions, improving the operation efficiency of the photovoltaic system, reducing the failure rate, and ensuring the safety and stability of the power grid.

[0110] An embodiment of the present invention further provides a storage medium, in which a computer program is stored, and the computer program is configured to execute the steps in any one of the above method embodiments when running.

[0111] Specifically, in this embodiment, the above storage medium may be configured to store a computer program for executing the following steps:

[0112] S201, collect the operation data and environmental data of each photovoltaic unit in the distributed photovoltaic cluster, where the distributed photovoltaic cluster is distributed in multiple geographical regions, and each geographical region includes multiple photovoltaic units;

[0113] S202, calculate the state stability index representing the stability degree of the photovoltaic operation state of each photovoltaic unit according to the operation data and the environmental data;

[0114] S203, determine the regulation level of each geographical region according to the state stability index, so that the control center of the distributed photovoltaic cluster implements the group regulation and control strategy corresponding to the regulation level of each geographical region.

[0115] It can be seen that by collecting the operation data and environmental data of each photovoltaic unit in the distributed photovoltaic cluster, where the distributed photovoltaic cluster is distributed in multiple geographical regions and each geographical region includes multiple photovoltaic units; calculating the state stability index representing the stability degree of the photovoltaic operation state of each photovoltaic unit according to the operation data and the environmental data; and determining the regulation level of each geographical region according to the state stability index, so that the control center of the distributed photovoltaic cluster implements the group regulation and control strategy corresponding to the regulation level of each geographical region, it is possible to achieve effective management and rapid response in different geographical regions, thereby improving the operation efficiency of the photovoltaic system, reducing the failure rate, and ensuring the safety and stability of the power grid.

[0116] An embodiment of the present invention further provides an electronic device, including a memory and a processor, where a computer program is stored in the memory, and the processor is configured to run the computer program to execute the steps in any one of the above method embodiments.

[0117] Specifically, the above electronic device may further include a transmission device and an input / output device, where the transmission device is connected to the above processor, and the input / output device is connected to the above processor.

[0118] Specifically, in this embodiment, the above processor may be configured to execute the following steps through a computer program:

[0119] S201. Collect the operation data and environmental data of each photovoltaic unit in the distributed photovoltaic cluster, where the distributed photovoltaic cluster is distributed in multiple geographical regions, and each geographical region includes multiple photovoltaic units.

[0120] S202. Calculate the state stability index representing the stability degree of the photovoltaic operation state of each photovoltaic unit according to the operation data and the environmental data.

[0121] S203. Determine the regulation level of each geographical region according to the state stability index, so that the control center of the distributed photovoltaic cluster can implement the group regulation and control strategy corresponding to the regulation level of each geographical region.

[0122] It can be seen that by collecting the operation data and environmental data of each photovoltaic unit in the distributed photovoltaic cluster, where the distributed photovoltaic cluster is distributed in multiple geographical regions and each geographical region includes multiple photovoltaic units; calculating the state stability index representing the stability degree of the photovoltaic operation state of each photovoltaic unit according to the operation data and the environmental data; and determining the regulation level of each geographical region according to the state stability index, so that the control center of the distributed photovoltaic cluster can implement the group regulation and control strategy corresponding to the regulation level of each geographical region, it is possible to achieve effective management and rapid response in different geographical regions, thereby improving the operation efficiency of the photovoltaic system, reducing the failure rate, and ensuring the safety and stability of the power grid.

[0123] The structure, features and effects of the present invention have been described in detail based on the embodiments shown in the drawings. The above is only the preferred embodiment of the present invention, but the present invention is not limited to the scope shown in the drawings. Any changes made according to the concept of the present invention, or modified into equivalent embodiments with equivalent changes, still within the spirit covered by the specification and the drawings, shall be within the protection scope of the present invention.

Claims

1. A distributed photovoltaic group control method, characterized in that: The method comprises: Collecting operation data and environmental data of each photovoltaic unit in a distributed photovoltaic cluster, wherein the distributed photovoltaic cluster is distributed in a plurality of geographical regions, each of which includes a plurality of photovoltaic units; Calculating a state stability index of each photovoltaic unit indicating a stability degree of photovoltaic operation state according to the operation data and the environmental data; According to the state stability index, the regulation level of each geographical area is determined so that the control center of the distributed photovoltaic cluster implements the group regulation and control strategy corresponding to the regulation level of each geographical area.

2. The method according to claim 1, characterized in that The calculation formula of the state stability index is: Wherein, the SSI_i is the state stability index of the i-th photovoltaic unit, the P_i(t) is the actual power generation of the i-th photovoltaic unit at time point t, the P_{max,i} is the designed maximum power generation of the i-th photovoltaic unit, the G_i(t) is the light intensity of the i-th photovoltaic unit at time point t, the G_{max,i} is the historical maximum light intensity in the geographical area where the i-th photovoltaic unit is located, the T_i(t) is the operating temperature of the i-th photovoltaic unit at time point t, and the T_{id wherein T_{eal,i} is the ideal operating temperature of the ith photovoltaic unit, T_{max,i} is the historical maximum value of the ambient temperature of the ith photovoltaic unit, T_{min,i} is the historical minimum value of the ambient temperature of the ith photovoltaic unit, H_i is the historical number of failures of the ith photovoltaic unit, H_{ideal,i} is the ideal number of failures of the ith photovoltaic unit, epsilon is a preset small positive number, and w_1, w_2, w_3, and w_4 are corresponding weight coefficients.

3. The method according to claim 2, characterized in that Determining the regulation level of each geographical area according to the state stability index includes: For each geographical area, searching for photovoltaic units in the geographical area whose state stability index is less than a preset stability threshold value as risk photovoltaic units; Calculate an overall risk index representing the risk level of all risk photovoltaic units in the geographical area according to the state stability index of all risk photovoltaic units in the geographical area; According to the pre-constructed mapping relationship table between the overall risk index and the regulation level, the regulation level corresponding to the overall risk index of the geographical area is determined.

4. The method according to claim 3, characterized in that The control levels include: high risk level, medium risk level and low risk level; The group control strategy corresponding to the control level of each geographical area includes: implementing a first regulation strategy for risky photovoltaic units in each geographical area where the regulation level is a high risk level; Implementing a second regulation strategy for risky PV units in each geographic area with a regulation level of medium risk; A third regulation strategy is implemented for risky photovoltaic units in each geographical area where the regulation level is a low risk level.

5. A distributed photovoltaic group control system, characterized in that: The system comprises: A collection module, used to collect operation data and environmental data of each photovoltaic unit in a distributed photovoltaic cluster, wherein the distributed photovoltaic cluster is distributed in a plurality of geographical areas, and each geographical area includes a plurality of photovoltaic units; A calculation module, used for calculating a state stability index of each photovoltaic unit indicating a stability degree of photovoltaic operation state according to the operation data and the environmental data; The control module is used to determine the control level of each geographical area according to the state stability index, so that the control center of the distributed photovoltaic cluster implements the group control strategy corresponding to the control level of each geographical area.

6. The system according to claim 5, characterized in that The calculation formula of the state stability index is: Wherein, the SSI_i is the state stability index of the i-th photovoltaic unit, the P_i(t) is the actual power generation of the i-th photovoltaic unit at time point t, the P_{max,i} is the designed maximum power generation of the i-th photovoltaic unit, the G_i(t) is the light intensity of the i-th photovoltaic unit at time point t, the G_{max,i} is the historical maximum light intensity in the geographical area where the i-th photovoltaic unit is located, the T_i(t) is the operating temperature of the i-th photovoltaic unit at time point t, and the T_{id wherein T_{eal,i} is the ideal operating temperature of the ith photovoltaic unit, T_{max,i} is the historical maximum value of the ambient temperature of the ith photovoltaic unit, T_{min,i} is the historical minimum value of the ambient temperature of the ith photovoltaic unit, H_i is the historical number of failures of the ith photovoltaic unit, H_{ideal,i} is the ideal number of failures of the ith photovoltaic unit, epsilon is a preset small positive number, and w_1, w_2, w_3, and w_4 are corresponding weight coefficients.

7. The system according to claim 6, characterized in that The control module is specifically used for: For each geographical area, searching for photovoltaic units in the geographical area whose state stability index is less than a preset stability threshold value as risk photovoltaic units; Calculate an overall risk index representing the risk level of all risk photovoltaic units in the geographical area according to the state stability index of all risk photovoltaic units in the geographical area; According to the pre-constructed mapping relationship table between the overall risk index and the regulation level, the regulation level corresponding to the overall risk index of the geographical area is determined.

8. The system according to claim 7, characterized in that The control levels include: high risk level, medium risk level and low risk level; the control module is specifically used to: implementing a first regulation strategy for risky photovoltaic units in each geographical area where the regulation level is a high risk level; Implementing a second regulation strategy for risky PV units in each geographic area with a regulation level of medium risk; A third regulation strategy is implemented for risky photovoltaic units in each geographical area where the regulation level is a low risk level.

9. A storage medium, characterized in that: The storage medium stores a computer program, wherein the computer program is configured to execute the method according to any one of claims 1 to 4 when executed.

10. An electronic device comprising a memory and a processor, characterized in that: A computer program is stored in the memory, and the processor is configured to run the computer program to perform the method according to any one of claims 1 to 4.

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