Distributed photovoltaic grid management method and system

Abstract

The invention discloses a distributed photovoltaic grid management method and system, and relates to the technical field of distributed photovoltaics, a distributed photovoltaic efficiency analysis module of the system monitors and evaluates the power utilization efficiency Psys of the whole system in real time by constructing a power efficiency formula, and compares the power utilization efficiency Psys with a preset efficiency threshold value X. When the operation efficiency of the system is lower than a set threshold value, the intelligent scheduling and energy distribution module starts an optimization strategy according to an electric power balance scheduling analysis result, redistributes electric power supply, preferentially meets a high-demand area or an area with insufficient energy storage, and ensures electric power supply and demand balance. According to the system, through an intelligent scheduling algorithm, power distribution is flexibly adjusted based on the priority factor of each micro-grid unit, and the operation efficiency of the system is improved. An intelligent feedback and iterative scheduling mechanism enables the system to still maintain efficient operation under continuously changing load and power generation conditions, power loss is reduced, resource waste is reduced, and the overall power utilization rate is improved.

Description

Technical Field

[0001] The present invention relates to the technical field of distributed photovoltaics, and in particular to a distributed photovoltaic grid management method and system. Background Art

[0002] Distributed photovoltaic grid management belongs to the field of new energy technology, specifically involving renewable energy management systems, especially distributed energy management based on photovoltaic power generation. With the increasing global demand for clean energy, photovoltaic power generation has been widely used as a green and renewable energy form. In recent years, distributed photovoltaic systems have played an important role in the power supply of cities and rural areas. Among them, efficient management of photovoltaic power generation units and energy storage equipment through grid management has become a key technology for optimizing energy distribution and improving power supply stability.

[0003] At present, the management of traditional distributed photovoltaic systems faces problems of low efficiency and imbalance between supply and demand. Since each photovoltaic power generation unit and energy storage device is often in an independent state, it is difficult to achieve a dynamic balance between power supply and demand in each region. Especially when the load demand fluctuates greatly, power waste or power shortage is more common. In addition, since photovoltaic power generation is affected by environmental factors such as weather and time, how to effectively predict power generation and reasonably allocate energy has become a management difficulty. These problems have led to low operating efficiency of photovoltaic power generation systems, especially the inability to flexibly dispatch power resources when faced with complex power demand. Summary of the invention

[0004] In view of the deficiencies in the prior art, the present invention provides a distributed photovoltaic grid management method and system, which solves the problems mentioned in the background technology.

[0005] To achieve the above objectives, the present invention is implemented by the following technical scheme: comprising the following steps:

[0006] S1. Distributed photovoltaics are divided into seven dispatching grids according to geographical location, load demand, and power generation and storage capacity. Each dispatching grid contains several microgrid units, each of which operates independently and has a dual-grid mode;

[0007] S2, by deploying an integrated monitoring device group in each microgrid unit, and using a wireless network to connect with the integrated monitoring device group deployed in the microgrid unit, to collect a comprehensive operation data set of distributed photovoltaics in real time, and then construct a database to store the comprehensive operation data set in the database;

[0008] S3. Calculate and output the predicted photovoltaic power generation PPV and energy storage output power POP based on the comprehensive operation data set extracted from the database, and then comprehensively calculate and output the microgrid power balance value Pbal based on the obtained predicted photovoltaic power generation PPV and energy storage output power POP, and perform preliminary comparative evaluation on the preset balance threshold P and the microgrid power balance value Pbal, and generate preliminary evaluation results;

[0009] S4. Based on the trigger of the preliminary evaluation results, the dispatch algorithm formula is constructed to calculate the output power dispatch value Pdis to balance the power supply and demand;

[0010] S5. Construct a power efficiency formula, perform comprehensive calculation to output the power efficiency Psys, and perform secondary comparative evaluation on the preset efficiency threshold X and the overall power efficiency Psys, and generate an optimization strategy based on the evaluation results.

[0011] Preferably, the dual network mode in step S1 includes a network connection mode and an island mode;

[0012] The network connection mode is used when the system is operating normally, the microgrid unit is connected to the external grid or other microgrid units, and power flows between the dispatching grids;

[0013] The island mode is used when a main grid fails and the microgrid unit is disconnected from the main grid and supplies power independently.

[0014] Preferably, the comprehensive operation data set in step S2 includes an environmental data set, an energy storage data set and a power data set;

[0015] The environmental data set includes photovoltaic panel conversion efficiency Gpv, solar radiation intensity Iso, cloud coverage Ccl and air humidity Hhu;

[0016] The energy storage data set includes the current discharge efficiency Pst of the energy storage device and the current temperature Tst of the energy storage device;

[0017] The power data set includes micro power demand Dre and power loss Lre;

[0018] The predicted photovoltaic power generation PPV in step S3 is calculated and output by the following photovoltaic power generation prediction algorithm formula;

[0019] PPV=Gpv×Apv×Iso×(1-Ccl)×(1-k1·Hhu);

[0020] In the formula, Apv represents the area of ​​​​the photovoltaic panel, k1 represents the humidity correction coefficient, and the humidity correction coefficient k1 and the photovoltaic panel conversion efficiency Gpv are automatically output based on the historical meteorological data and actual photovoltaic power generation data and the machine learning training prediction model.

[0021] Preferably, the energy storage output power POP in step S3 is calculated and obtained by the following energy storage device optimization algorithm formula;

[0022] POP=η storage ×Pst×(1-k2(Tst-Topt) 2 );

[0023] Where η storage It represents the discharge efficiency of the energy storage device, k2 represents the temperature influence coefficient, and Topt represents the normal operating temperature of the energy storage device.

[0024] The microgrid power balance value Pbal in step S3 is calculated and obtained by the following algorithm formula;

[0025] Pbal = (PPV + POP) - Dre - Lre.

[0026] The specific evaluation contents in step S3 are as follows;

[0027] When the microgrid power balance value Pbal ≥ the balance threshold P, it means that the current microgrid unit power supply is sufficient, the microgrid unit power is balanced and there is surplus power. At this time, the current dual-grid mode is further analyzed;

[0028] exporting surplus power to an external microgrid unit when in networking mode;

[0029] Stores surplus power when in island mode;

[0030] When the microgrid power balance value Pbal < the balance threshold P, it means that the current microgrid unit power supply is insufficient and the distributed photovoltaic power generation of the microgrid unit is insufficient. At this time, power is allocated from the energy storage device first, and the current dual-grid mode is further analyzed;

[0031] When in networking mode and when energy storage is insufficient, power is obtained from external microgrid units;

[0032] When in island mode the distributed load is reduced to 30%.

[0033] Preferably, the power dispatch value Pdis in step S4 is calculated and obtained by the following dispatch algorithm formula:

[0034]

[0035] In the formula, α i It represents the priority factor of the i-th microgrid unit, which is obtained based on the microgrid power balance value Pbal and the distance calculation. n represents the number of microgrid power sources participating in the scheduling. PPV i represents the photovoltaic power generation forecast of the i-th microgrid unit, POP irepresents the energy storage output power POP of the i-th microgrid unit, Dre i Denotes the power demand of the i-th microgrid unit Dre, Lre i The power loss Lre of the i-th microgrid unit.

[0036] The power efficiency Psys in step S4 is calculated and obtained by the following power efficiency formula;

[0037]

[0038] Preferably, in step S5, the preset efficiency threshold X and the obtained power efficiency Psys are subjected to secondary comparative evaluation to analyze the operation of distributed photovoltaics, and the specific evaluation contents are as follows;

[0039] When the power efficiency Psys ≥ the efficiency threshold X, it means that the distributed photovoltaic operation efficiency is normal and the supply and demand of the microgrid unit circuit in the table are balanced;

[0040] When the power efficiency Psys is less than the efficiency threshold X, it indicates that the distributed photovoltaic operation efficiency is abnormal and the power supply and demand of the microgrid units in the table are unbalanced. At this time, the intelligent scheduling and energy distribution module is iteratively executed to perform power scheduling and distribution until the power supply and demand are balanced and the iteration is stopped.

[0041] The present invention also relates to a distributed photovoltaic grid management system, including a microgrid management module, a data acquisition module, a power balance and scheduling module, an intelligent scheduling and energy distribution module and a distributed photovoltaic efficiency analysis module;

[0042] The microgrid management module is used to divide the distributed photovoltaic into seven dispatching grids according to geographical location, load demand, and power generation and energy storage capacity. Each dispatching grid contains several microgrid units, each of which operates independently and has a dual-grid mode;

[0043] The data acquisition module deploys an integrated monitoring device group in each microgrid unit and uses a wireless network to connect with the integrated monitoring device group deployed in the microgrid unit to collect the comprehensive operation data set of distributed photovoltaics in real time, and then constructs a database to store the comprehensive operation data set in the database;

[0044] The power balance and dispatch module is used to calculate and output the predicted photovoltaic power generation PPV and energy storage output power POP based on the comprehensive operation data set extracted from the database, and then comprehensively calculate and output the microgrid power balance value Pbal based on the obtained predicted photovoltaic power generation PPV and energy storage output power POP, and perform preliminary comparative evaluation on the preset balance threshold P and the microgrid power balance value Pbal, and generate preliminary evaluation results;

[0045] The intelligent dispatching and energy distribution module is triggered by the preliminary evaluation results. By constructing a dispatching algorithm formula, it calculates and outputs the power dispatching value Pdis to balance the power supply and demand.

[0046] The distributed photovoltaic efficiency analysis module is used to construct the power efficiency formula, perform comprehensive calculation of the output power efficiency Psys, and perform secondary comparative evaluation of the preset efficiency threshold X and the overall power efficiency Psys, and generate an optimization strategy based on the evaluation results.

[0047] Preferably, the microgrid management module includes a dispatching grid construction unit and a grid structure setting unit;

[0048] The dispatch grid construction unit uses the geographic information system GIS to perform geographic location and environmental analysis to determine the specific locations of photovoltaic power generation units and energy storage equipment, as well as the load demand of each region. Then, based on the regional load demand and photovoltaic power generation capacity, the entire system is divided into seven dispatch grids. Each dispatch grid includes the power demand of photovoltaic power generation units, energy storage equipment and loads. The dispatch grid includes several microgrid units.

[0049] The grid structure setting unit is independently responsible for power generation, energy storage and load management in its area through the microgrid unit. Each microgrid unit operates independently and has a dual-grid mode;

[0050] Dual network mode includes network mode and island mode;

[0051] The interconnection mode is used when the system is operating normally, the microgrid unit is connected to the external grid or other microgrid units, and power can flow between the dispatching grids;

[0052] The island mode is used when the main grid fails and the microgrid unit is disconnected from the main grid and powered independently.

[0053] Preferably, the data acquisition module includes an integrated monitoring unit and a data storage unit;

[0054] The integrated monitoring unit deploys an integrated monitoring device group inside each microgrid unit to monitor the photovoltaic power generation equipment, energy storage equipment and load in real time. The integrated microgrid control system then extracts the comprehensive operation data set of distributed photovoltaics in real time and uploads the collected comprehensive operation data set to the integrated monitoring unit in real time through LaRa.

[0055] The monitoring equipment group includes photovoltaic inverters, solar radiation intensity sensors, humidity sensors, and full sky imagers;

[0056] The comprehensive operation dataset includes environmental dataset, energy storage dataset and power dataset;

[0057] The environmental data set includes photovoltaic panel conversion efficiency Gpv, solar radiation intensity Iso, cloud coverage Ccl and air humidity Hhu;

[0058] The energy storage data set includes the current discharge efficiency Pst of the energy storage device and the current temperature Tst of the energy storage device;

[0059] The power data set includes micro-power demand Dre and power loss Lre;

[0060] The energy storage data set and the power data set are collected and acquired through the distributed energy management system in the microgrid control system to monitor the distributed photovoltaic equipment and energy storage equipment in real time;

[0061] The data storage unit is used to construct a MySQL relational database, and set a write port to connect with the integrated monitoring unit, and write the comprehensive operation data set collected in real time into the data storage table of the MySQL relational database for storage;

[0062] The write port is set to a one-way setting, allowing only the integrated monitoring unit to write to the MySQL relational database.

[0063] Preferably, the power balance and dispatch module includes a power generation prediction unit, an energy storage device optimization unit and a power balance dispatch analysis unit;

[0064] The power generation prediction unit constructs a photovoltaic power generation prediction algorithm formula, extracts the environmental data set through the write port of the MySQL relational database, inputs it into the photovoltaic power generation prediction algorithm formula, and calculates and outputs the predicted photovoltaic power generation PPV;

[0065] The predicted photovoltaic power generation PPV is calculated and output by the following photovoltaic power generation prediction algorithm formula;

[0066] PPV=Gpv×Apv×Iso×(1-Ccl)×(1-k1·Hhu);

[0067] In the formula, Apv represents the area of ​​​​the photovoltaic panel, k1 represents the humidity correction coefficient, and the humidity correction coefficient k1 and the photovoltaic panel conversion efficiency Gpv are automatically output based on the historical meteorological data and actual photovoltaic power generation data and the machine learning training prediction model.

[0068] Preferably, the energy storage device optimization unit is used to integrate a temperature monitoring and regulating system in the energy storage device, and by constructing an energy storage device optimization algorithm formula, extract the current energy storage data set through the write port of the MySQL relational database, input it into the energy storage device optimization algorithm formula, and output the energy storage output power POP;

[0069] The energy storage output power POP is calculated and obtained through the following energy storage equipment optimization algorithm formula;

[0070] POP=η storage ×Pst×(1-k2(Tst-Topt) 2 );

[0071] Where η storage It represents the discharge efficiency of the energy storage device, k2 represents the temperature influence coefficient, and Topt represents the normal operating temperature of the energy storage device.

[0072] Preferably, the power balance scheduling analysis unit includes a power balance scheduling algorithm unit and a power balance evaluation unit;

[0073] The power balance scheduling algorithm unit is used to construct the power balance formula, calculate the output microgrid power balance value Pbal based on the predicted photovoltaic power generation PPV and energy storage output power POP and combined with the power data set, and dynamically adjust the power supply and demand balance of the microgrid;

[0074] The microgrid power balance value Pbal is calculated by the following algorithm formula:

[0075] Pbal = (PPV + POP) - Dre - Lre;

[0076] The power balance evaluation unit is used to preset the balance threshold value P based on the microgrid power balance standard, and then make a preliminary comparison and evaluation with the obtained microgrid power balance value Pbal to analyze the power demand of the microgrid unit. The specific evaluation contents are as follows;

[0077] When the microgrid power balance value Pbal ≥ the balance threshold P, it means that the current microgrid unit power supply is sufficient, the microgrid unit power is balanced and there is surplus power. At this time, the current dual-grid mode is further analyzed;

[0078] exporting surplus power to an external microgrid unit when in networking mode;

[0079] Stores surplus power when in island mode;

[0080] When the microgrid power balance value Pbal < the balance threshold P, it means that the current microgrid unit power supply is insufficient and the distributed photovoltaic power generation of the microgrid unit is insufficient. At this time, power is allocated from the energy storage device first, and the current dual-grid mode is further analyzed;

[0081] When in networking mode and when energy storage is insufficient, power is obtained from external microgrid units;

[0082] When in island mode the distributed load is reduced to 30%.

[0083] Preferably, the intelligent scheduling and energy distribution module is used to construct a scheduling algorithm formula when the energy storage is insufficient while in the networking mode, calculate the output power scheduling value Pdis, and perform precise power scheduling and distribution through the microgrid control system;

[0084] The power dispatch value Pdis is calculated by the following dispatch algorithm formula;

[0085]

[0086] In the formula, α i It represents the priority factor of the i-th microgrid unit, which is obtained based on the microgrid power balance value Pbal and the distance calculation. n represents the number of microgrid power sources participating in the scheduling. PPV i represents the photovoltaic power generation forecast of the i-th microgrid unit, POP i represents the energy storage output power POP of the i-th microgrid unit, Dre i Denotes the power demand of the i-th microgrid unit Dre, Lre i The power loss Lre of the i-th microgrid unit.

[0087] Preferably, the distributed photovoltaic efficiency analysis module includes a power efficiency analysis unit and an optimization evaluation unit;

[0088] The power efficiency analysis unit is used to construct a power efficiency formula to calculate the output power efficiency Psys after the microgrid unit is dispatched and allocated, and comprehensively analyze the power efficiency of all microgrid units in the dispatch grid;

[0089] The power efficiency Psys is calculated by the following power efficiency formula:

[0090]

[0091] Preferably, the optimization evaluation unit performs a secondary comparative evaluation based on the preset efficiency threshold X by the user and the acquired power efficiency Psys to analyze the operation of the distributed photovoltaic system. The specific evaluation contents are as follows;

[0092] When the power efficiency Psys ≥ the efficiency threshold X, it means that the distributed photovoltaic operation efficiency is normal and the supply and demand of the microgrid unit circuit in the table are balanced;

[0093] When the power efficiency Psys is less than the efficiency threshold X, it indicates that the distributed photovoltaic operation efficiency is abnormal and the power supply and demand of the microgrid units in the table are unbalanced. At this time, the intelligent scheduling and energy distribution module is iteratively executed to perform power scheduling and distribution until the power supply and demand are balanced and the iteration is stopped.

[0094] The present invention provides a distributed photovoltaic grid management method and system, which has the following beneficial effects:

[0095] (1) The system divides the entire distributed photovoltaic system into multiple microgrid areas through the microgrid management module, and configures each area as an independent microgrid unit to form a dispatching grid power management system. Each microgrid unit independently manages power generation, energy storage and load conditions, and can monitor the power supply and demand and power generation conditions in the area in real time by deploying an integrated monitoring device group. When power is insufficient or the load increases, the system can quickly mobilize the remaining power of other microgrid units to ensure stable power supply. This dynamic management method not only avoids local power outages, but also improves the risk resistance of the entire system, so that even when the power grid fails, the microgrid unit can operate independently in island mode to maintain the continuity and reliability of regional power supply.

[0096] (2) The data acquisition module of the system is connected to the integrated monitoring equipment group in the microgrid to collect environmental data and energy storage equipment data in real time. These data are stored in the MySQL relational database and used for calculation and analysis by the power balance and scheduling module. The system accurately calculates the photovoltaic power generation PPV and energy storage output power POP based on the photovoltaic power generation prediction algorithm, and outputs the power balance value Pbal based on the current power demand Dre and power loss Lre. Through these optimized algorithms, the system can accurately match power generation and power demand, reduce energy waste, ensure the optimal use of energy storage equipment, and maximize the efficiency of photovoltaic power generation and the utilization of the energy storage system.

[0097] (3) The distributed photovoltaic efficiency analysis module of the system constructs an electric efficiency formula to monitor and evaluate the power utilization efficiency Psys of the entire system in real time, and compares it with the preset efficiency threshold X. When the system operating efficiency is lower than the set threshold, the intelligent scheduling and energy distribution module will start the optimization strategy based on the power balance scheduling analysis results, redistribute the power supply, give priority to high-demand areas or areas with insufficient energy storage, and ensure the balance of power supply and demand. The system uses an intelligent scheduling algorithm to flexibly adjust power distribution based on the priority factor of each microgrid unit to improve the operating efficiency of the system. The intelligent feedback and iterative scheduling mechanism enables the system to maintain efficient operation under changing load and power generation conditions, reduce power loss, reduce resource waste, and improve overall power utilization. BRIEF DESCRIPTION OF THE DRAWINGS

[0098] Figure 1 A schematic diagram of a distributed photovoltaic grid management system process of the present invention;

[0099] Figure 2 The figure is a schematic diagram of the steps of a distributed photovoltaic grid management method according to the present invention. DETAILED DESCRIPTION

[0100] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0101] Example 1

[0102] See also Figure 1 The present invention provides a distributed photovoltaic grid management method. To achieve the above purpose, the present invention is implemented by the following technical scheme: comprising the following steps:

[0103] S1. Distributed photovoltaics are divided into seven dispatching grids according to geographical location, load demand, and power generation and storage capacity. Each dispatching grid contains several microgrid units, each of which operates independently and has a dual-grid mode;

[0104] S2, by deploying an integrated monitoring device group in each microgrid unit, and using a wireless network to connect with the integrated monitoring device group deployed in the microgrid unit, to collect a comprehensive operation data set of distributed photovoltaics in real time, and then construct a database to store the comprehensive operation data set in the database;

[0105] S3. Calculate and output the predicted photovoltaic power generation PPV and energy storage output power POP based on the comprehensive operation data set extracted from the database, and then comprehensively calculate and output the microgrid power balance value Pbal based on the obtained predicted photovoltaic power generation PPV and energy storage output power POP, and perform preliminary comparative evaluation on the preset balance threshold P and the microgrid power balance value Pbal, and generate preliminary evaluation results;

[0106] S4. Based on the trigger of the preliminary evaluation results, the dispatch algorithm formula is constructed to calculate the output power dispatch value Pdis to balance the power supply and demand;

[0107] S5. Construct a power efficiency formula, perform comprehensive calculation to output the power efficiency Psys, and perform secondary comparative evaluation on the preset efficiency threshold X and the overall power efficiency Psys, and generate an optimization strategy based on the evaluation results.

[0108] A distributed photovoltaic grid management system, including a microgrid management module, a data acquisition module, a power balance and dispatching module, an intelligent dispatching and energy distribution module and a distributed photovoltaic efficiency analysis module;

[0109] The microgrid management module is used to divide the distributed photovoltaic into seven dispatching grids according to geographical location, load demand, and power generation and energy storage capacity. Each dispatching grid contains several microgrid units, each of which operates independently and has a dual-grid mode;

[0110] The data acquisition module deploys an integrated monitoring device group in each microgrid unit and uses a wireless network to connect with the integrated monitoring device group deployed in the microgrid unit to collect the comprehensive operation data set of distributed photovoltaics in real time, and then constructs a database to store the comprehensive operation data set in the database;

[0111] The power balance and dispatch module is used to calculate and output the predicted photovoltaic power generation PPV and energy storage output power POP based on the comprehensive operation data set extracted from the database, and then comprehensively calculate and output the microgrid power balance value Pbal based on the obtained predicted photovoltaic power generation PPV and energy storage output power POP, and perform preliminary comparative evaluation on the preset balance threshold P and the microgrid power balance value Pbal, and generate preliminary evaluation results;

[0112] The intelligent dispatching and energy distribution module is triggered by the preliminary evaluation results. By constructing a dispatching algorithm formula, it calculates and outputs the power dispatching value Pdis to balance the power supply and demand.

[0113] The distributed photovoltaic efficiency analysis module is used to construct the power efficiency formula, perform comprehensive calculation of the output power efficiency Psys, and perform secondary comparative evaluation of the preset efficiency threshold X and the overall power efficiency Psys, and generate an optimization strategy based on the evaluation results.

[0114] In this embodiment, the system divides the system into multiple independent microgrid units through the microgrid management module to form a dispatching grid structure, and monitors the power generation and load conditions in real time through integrated monitoring equipment to achieve distributed management. This mechanism improves the flexibility of the system, allowing each microgrid to operate autonomously according to actual needs. Secondly, the data acquisition module is connected to the monitoring equipment through a wireless network, collects the comprehensive operation data set in real time, ensures the timely transmission and efficient management of information, and builds an extensible database to provide reliable data support for subsequent analysis and scheduling. The power balance and scheduling module calculates and predicts the photovoltaic power generation PPV and energy storage power POP through comprehensive data, evaluates and outputs the power balance value Pbal in real time to achieve a preliminary assessment of the supply and demand balance. This module ensures the precise matching of power supply and demand, and effectively reduces power waste and shortage. Based on the preliminary evaluation results, the intelligent scheduling and energy distribution module uses the scheduling algorithm to further optimize the power scheduling, ensure the balance of supply and demand, and improve the responsiveness and efficiency of the system. Finally, the distributed photovoltaic efficiency analysis module generates an optimization strategy by calculating the overall power efficiency Psys and comparing it with the efficiency threshold X, ensuring the efficient operation of the system under different load conditions. The system has greatly improved the utilization rate of photovoltaic power generation and energy storage equipment, reduced power loss, and achieved more accurate power dispatching and smarter energy distribution. Through efficient data collection, real-time monitoring and intelligent dispatching, the overall efficiency of the system has been significantly improved, ensuring that the power supply remains stable and efficient under the changing power demand environment.

[0115] Example 2

[0116] This embodiment is explained in Example 1, please refer to Figure 1 ,Specifically: the microgrid management module includes a dispatching grid building unit and a grid ,structure setting unit;

[0117] The dispatch grid construction unit uses the geographic information system GIS to perform geographic location and environmental analysis to determine the specific locations of photovoltaic power generation units and energy storage equipment, as well as the load demand of each region. Then, based on the regional load demand and photovoltaic power generation capacity, the entire system is divided into seven dispatch grids. Each dispatch grid includes the power demand of photovoltaic power generation units, energy storage equipment and loads. The dispatch grid includes several microgrid units.

[0118] The grid structure setting unit is independently responsible for power generation, energy storage and load management in its area through the microgrid unit. Each microgrid unit operates independently and has a dual-grid mode;

[0119] Dual network mode includes network mode and island mode;

[0120] The interconnection mode is used when the system is operating normally, the microgrid unit is connected to the external grid or other microgrid units, and power can flow between the dispatching grids;

[0121] The island mode is used when the main grid fails and the microgrid unit is disconnected from the main grid and powered independently.

[0122] In this embodiment, the system realizes efficient management and flexible dispatch of power resources in distributed photovoltaic systems through the coordinated work of the dispatch grid construction unit and the grid structure setting unit through the microgrid management module. The dispatch grid construction unit uses GIS to analyze the geographical location and load demand, reasonably divides 7 dispatch grids, and distributes photovoltaic power generation units, energy storage equipment and load demand in each grid, so as to achieve accurate matching of power supply and demand. The grid structure setting unit is connected to the external power grid or other microgrid units through the network connection mode when the system is normal through the independent operation capability of the microgrid unit, ensuring the flexible flow of power; when the main power grid fails, it switches to the island mode to ensure independent power supply. This design not only improves the stability and adaptability of the system, but also solves the problem of dependence on the main power grid in traditional power systems. Compared with traditional technologies, this module reduces power waste and transmission loss through grid-based flexible dispatching, improves the power supply reliability and energy utilization efficiency of the system, and ensures continuous power supply in the area, especially in the case of power grid failure or fluctuation.

[0123] Example 3

[0124] This embodiment is explained in Example 2. Please refer to Figure 1 ,Specifically: the data acquisition module includes an integrated monitoring unit and a data storage unit;

[0125] The integrated monitoring unit deploys an integrated monitoring device group inside each microgrid unit to monitor the photovoltaic power generation equipment, energy storage equipment and load in real time. The integrated microgrid control system then extracts the comprehensive operation data set of distributed photovoltaics in real time and uploads the collected comprehensive operation data set to the integrated monitoring unit in real time through LaRa.

[0126] The monitoring equipment group includes photovoltaic inverters, solar radiation intensity sensors, humidity sensors, and full sky imagers;

[0127] The comprehensive operation dataset includes environmental dataset, energy storage dataset and power dataset;

[0128] The environmental data set includes photovoltaic panel conversion efficiency Gpv, solar radiation intensity Iso, cloud coverage Ccl and air humidity Hhu;

[0129] The energy storage data set includes the current discharge efficiency Pst of the energy storage device and the current temperature Tst of the energy storage device;

[0130] The power data set includes micro-power demand Dre and power loss Lre;

[0131] The energy storage data set and the power data set are collected and acquired through the distributed energy management system in the microgrid control system to monitor the distributed photovoltaic equipment and energy storage equipment in real time;

[0132] The data storage unit is used to construct a MySQL relational database, and set a write port to connect with the integrated monitoring unit, and write the comprehensive operation data set collected in real time into the data storage table of the MySQL relational database for storage;

[0133] The write port is set to a one-way setting, allowing only the integrated monitoring unit to write to the MySQL relational database.

[0134] In this embodiment, the data acquisition module of the system realizes comprehensive real-time data acquisition and storage of distributed photovoltaic systems through the collaborative work of the integrated monitoring unit and the data storage unit. The integrated monitoring unit is deployed inside each microgrid unit, and monitors the operating status of photovoltaic power generation, energy storage equipment and loads in real time through equipment such as photovoltaic inverters, solar radiation intensity sensors, humidity sensors and full-sky imagers, collects environmental data sets, energy storage data sets and power data sets, and summarizes them to generate a comprehensive operating data set. Through LoRa technology, these data are uploaded to the monitoring center in real time to ensure that the system can obtain the latest operating information at any time. The data storage unit builds a relational database based on MySQL, stores all operating data sets in the database, and ensures the security and integrity of the data.

[0135] Example 4

[0136] This embodiment is explained in Example 3, please refer to Figure 1 ,Specifically: the power balance and scheduling module includes a power generation prediction unit, an ,energy storage equipment optimization unit and a power balance scheduling ,analysis unit;

[0137] The power generation prediction unit constructs a photovoltaic power generation prediction algorithm formula, extracts the environmental data set through the write port of the MySQL relational database, inputs it into the photovoltaic power generation prediction algorithm formula, and calculates and outputs the predicted photovoltaic power generation PPV;

[0138] The predicted photovoltaic power generation PPV is calculated and output by the following photovoltaic power generation prediction algorithm formula;

[0139] PPV=Gpv×Apv×Iso×(1-Ccl)×(1-k1·Hhu);

[0140] In the formula, Apv represents the area of ​​​​the photovoltaic panel, k1 represents the humidity correction coefficient, and the humidity correction coefficient k1 and the photovoltaic panel conversion efficiency Gpv are automatically output based on the historical meteorological data and actual photovoltaic power generation data and the machine learning training prediction model.

[0141] The energy storage device optimization unit is used to integrate the temperature monitoring and regulation system in the energy storage device, and to construct the energy storage device optimization algorithm formula. The current energy storage data set is extracted through the write port of the MySQL relational database, and input into the energy storage device optimization algorithm formula to output the energy storage output power POP;

[0142] The energy storage output power POP is calculated and obtained through the following energy storage equipment optimization algorithm formula;

[0143] POP=η storage ×Pst×(1-k2(Tst-Topt) 2 );

[0144] Where η storage It represents the discharge efficiency of the energy storage device, k2 represents the temperature influence coefficient, and Topt represents the normal operating temperature of the energy storage device.

[0145] The power balance dispatch analysis unit includes a power balance dispatch algorithm unit and a power balance evaluation unit;

[0146] The power balance scheduling algorithm unit is used to construct the power balance formula, calculate the output microgrid power balance value Pbal based on the predicted photovoltaic power generation PPV and energy storage output power POP and combined with the power data set, and dynamically adjust the power supply and demand balance of the microgrid;

[0147] The microgrid power balance value Pbal is calculated by the following algorithm formula:

[0148] Pbal = (PPV + POP) - Dre - Lre;

[0149] The power balance evaluation unit is used to preset the balance threshold value P based on the microgrid power balance standard, and then make a preliminary comparison and evaluation with the obtained microgrid power balance value Pbal to analyze the power demand of the microgrid unit. The specific evaluation contents are as follows;

[0150] When the microgrid power balance value Pbal ≥ the balance threshold P, it means that the current microgrid unit power supply is sufficient, the microgrid unit power is balanced and there is surplus power. At this time, the current dual-grid mode is further analyzed;

[0151] exporting surplus power to an external microgrid unit when in networking mode;

[0152] Stores surplus power when in island mode;

[0153] When the microgrid power balance value Pbal < the balance threshold P, it means that the current microgrid unit power supply is insufficient and the distributed photovoltaic power generation of the microgrid unit is insufficient. At this time, power is allocated from the energy storage device first, and the current dual-grid mode is further analyzed;

[0154] When in networking mode and when energy storage is insufficient, power is obtained from external microgrid units;

[0155] When in island mode the distributed load is reduced to 30%.

[0156] In this embodiment, the system ensures the dynamic balance of power generation and power consumption in the distributed photovoltaic system through the collaborative work of the power generation prediction unit, energy storage device optimization unit and power balance scheduling analysis unit of the power balance and scheduling module. The power generation prediction unit accurately predicts the photovoltaic power generation PPV by extracting the environmental data set and combining the machine learning algorithm, thereby improving the accuracy and forward-looking judgment of photovoltaic power generation. The energy storage device optimization unit monitors the status of the energy storage device in real time and dynamically adjusts the discharge power POP of the energy storage device based on the energy storage device optimization algorithm to ensure that the energy storage system works in the best state, prolong the equipment life and improve efficiency. The power balance scheduling analysis unit calculates and evaluates the power balance value Pbal of the microgrid based on the predicted photovoltaic power generation and energy storage output power, and realizes the balance of power supply by real-time scheduling of photovoltaic power generation and energy storage equipment. This module improves the accuracy of photovoltaic power generation and energy storage utilization by introducing data-driven power generation prediction and energy storage optimization algorithms, thereby avoiding the problems of power waste and shortage. The system can automatically adjust power supply and demand according to real-time environment and power demand data, ensuring that excess power is output when power supply is sufficient, and that power is obtained from energy storage devices or external power grids first when power is insufficient, thus ensuring the stable operation of the system to the greatest extent. This dynamic scheduling and balancing mechanism greatly improves the utilization efficiency of power resources, and through the flexible switching of dual-network modes, it enhances the system's adaptability in different scenarios, significantly improving the overall operating efficiency and power supply reliability of the photovoltaic system.

[0157] Example 5

[0158] This embodiment is explained in Example 4. Please refer to Figure 1 ,Specifically: ,The intelligent scheduling and energy distribution module is used to construct a scheduling algorithm formula and ,calculate the output power scheduling value Pdis when the energy storage is insufficient while in ,network mode, and the microgrid control system performs precise ,power scheduling and distribution;

[0159] The power dispatch value Pdis is calculated by the following dispatch algorithm formula;

[0160]

[0161] In the formula, α i It represents the priority factor of the i-th microgrid unit, which is obtained based on the microgrid power balance value Pbal and the distance calculation. n represents the number of microgrid power sources participating in the scheduling. PPV i represents the photovoltaic power generation forecast of the i-th microgrid unit, POP i represents the energy storage output power POP of the i-th microgrid unit, Dre i Denotes the power demand of the i-th microgrid unit Dre, Lre i The power loss Lre of the i-th microgrid unit.

[0162] In this embodiment, the system realizes accurate power dispatching when power supply is insufficient or energy storage equipment is lacking by constructing a dispatching algorithm. By calculating the power dispatching value Pdis, the system can flexibly dispatch power resources based on comprehensive factors such as the priority of each microgrid unit, photovoltaic power generation PPV, energy storage output power POP, power demand Dre and power loss Lre to ensure the balance of power supply and demand in the networking mode. The core of this module is to use intelligent dispatching algorithms to dynamically allocate power, give priority to allocating resource-rich microgrid units to support units with insufficient power, and ensure the overall power balance of the system. This module introduces a dispatching algorithm based on real-time data, which can more accurately predict and meet the power demand of each region, reducing resource waste and power shortages. Through intelligent dispatching logic, the system no longer relies on fixed rule dispatching, but adaptively optimizes according to real-time data, improving the flexibility and response speed of dispatching.

[0163] Example 6

[0164] This embodiment is explained in Example 5. Please refer to Figure 1 ,Specifically: the distributed photovoltaic efficiency analysis module includes a power efficiency ,analysis unit and an optimization evaluation unit;

[0165] The power efficiency analysis unit is used to construct a power efficiency formula to calculate the output power efficiency Psys after the microgrid unit is dispatched and allocated, and comprehensively analyze the power efficiency of all microgrid units in the dispatch grid;

[0166] The power efficiency Psys is calculated by the following power efficiency formula:

[0167]

[0168] The optimization evaluation unit performs a secondary comparative evaluation based on the user's preset efficiency threshold X and the obtained power efficiency Psys to analyze the operation of distributed photovoltaics. The specific evaluation contents are as follows;

[0169] When the power efficiency Psys ≥ the efficiency threshold X, it means that the distributed photovoltaic operation efficiency is normal and the supply and demand of the microgrid unit circuit in the table are balanced;

[0170] When the power efficiency Psys is less than the efficiency threshold X, it indicates that the distributed photovoltaic operation efficiency is abnormal and the power supply and demand of the microgrid units in the table are unbalanced. At this time, the intelligent scheduling and energy distribution module is iteratively executed to perform power scheduling and distribution until the power supply and demand are balanced and the iteration is stopped.

[0171] In this embodiment, the distributed photovoltaic efficiency analysis module of the system ensures that the power utilization efficiency of the microgrid system reaches the optimal level through the collaborative work of the power efficiency analysis unit and the optimization evaluation unit. After each dispatch and energy distribution, the power efficiency analysis unit uses the power efficiency formula to calculate the power efficiency Psys of the entire system and comprehensively evaluates the operating status of each microgrid unit. The optimization evaluation unit compares the calculated power efficiency with the preset efficiency threshold X. When the efficiency is lower than the threshold, the system automatically adjusts by iteratively executing the intelligent dispatch and energy distribution module until the power supply and demand are balanced. Through this closed-loop optimization mechanism, the system can maintain efficient operation after real-time adjustment. By automatically evaluating power efficiency, the system can promptly discover and respond to the imbalance of power supply and demand to prevent power waste or shortage. This dynamic optimization capability ensures the optimal allocation of power resources in each microgrid unit and improves the overall energy utilization efficiency. At the same time, the module provides a clear operation evaluation mechanism, enabling operators to identify and optimize inefficient units based on specific efficiency data. In the end, the system effectively improves the operating efficiency, stability and intelligent level of energy management of the distributed photovoltaic system, reduces operating costs, and improves the long-term reliability and sustainability of the system.

[0172] Example 7

[0173] See also Figure 1 and Figure 2 , a distributed photovoltaic grid management method, comprising the following steps:

[0174] S1. Distributed photovoltaics are divided into seven dispatching grids according to geographical location, load demand, and power generation and storage capacity. Each dispatching grid contains several microgrid units, each of which operates independently and has a dual-grid mode;

[0175] S2, by deploying an integrated monitoring device group in each microgrid unit, and using a wireless network to connect with the integrated monitoring device group deployed in the microgrid unit, to collect a comprehensive operation data set of distributed photovoltaics in real time, and then construct a database to store the comprehensive operation data set in the database;

[0176] S3. Calculate and output the predicted photovoltaic power generation PPV and energy storage output power POP based on the comprehensive operation data set extracted from the database, and then comprehensively calculate and output the microgrid power balance value Pbal based on the obtained predicted photovoltaic power generation PPV and energy storage output power POP, and perform preliminary comparative evaluation on the preset balance threshold P and the microgrid power balance value Pbal, and generate preliminary evaluation results;

[0177] S4. Based on the trigger of the preliminary evaluation results, the dispatch algorithm formula is constructed to calculate the output power dispatch value Pdis to balance the power supply and demand;

[0178] S5. Construct a power efficiency formula, perform comprehensive calculation to output the power efficiency Psys, and perform secondary comparative evaluation on the preset efficiency threshold X and the overall power efficiency Psys, and generate an optimization strategy based on the evaluation results.

[0179] While the embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that many changes, modifications, substitutions and variations can be made to the embodiments without departing from the principles and spirit of the invention.

Claims

1. A distributed photovoltaic grid management method, characterized in that: The following steps are involved: S1. Distributed photovoltaics are divided into seven dispatching grids according to geographical location, load demand, and power generation and storage capacity. Each dispatching grid contains several microgrid units, each of which operates independently and has a dual-grid mode; S2, by deploying an integrated monitoring device group in each microgrid unit, and using a wireless network to connect with the integrated monitoring device group deployed in the microgrid unit, to collect a comprehensive operation data set of distributed photovoltaics in real time, and then construct a database to store the comprehensive operation data set in the database; S3. Calculate and output the predicted photovoltaic power generation PPV and energy storage output power POP based on the comprehensive operation data set extracted from the database, and then comprehensively calculate and output the microgrid power balance value Pbal based on the obtained predicted photovoltaic power generation PPV and energy storage output power POP, and perform preliminary comparative evaluation on the preset balance threshold P and the microgrid power balance value Pbal, and generate preliminary evaluation results; S4. Based on the trigger of the preliminary evaluation results, the dispatch algorithm formula is constructed to calculate the output power dispatch value Pdis to balance the power supply and demand; S5. Construct a power efficiency formula, perform comprehensive calculation to output the power efficiency Psys, and perform secondary comparative evaluation on the preset efficiency threshold X and the overall power efficiency Psys, and generate an optimization strategy based on the evaluation results.

2. A distributed photovoltaic grid management method according to claim 1, characterized in that: The dual network mode in step S1 includes a network connection mode and an island mode; The network connection mode is used when the system is operating normally, the microgrid unit is connected to the external grid or other microgrid units, and power flows between the dispatching grids; The island mode is used when a main grid fails and the microgrid unit is disconnected from the main grid and supplies power independently.

3. A distributed photovoltaic grid management method according to claim 1, characterized in that: The comprehensive operation data set in step S2 includes an environment data set, an energy storage data set and a power data set; The environmental data set includes photovoltaic panel conversion efficiency Gpv, solar radiation intensity Iso, cloud coverage Ccl and air humidity Hhu; The energy storage data set includes the current discharge efficiency Pst of the energy storage device and the current temperature Tst of the energy storage device; The power data set includes micro power demand Dre and power loss Lre; The predicted photovoltaic power generation PPV in step S3 is calculated and output by the following photovoltaic power generation prediction algorithm formula; PPV=Gpv×Apv×Iso×(1-Ccl)×(1-k1·Hhu); In the formula, Apv represents the area of ​​​​the photovoltaic panel, k1 represents the humidity correction coefficient, and the humidity correction coefficient k1 and the photovoltaic panel conversion efficiency Gpv are automatically output based on the historical meteorological data and actual photovoltaic power generation data and the machine learning training prediction model.

4. A distributed photovoltaic grid management method according to claim 3, characterized in that: The energy storage output power POP in step S3 is calculated and obtained by the following energy storage device optimization algorithm formula; POP=η storage ×Pst×(1-k2(Tst-Topt) 2 ); Where η storage It represents the discharge efficiency of the energy storage device, k2 represents the temperature influence coefficient, and Topt represents the normal operating temperature of the energy storage device.

5. A distributed photovoltaic grid management method according to claim 3, characterized in that: The microgrid power balance value Pbal in step S3 is calculated and obtained by the following algorithm formula; Pbal = (PPV + POP) - Dre - Lre.

6. A distributed photovoltaic grid management method according to claim 1, characterized in that: The specific evaluation contents in step S3 are as follows; When the microgrid power balance value Pbal ≥ the balance threshold P, it means that the current microgrid unit power supply is sufficient, the microgrid unit power is balanced and there is surplus power. At this time, the current dual-grid mode is further analyzed; exporting surplus power to an external microgrid unit when in networking mode; Stores surplus power when in island mode; When the microgrid power balance value Pbal < the balance threshold P, it means that the current microgrid unit power supply is insufficient and the distributed photovoltaic power generation of the microgrid unit is insufficient. At this time, power is allocated from the energy storage device first, and the current dual-grid mode is further analyzed; When in networking mode and energy storage is insufficient, power is obtained from external microgrid units; When in island mode the distributed load is reduced to 30%.

7. A distributed photovoltaic grid management method according to claim 3, characterized in that: The power dispatch value Pdis in step S4 is calculated and obtained by the following dispatch algorithm formula; In the formula, α i It represents the priority factor of the i-th microgrid unit, which is obtained based on the microgrid power balance value Pbal and the distance calculation. n represents the number of microgrid power sources participating in the scheduling. PPV i represents the photovoltaic power generation forecast of the i-th microgrid unit, POP i represents the energy storage output power POP of the i-th microgrid unit, Dre i Denotes the power demand of the i-th microgrid unit Dre, Lre i The power loss Lre of the i-th microgrid unit.

8. A distributed photovoltaic grid management method according to claim 3, characterized in that: The power efficiency Psys in step S4 is calculated and obtained by the following power efficiency formula; 9. A distributed photovoltaic grid management method according to claim 1, characterized in that: In step S5, the preset efficiency threshold X is compared with the obtained power efficiency Psys for secondary evaluation to analyze the operation of distributed photovoltaics. The specific evaluation contents are as follows; When the power efficiency Psys ≥ the efficiency threshold X, it means that the distributed photovoltaic operation efficiency is normal and the supply and demand of the microgrid unit circuit in the table are balanced; When the power efficiency Psys is less than the efficiency threshold X, it indicates that the distributed photovoltaic operation efficiency is abnormal and the power supply and demand of the microgrid units in the table are unbalanced. At this time, the intelligent scheduling and energy distribution module is iteratively executed to perform power scheduling and distribution until the power supply and demand are balanced and the iteration is stopped.

10. A management analysis system based on big data, applied to the management analysis method based on big data according to claim 1, characterized in that: It includes microgrid management module, data acquisition module, power balance and dispatching module, intelligent dispatching and energy distribution module and distributed photovoltaic efficiency analysis module; The microgrid management module is used to divide the distributed photovoltaic into seven dispatching grids according to geographical location, load demand, and power generation and energy storage capacity. Each dispatching grid contains a number of microgrid units, and each microgrid unit operates independently and has a dual-grid mode; The data acquisition module deploys an integrated monitoring device group in each microgrid unit, and uses a wireless network to connect with the integrated monitoring device group deployed in the microgrid unit to collect the comprehensive operation data set of distributed photovoltaics in real time, and then constructs a database to store the comprehensive operation data set in the database; The power balance and scheduling module is used to calculate and output the predicted photovoltaic power generation PPV and energy storage output power POP based on the comprehensive operation data set extracted from the database, and then comprehensively calculate and output the microgrid power balance value Pbal based on the obtained predicted photovoltaic power generation PPV and energy storage output power POP, and perform preliminary comparative evaluation on the preset balance threshold P and the microgrid power balance value Pbal, and generate a preliminary evaluation result; The intelligent scheduling and energy distribution module is triggered according to the preliminary evaluation results, and calculates and outputs the power scheduling value Pdis by constructing a scheduling algorithm formula to balance the power supply and demand; The distributed photovoltaic efficiency analysis module is used to construct an electric power efficiency formula, perform comprehensive calculation of the output electric power efficiency Psys, and perform secondary comparative evaluation of the preset efficiency threshold X and the overall electric power efficiency Psys, and generate an optimization strategy based on the evaluation results.

11. A distributed photovoltaic grid management system according to claim 10, characterized in that: The microgrid management module includes a dispatching grid construction unit and a grid structure setting unit; The dispatch grid construction unit determines the specific location of the photovoltaic power generation unit and the energy storage device, as well as the load demand of each region by using the geographic information system GIS for geographic location and environmental analysis, and then divides the entire system into 7 dispatch grids according to the load demand of the region and the photovoltaic power generation capacity. Each dispatch grid includes the power demand of the photovoltaic power generation unit, the energy storage device and the load, and the dispatch grid includes several microgrid units; The grid structure setting unit is independently responsible for power generation, energy storage and load management in its area through microgrid units, and each microgrid unit operates independently and has a dual-grid mode; The dual network mode includes a network connection mode and an island mode; The network connection mode is used when the system is operating normally, the microgrid unit is connected to the external grid or other microgrid units, and power flows between the dispatching grids; The island mode is used when a main grid fails and the microgrid unit is disconnected from the main grid and supplies power independently.

12. A distributed photovoltaic grid management system according to claim 10, characterized in that: The data acquisition module includes an integrated monitoring unit and a data storage unit; The integrated monitoring unit monitors photovoltaic power generation equipment, energy storage equipment and loads in real time by deploying an integrated monitoring device group inside each microgrid unit. The integrated microgrid control system then extracts the comprehensive operation data set of distributed photovoltaics in real time, and uploads the collected comprehensive operation data set to the integrated monitoring unit in real time through LaRa. The monitoring equipment group includes a photovoltaic inverter, a solar radiation intensity sensor, a humidity sensor, and a full sky imager; The comprehensive operation data set includes an environmental data set, an energy storage data set and a power data set; The environmental data set includes photovoltaic panel conversion efficiency Gpv, solar radiation intensity Iso, cloud coverage Ccl and air humidity Hhu; The energy storage data set includes the current discharge efficiency Pst of the energy storage device and the current temperature Tst of the energy storage device; The power data set includes micro power demand Dre and power loss Lre; The energy storage data set and the power data set are collected and acquired by real-time monitoring of distributed photovoltaic devices and energy storage devices by a distributed energy management system in a microgrid control system; The data storage unit is used to construct a MySQL relational database, and is provided with a write port to connect with the integrated monitoring unit, and writes the comprehensive operation data set collected in real time into the data storage table of the MySQL relational database for storage; The write port is a one-way setting that only allows the integrated monitoring unit to write into the MySQL relational database.

13. A distributed photovoltaic grid management system according to claim 12, characterized in that: The power balance and scheduling module includes a power generation prediction unit, an energy storage device optimization unit and a power balance scheduling analysis unit; The power generation prediction unit constructs a photovoltaic power generation prediction algorithm formula, extracts the environmental data set through the write port of the MySQL relational database, inputs it into the photovoltaic power generation prediction algorithm formula, calculates and outputs the predicted photovoltaic power generation PPV; The predicted photovoltaic power generation PPV is calculated and output by the following photovoltaic power generation prediction algorithm formula; PPV=Gpv×Apv×Iso×(1-Ccl)×(1-k1·Hhu); In the formula, Apv represents the area of ​​​​the photovoltaic panel, k1 represents the humidity correction coefficient, and the humidity correction coefficient k1 and the photovoltaic panel conversion efficiency Gpv are automatically output based on the historical meteorological data and actual photovoltaic power generation data and the machine learning training prediction model.

14. A distributed photovoltaic grid management system according to claim 12, characterized in that: The energy storage device optimization unit is used to integrate a temperature monitoring and regulating system in the energy storage device, and by constructing an energy storage device optimization algorithm formula, extract the current energy storage data set through the write port of the MySQL relational database, input it into the energy storage device optimization algorithm formula, and output the energy storage output power POP; The energy storage output power POP is calculated and obtained by the following energy storage device optimization algorithm formula; POP=η storage ×Pst×(1-k2(Tst-Topt) 2 ); Where η storage It represents the discharge efficiency of the energy storage device, k2 represents the temperature influence coefficient, and Topt represents the normal operating temperature of the energy storage device.

15. A distributed photovoltaic grid management system according to claim 12, characterized in that: The power balance scheduling analysis unit includes a power balance scheduling algorithm unit and a power balance evaluation unit; The power balance scheduling algorithm unit is used to construct a power balance formula, calculate the output microgrid power balance value Pbal based on the predicted photovoltaic power generation PPV and energy storage output power POP and combined with the power data set, and dynamically adjust the power supply and demand balance of the microgrid; The microgrid power balance value Pbal is calculated and obtained by the following algorithm formula: Pbal = (PPV + POP) - Dre - Lre; The power balance evaluation unit is used to preset a balance threshold value P based on the microgrid power balance standard, and then perform a preliminary comparative evaluation with the obtained microgrid power balance value Pbal to analyze the power demand of the microgrid unit. The specific evaluation content is as follows; When the microgrid power balance value Pbal ≥ the balance threshold P, it means that the current microgrid unit power supply is sufficient, the microgrid unit power is balanced and there is surplus power. At this time, the current dual-grid mode is further analyzed; exporting surplus power to an external microgrid unit when in networking mode; Stores surplus power when in island mode; When the microgrid power balance value Pbal < the balance threshold P, it means that the current microgrid unit power supply is insufficient and the distributed photovoltaic power generation of the microgrid unit is insufficient. At this time, power is allocated from the energy storage device first, and the current dual-grid mode is further analyzed; When in networking mode and energy storage is insufficient, power is obtained from external microgrid units; When in island mode the distributed load is reduced to 30%.

16. A distributed photovoltaic grid management system according to claim 12, characterized in that: The intelligent scheduling and energy distribution module is used to construct a scheduling algorithm formula when the energy storage is insufficient while in networking mode, calculate the output power scheduling value Pdis, and perform precise power scheduling and distribution through the microgrid control system; The power dispatch value Pdis is calculated and obtained by the following dispatch algorithm formula; In the formula, α i It represents the priority factor of the i-th microgrid unit, which is obtained based on the microgrid power balance value Pbal and the distance calculation. n represents the number of microgrid power sources participating in the scheduling. PPV i represents the photovoltaic power generation forecast of the i-th microgrid unit, POP i represents the energy storage output power POP of the i-th microgrid unit, Dre i Denotes the power demand of the i-th microgrid unit Dre, Lre i The power loss Lre of the i-th microgrid unit.

17. A distributed photovoltaic grid management system according to claim 12, characterized in that: The distributed photovoltaic efficiency analysis module includes a power efficiency analysis unit and an optimization evaluation unit; The power efficiency analysis unit is used to construct a power efficiency formula to calculate the output power efficiency Psys after the microgrid unit is dispatched and allocated, and comprehensively analyze the power efficiency of all microgrid units in the dispatch grid; The power efficiency Psys is calculated by the following power efficiency formula:

18. A distributed photovoltaic grid management system according to claim 10, characterized in that: The optimization evaluation unit performs a secondary comparative evaluation based on the preset efficiency threshold X and the acquired power efficiency Psys by the user to analyze the operation of the distributed photovoltaic system. The specific evaluation contents are as follows; When the power efficiency Psys ≥ the efficiency threshold X, it means that the distributed photovoltaic operation efficiency is normal and the supply and demand of the microgrid unit circuit in the table are balanced; When the power efficiency Psys is less than the efficiency threshold X, it indicates that the distributed photovoltaic operation efficiency is abnormal and the power supply and demand of the microgrid units in the table are unbalanced. At this time, the intelligent scheduling and energy distribution module is iteratively executed to perform power scheduling and distribution until the power supply and demand are balanced and the iteration is stopped.

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