Energy storage management system of distributed photovoltaic power generation equipment

Abstract

The invention belongs to the technical field of photovoltaic power generation, and particularly relates to an energy storage management system of distributed photovoltaic power generation equipment, which comprises a photovoltaic module used for converting illumination into direct current; the energy storage module is used for storing direct current; the grid-connected inverter is connected with the energy storage module and is used for converting the direct current into alternating current and supplying power to a load in cooperation with a power grid; the cloud platform is used for predicting the power demand J of the load in the next day and predicting the power generation R of the photovoltaic module in the next day; judging whether the sum of the next-day generating capacity and the remaining capacity meets the next-day power consumption of the load or not based on the next-day power demand, the next-day generating capacity and the remaining capacity by predicting the next-day power demand of the load and the next-day generating capacity of the photovoltaic module and obtaining the remaining capacity of the energy storage module; the decision module controls the power grid and the grid-connected inverter to supply power to the load; the influence on the chemical property of the energy storage battery, the acceleration on the aging of the energy storage battery and the sulfation phenomenon of the energy storage battery due to long-time deficiency of the energy storage battery are prevented.

Description

Technical Field

[0001] The present invention belongs to the technical field of photovoltaic power generation, and in particular to an energy storage management system for distributed photovoltaic power generation equipment. Background Art

[0002] With the urgent need for clean energy and the rapid decline in the cost of photovoltaic power, photovoltaic power generation technology has been widely used. In order to solve the shortage of electricity in some areas and to ease the pressure on the operation of local power grids, distributed photovoltaic power generation technology has also entered people's family life. A large number of photovoltaic power generation systems have been installed on household buildings to provide electricity for daily life.

[0003] In the prior art, distributed photovoltaic power generation equipment usually includes basic equipment such as photovoltaic cell modules, brackets, DC combiner boxes, DC distribution cabinets, grid-connected inverters, AC distribution cabinets, as well as power supply system monitoring devices and environmental monitoring devices; its operating mode is to convert solar energy into electrical energy through a solar cell module array under the condition of solar radiation, and then send it to the DC distribution cabinet through a DC combiner box, and finally invert it into AC power by a grid-connected inverter to supply the building's own load. Excess or insufficient power is regulated by connection to the power grid.

[0004] Based on the above background, when the regional power grid is under great pressure to operate, the promotion of distributed photovoltaic power generation technology can play a role in regulating the supply of the power grid. By converting sunlight into direct current and then converting direct current into alternating current, it can alleviate the operating pressure of the power grid to a certain extent and meet daily electricity demand. However, in the actual application stage, there is unreasonable management of the power grid and photovoltaic system for power supply to the load. Over-reliance on the photovoltaic system leads to frequent power loss of the energy storage module, affecting the chemical properties of the energy storage battery, accelerating the aging of the energy storage battery and causing the sulfation of the energy storage battery. To this end, the present invention provides an energy storage management system for distributed photovoltaic power generation equipment. Summary of the invention

[0005] In order to make up for the deficiencies of the prior art, at least one technical problem raised in the background technology is solved.

[0006] The technical solution adopted by the present invention to solve the technical problem is: an energy storage management system for distributed photovoltaic power generation equipment described in the present invention comprises: Photovoltaic panels, which convert sunlight into direct current electricity; Energy storage module, used to store direct current; The grid-connected inverter is connected to the energy storage module and is used to convert DC power into AC power, which is then used in conjunction with the grid to supply power to the load. It also includes a cloud platform for predicting the next day's power demand J of the load and the next day's power generation R of the photovoltaic module; the cloud platform communicates with the energy storage module; It also includes a power feedback module for recording the remaining power G of the energy storage module; It also includes a decision-making module for controlling the power grid and grid-connected inverters to supply power to the load: When R+G≤JV, the load is powered only by the grid; When JV<R+G≤J+V, the grid and the grid-connected inverter supply power to the load at the same time, and when the remaining power G is lower than the threshold, only the grid supplies power to the load; When R+G>J+V, only the grid-connected inverter supplies power to the load, and the maximum storage capacity S of the energy storage module is calculated according to the formula:

[0007] Where D represents the maximum capacity of the energy storage battery in the energy storage module; V is the error, which is used to reduce the frequent switching of the decision-making module to control the power grid and the grid-connected inverter due to the difference between the J value and the actual power demand; When G>S, the extra electricity is fed into the grid for sale at the end of the day.

[0008] Preferably, the cloud platform is also used to record the historical power consumption data of the load, and to construct a historical power consumption curve of the load according to the historical power consumption data of the load; and to predict the power demand J of the load the next day based on the historical power consumption curve of the load.

[0009] Preferably, the cloud platform decomposes the load power demand for the next day into peak power demand Jm and valley power demand Jn according to the load peak power consumption period and valley power consumption period; The decision module controls the power grid and the grid-connected inverter to supply power to the load according to the peak power demand Jm of the load.

[0010] Preferably, the method in which the decision module controls the power grid and the grid-connected inverter to supply power to the load according to the peak power demand Jm is: when , then only the grid supplies power to the load; when , the grid and the grid-connected inverter supply power to the load at the same time, and when the remaining power G is lower than the threshold, only the grid supplies power to the load; when , then only the grid-connected inverter supplies power to the load; in, Indicates the error of peak power demand Jm; .

[0011] Preferably, the maximum capacity D of the energy storage battery in the energy storage module varies with the running time: According to the formula:

[0012] Where D represents the initial maximum capacity of the energy storage battery; Indicates the attenuation value; It represents the attenuation coefficient of the maximum capacity of the energy storage battery; t represents the operating time of the energy storage battery.

[0013] Preferably, the method for obtaining the next day's power generation R is: Get weather forecast and historical data; Analyze the power generation of photovoltaic modules in the same weather conditions in history, and summarize and organize the power generation data; Calculate the arithmetic mean of the power generation data; Obtain an average data reflecting the power generation of the photovoltaic module, which is recorded as the average power generation; By obtaining the weather forecast for the next day, the corresponding historical average power generation is used as the predicted power generation R for the next day.

[0014] Preferably, it also includes a calculation module, which calculates the error rate between the actual power generation K of the photovoltaic module and the predicted power generation R of the next day according to the actual power generation of the photovoltaic module; According to the formula:

[0015] Among them, P represents the error rate between the actual power generation K of the photovoltaic module and the power generation R of the next day.

[0016] Preferably, the decision module is also used to analyze abnormal situations according to the error rate P; The method for analyzing abnormal conditions according to the error rate P is: Obtain the next day's power generation R, actual power generation K and calculation error rate P; If the error rate P≤5%, the PV module is judged to be normal; If the error rate P>5%, it is judged that the photovoltaic module is suspected to be abnormal.

[0017] Preferably, it also includes a monitoring module for monitoring whether there is a shadow area in the photovoltaic component; the monitoring module includes a camera for monitoring the state of the receiving surface of the photovoltaic component.

[0018] Preferably, based on the error rate P>5%, the monitoring module acquires the surface image of the photovoltaic module via a camera; If there is an obstruction that causes a shadow on the light receiving surface of the photovoltaic module, the photovoltaic module is judged to be abnormal; If there is no obstruction, it is determined that the connection line between the photovoltaic component and the energy storage module is faulty or aged.

[0019] The beneficial effects of the present invention are as follows: 1. The energy storage management system of a distributed photovoltaic power generation equipment described in the present invention predicts the next day's power demand of the load, the next day's power generation of the photovoltaic module, and obtains the remaining power of the energy storage module. Based on the next day's power demand, the next day's power generation, and the remaining power, it is determined whether the sum of the next day's power generation and the remaining power meets the next day's power consumption of the load; thereby controlling the power grid and the grid-connected inverter to supply power to the load through the decision module; preventing the energy storage battery from being affected by the chemical properties of the energy storage battery due to long-term deficit, accelerating the aging of the energy storage battery, and causing the sulfation phenomenon of the energy storage battery; 2. The energy storage management system of a distributed photovoltaic power generation equipment described in the present invention is based on the monitoring of the remaining power and the prediction of the power generation of the next day. If there is power remaining and stored in the energy storage module at the end of each natural day, considering the limited capacity of the energy storage battery in the energy storage module and avoiding affecting the thermochemical reaction of the energy storage module the next day and accelerating the aging of the energy storage battery, by calculating the extra power, the extra power is sold at the end of each natural day, which can alleviate the pressure on the energy storage battery the next day, thereby ensuring the operating state of the energy storage battery and avoiding accelerated aging of the energy storage battery. BRIEF DESCRIPTION OF THE DRAWINGS

[0020] The present invention will be further described below in conjunction with the accompanying drawings.

[0021] Figure 1 It is a flow chart of the present invention. DETAILED DESCRIPTION

[0022] In order to make the technical means, creative features, objectives and effects achieved by the present invention easy to understand, the present invention is further explained below in conjunction with specific implementation methods.

[0023] like Figure 1 As shown, an energy storage management system for distributed photovoltaic power generation equipment according to an embodiment of the present invention includes: a photovoltaic component for converting light into direct current; an energy storage module for storing direct current; a grid-connected inverter connected to the energy storage module for converting direct current into alternating current, and then cooperating with the power grid to supply power to the load; a cloud platform for predicting the power demand J of the load the next day and predicting the power generation R of the photovoltaic component the next day; the cloud platform communicates with the energy storage module; an electric quantity feedback module for recording the remaining electric quantity G of the energy storage module; and a decision module for controlling the power grid and the grid-connected inverter to supply power to the load: When R+G≤JV, the load is powered only by the grid; When JV<R+G≤J+V, the grid and the grid-connected inverter supply power to the load at the same time, and when the remaining power G is lower than the threshold, only the grid supplies power to the load; When R+G>J+V, only the grid-connected inverter supplies power to the load, and the maximum storage capacity S of the energy storage module is calculated according to the formula:

[0024] Where D represents the maximum capacity of the energy storage battery in the energy storage module; V is the error, which is used to reduce the frequent switching of the decision-making module to control the power grid and the grid-connected inverter due to the difference between the J value and the actual power demand; When G>S, the extra electricity is fed into the grid for sale at the end of the day.

[0025] In the existing technology, when the regional power grid is under great operating pressure, the promotion and use of distributed photovoltaic power generation technology can play a role in regulating the supply of the power grid. By converting sunlight into direct current and then converting direct current into alternating current, it can alleviate the operating pressure of the power grid to a certain extent and meet daily power demand. However, in the actual application stage, there is unreasonable management of the power grid and photovoltaic system for power supply to the load, and excessive reliance on the photovoltaic system leads to frequent power loss of the energy storage module, affecting the chemical properties of the energy storage battery, accelerating the aging of the energy storage battery and causing the sulfation of the energy storage battery. In view of the above, in one embodiment, a cloud platform is used to predict the load's next day power demand J, and then predict the next day's power generation R of the photovoltaic module; by calculating whether the sum of the next day's power generation R and the remaining power G can meet the load's next day's power demand J; if R+G≤JV, it means that the sum of the next day's power generation R and the remaining power G is less than or equal to the difference between the next day's power demand J and the error, then the power grid supplies power to the load, and when JV<R+G≤J+V, the power grid and the energy storage module simultaneously supply power to the load, and when G is equal to the threshold, the energy storage module stops supplying power, and only the power grid supplies power; when the sum of the next day's power generation R and the remaining power G is greater than the sum of the next day's power demand J and the error, the load can only be supplied by the grid-connected inverter, so as to prevent the energy storage battery from affecting the chemical properties of the energy storage battery due to long-term deficit, accelerating the aging of the energy storage battery and causing the sulfation of the energy storage battery; wherein the threshold is obtained from experience and is set according to actual usage requirements.

[0026] For example: the remaining power on the day G = 1kwh; the power generation on the next day R = 6kwh; the power demand on the next day J = 6.5kwh; let V = 2kwh; Then R+G=7kwh. If V is not set, then according to the judgment of the decision module, if the power demand J on the next day is less than R+G, only the grid-connected inverter will supply power to the load. If the actual power demand J'=7kwh, from the perspective of the energy storage battery alone, all the power stored in the energy storage battery will be consumed, resulting in a deficit in the energy storage battery. By setting the V value, R+G=7kwh is between [JV, J+V], and the grid-connected inverter and the grid supply power to the load at the same time, and when the remaining power G is lower than the threshold, only the grid supplies power to the load, which plays a role in ensuring that the energy storage battery is not depleted; even if the actual power demand Ji=7kwh, it will not cause the energy storage battery to be depleted.

[0027] For example: Maximum capacity D = 20kwh; remaining power on the day G = 16kwh; power generation on the next day R = 6kwh; power demand on the next day J = 4kwh; After calculation, the next day's power generation R meets the next day's power demand J, and there is still a surplus of 2Kwh; At the same time, G>S on that day, that is, 16>20-6; the energy storage battery will be fully charged the next day. Due to the different efficiencies of the grid-connected inverter and the photovoltaic modules, when the energy storage battery is about to be fully charged or is fully charged, it may cause the thermochemical reaction of the energy storage battery to increase, generate heat, and accelerate the aging of the energy storage battery. Therefore, the excess electricity is connected to the grid for sale on that day, which can alleviate the pressure on the energy storage battery the next day, and G and S are repeatedly calculated on the next day to ensure that the maximum storage capacity S in the energy storage battery is ≥ the remaining capacity G on that day; thereby ensuring the operating status of the energy storage battery and avoiding accelerated aging of the energy storage battery.

[0028] As an embodiment of the present invention, the cloud platform is also used to record the historical power consumption data of the load, construct the historical power consumption curve of the load according to the historical power consumption data of the load; and predict the power demand J of the load the next day based on the historical power consumption curve of the load.

[0029] Based on the above, the next day's power demand J represents the total power consumed by the load at the end of a natural day. In order to obtain a value closer to the actual value, the cloud platform is used to obtain the total power consumed by the load in multiple natural days, and the power consumption curve is constructed according to the historical power consumption data of the load. The next day's power demand J of the load is predicted through the trend of the historical power consumption curve. It is worth noting that the next day's power demand J of the load given here is not equivalent to the actual power consumption of the load the next day; based on the fact that the next day's power demand J of the load given here is not accurate, the error V is introduced when the above decision module makes a judgment. By setting the error V, the energy storage battery deficit can be effectively prevented; Specifically, after obtaining the historical power consumption data of the load, data preprocessing is performed, which includes steps such as data type conversion, data standardization, and missing value processing, so that the data is more suitable for subsequent modeling needs.

[0030] After data processing is completed, historical data is used to build a neural network model. In the model training and verification stage, historical data needs to be used to train the selected model. This involves steps such as parameter adjustment and network structure optimization to ensure that the model can effectively capture the patterns in the data. After the model training is completed, it needs to be verified on the test set to evaluate the prediction accuracy and performance of the model. Based on the verification results, the model parameters or structure may need to be further adjusted; The trained and validated model can be used to make predictions about future data. This stage may involve feeding future input data into the model to obtain the predicted electricity demand J for the next day.

[0031] As an implementation mode of the present invention, the cloud platform decomposes the load power demand for the next day into peak power demand Jm and valley power demand Jn according to the load peak power consumption period and valley power consumption period; The decision module controls the power grid and the grid-connected inverter to supply power to the load according to the peak power demand Jm of the load.

[0032] According to the operation of the existing power grid, during the peak power consumption period, the power grid operation pressure is large and the electricity price is high. Based on the cost and power consumption stability, the user's power consumption period is analyzed. Specifically, in one embodiment, the next day's power demand of the user's load is decomposed into the load peak power demand Jm and the load valley power demand Jn according to the peak power consumption period and the valley power consumption period; Based on electricity cost and stability, energy storage batteries are used to supply electricity during peak load periods. However, when electricity is used during valley load periods, since electricity prices are relatively cheap and the weather conditions of the next day are unknown, if energy storage batteries are still used for power supply, it may lead to a deficit of energy storage batteries the next day, which in turn causes an increase in electricity costs and instability. Therefore, by controlling the power grid and grid-connected inverter to supply power to the load according to the peak power demand Jm through the decision-making module, it is possible to ensure low-cost electricity use for users and maintain the stability of electricity use for users.

[0033] As an embodiment of the present invention, the method in which the decision module controls the power grid and the grid-connected inverter to supply power to the load according to the peak power demand Jm is: when , then only the grid supplies power to the load; when , the grid and the grid-connected inverter supply power to the load at the same time, and when the remaining power G is lower than the threshold, only the grid supplies power to the load; when , then only the grid-connected inverter supplies power to the load; in, Indicates the error of peak power demand Jm; .

[0034] Based on the above, J is decomposed into Jm and Jn. When R+G≤Jm, it means that the sum of the next day's power generation R and the residual current G is less than the peak power demand Jm of the load. Therefore, the power grid must be involved in the power supply. When R+G≤V, in order to prevent the energy storage battery from running out of power, only the power grid supplies power to the load; where V<Jm; When R+G>Jm, it means that the sum of the next day's power generation R and the remaining power G is greater than the peak power demand Jm of the load. Therefore, only the energy storage module can supply power to the load, and the power grid does not need to supply power to the load, which reduces the user's electricity cost and avoids the impact of the instability of the power grid during peak power consumption on the user. For example: When R=6kwh; G=4kwh; Jm=10kwh; V=2kwh; J=12kwh; Then at this time , but in order to ensure that the battery is not depleted, when G=2kwh, the grid supplies power to the load, and at the end of the day, the energy storage battery will not be depleted; If R=6kwh; G=12kwh; Jm=10kwh; V=2kwh; J=12kwh; at this time , the load is powered only by the grid-connected inverter, and at the end of the day, G is approximately 8kwh.

[0035] As an embodiment of the present invention, the maximum capacity D of the energy storage battery in the energy storage module varies with the running time: According to the formula:

[0036] Where D represents the initial maximum capacity of the energy storage battery; Indicates the attenuation value; It represents the attenuation coefficient of the maximum capacity of the energy storage battery; t represents the operating time of the energy storage battery.

[0037] Since the maximum capacity of the energy storage battery will decay with the change of running time, which will cause the actual maximum capacity D to change, in one embodiment, Dt represents the current maximum capacity of the energy storage battery; Specifically, for example, D = 20kwh, and Dt = 18kwh; If R=6kwh; G=16kwh; At this time, S=14kwh. If the S value is used, the electricity sold on that day is 2kwh. However, since Dt=18, St=12kwh, the electricity sold on that day should be 4kwh to prevent the loss of energy storage battery power and the occurrence of thermochemical reactions, which will lead to accelerated aging of the energy storage battery; where St represents the maximum storage capacity at the current moment.

[0038] As an embodiment of the present invention, the method for obtaining the next day's power generation R is: Get weather forecast and historical data; Analyze the power generation of photovoltaic modules in the same weather conditions in history, and summarize and organize the power generation data; Calculate the arithmetic mean of the power generation data; Obtain an average data reflecting the power generation of the photovoltaic module, which is recorded as the average power generation; By obtaining the weather forecast for the next day, the corresponding historical average power generation is used as the predicted power generation R for the next day.

[0039] In one embodiment, the method for predicting the power generation of the next day is as follows: since the power generation efficiency of the photovoltaic module is similar under normal circumstances, the power generation data thereof is not much different under the same illumination time and the same weather conditions; for example, if the temperature and weather of multiple natural days are similar, the power generation data of the photovoltaic modules of the multiple natural days are obtained and recorded as A1, A2, A3, and A4 respectively; According to the formula ; Obtain the average power generation Amean with similar environmental factors; When the weather forecast is similar to the environmental factor, use the average power generation as the predicted power generation R for the next day; By summarizing and arranging the power generation data in the historical data, we can obtain the historical data similar to the weather of the next day, and calculate the arithmetic mean to obtain the average power generation reflecting the power generation of the photovoltaic components. The average power generation is used as the predicted power generation R of the next day. Based on this, we can predict in advance the sum of the power generation R of the next day and the remaining power G and the size of the peak power demand Jm. Through judgment, we can decide whether the power grid and the grid-connected inverter will supply power to the load, so as to avoid the energy storage module being short or frequently opened and closed, which will cause the equipment to be vulnerable and increase the maintenance cost. As an embodiment of the present invention, it also includes a calculation module, which calculates the error rate between the actual power generation K of the photovoltaic module and the predicted power generation R of the next day according to the actual power generation of the photovoltaic module; According to the formula:

[0040] Among them, P represents the error rate between the actual power generation K of the photovoltaic module and the power generation R of the next day.

[0041] Since the actual power generation of the photovoltaic module will be affected by the shadow, the shadow is that the receiving surface of the photovoltaic module is blocked, resulting in a decrease in the power generation efficiency of the photovoltaic module, and the power generation per unit time is affected, which directly affects the actual power generation K of the photovoltaic module in a natural day; Based on the above, the error rate of the next day's power generation R of the photovoltaic module is calculated according to the next day's power generation R predicted by the photovoltaic module and the actual power generation K. Through the error rate calculation, the state of the photovoltaic module can be grasped to prevent the photovoltaic module from having shadow problems, which causes its power generation efficiency to fail to meet the standard and thus affects the power generation.

[0042] As an embodiment of the present invention, the decision module is further used to analyze abnormal situations according to the error rate P; The method for analyzing abnormal conditions according to the error rate P is: Obtain the next day's power generation R, actual power generation K and calculation error rate P; If the error rate P≤5%, the PV module is judged to be normal; If the error rate P>5%, it is judged that the photovoltaic module is suspected to be abnormal.

[0043] According to the calculated error rate, if the error rate is within 5%, 5% is due to the error caused by factors such as environment, resistance and aging caused by the charge and discharge cycle of the energy storage module; the PV module is judged to be normal and there is no shadow; if the error rate exceeds 5%, it means that the power generation of the PV module is significantly lower than the historical data, and the PV module is suspected to be abnormal; the PV module needs to be monitored to determine its status.

[0044] As an embodiment of the present invention, it also includes a monitoring module for monitoring whether there is a shadow area in the photovoltaic component; the monitoring module includes a camera for monitoring the state of the receiving surface of the photovoltaic component.

[0045] Based on the above, a monitoring module is set up. The monitoring module is set near the photovoltaic component and can monitor the receiving surface of the photovoltaic component. Specifically, a camera is used to capture the image of the receiving surface of the photovoltaic component, and then the image is analyzed to determine whether the surface of the photovoltaic component is blocked and a shadow is generated.

[0046] As an embodiment of the present invention, based on the error rate P>5%, the monitoring module acquires the surface image of the photovoltaic module via a camera; If there is an obstruction that causes a shadow on the light receiving surface of the photovoltaic module, the photovoltaic module is judged to be abnormal; If there is no obstruction, it is determined that the connection line between the photovoltaic component and the energy storage module is faulty or aged.

[0047] In one embodiment, when the error rate exceeds 5%, it is determined whether the photovoltaic assembly is blocked by the image captured by the monitoring module. If there is a blockage, it is determined that the photovoltaic assembly is abnormal and needs to be cleaned, and the error is caused by the blockage of the receiving surface of the photovoltaic assembly; If there is no obstruction, there is no abnormality in the photovoltaic module. The error is caused by aging or failure of the connection line between the photovoltaic module and the energy storage module, which causes the DC power generated by the photovoltaic module to be unable to be effectively input into the energy storage module, resulting in power loss.

[0048] Working principle: By predicting the next day's power demand of the load, the next day's power generation of the photovoltaic module, and obtaining the remaining power of the energy storage module, based on the next day's power demand, the next day's power generation and the remaining power, it is judged whether the sum of the next day's power generation and the remaining power can meet the load's power consumption for the next day; thus, the decision-making module controls the power grid and the grid-connected inverter to supply power to the load; and based on the monitoring of the remaining power and the prediction of the next day's power generation, if the energy storage module has power remaining and stored in the energy storage module at the end of each natural day, considering that the energy storage battery capacity in the energy storage module is limited, and to avoid affecting the thermochemical reaction of the energy storage module the next day and accelerating the aging of the energy storage battery, by calculating the extra power, at the end of each natural day, the extra power is sold, which can alleviate the pressure on the energy storage battery the next day, thereby ensuring the operating status of the energy storage battery and avoiding the accelerated aging of the energy storage battery.

[0049] The above shows and describes the basic principles, main features and advantages of the present invention. It should be understood by those skilled in the art that the present invention is not limited to the above embodiments. The above embodiments and descriptions are only for explaining the principles of the present invention. Without departing from the spirit and scope of the present invention, the present invention may have various changes and improvements, which fall within the scope of the present invention. The scope of protection of the present invention is defined by the attached claims and their equivalents.

Claims

1. An energy storage management system for distributed photovoltaic power generation equipment, characterized in that: include: Photovoltaic panels, which convert sunlight into direct current electricity; Energy storage module, used to store direct current; The grid-connected inverter is connected to the energy storage module and is used to convert DC power into AC power, which is then used in conjunction with the grid to supply power to the load. It also includes a cloud platform for predicting the next day's power demand J of the load and the next day's power generation R of the photovoltaic module; the cloud platform communicates with the energy storage module; It also includes a power feedback module for recording the remaining power G of the energy storage module; It also includes a decision-making module for controlling the power grid and grid-connected inverters to supply power to the load: When R+G≤JV, the load is powered only by the grid; When JV<R+G≤J+V, the grid and the grid-connected inverter supply power to the load at the same time, and when the remaining power G is lower than the threshold, only the grid supplies power to the load; When R+G>J+V, only the grid-connected inverter supplies power to the load, and the maximum storage capacity S of the energy storage module is calculated according to the formula: Where D represents the maximum capacity of the energy storage battery in the energy storage module; V is the error, which is used to reduce the frequent switching of the decision module to control the power grid and the grid-connected inverter due to the difference between the J value and the actual power demand; When G>S, the extra electricity is fed into the grid for sale at the end of the day.

2. The energy storage management system for distributed photovoltaic power generation equipment according to claim 1, characterized in that: The cloud platform is also used to record the historical power consumption data of the load, construct the historical power consumption curve of the load according to the historical power consumption data of the load; and predict the power demand J of the load the next day based on the historical power consumption curve of the load.

3. The energy storage management system of a distributed photovoltaic power generation equipment according to claim 2, characterized in that: The cloud platform decomposes the load power demand for the next day into peak power demand Jm and valley power demand Jn according to the load peak power consumption period and valley power consumption period; The decision module controls the power grid and the grid-connected inverter to supply power to the load according to the peak power demand Jm of the load.

4. The energy storage management system for distributed photovoltaic power generation equipment according to claim 3, characterized in that: The method in which the decision module controls the power grid and the grid-connected inverter to supply power to the load according to the peak power demand Jm is: when , then only the grid supplies power to the load; when , the grid and the grid-connected inverter supply power to the load at the same time, and when the remaining power G is lower than the threshold, only the grid supplies power to the load; when , then only the grid-connected inverter supplies power to the load; in, Indicates the error of peak power demand Jm; .

5. The energy storage management system for distributed photovoltaic power generation equipment according to claim 4, characterized in that: The maximum capacity D of the energy storage battery in the energy storage module varies with the running time: According to the formula: Where D represents the initial maximum capacity of the energy storage battery; Indicates the attenuation value; It represents the attenuation coefficient of the maximum capacity of the energy storage battery; t represents the operating time of the energy storage battery.

6. The energy storage management system for distributed photovoltaic power generation equipment according to claim 5, characterized in that: The method for obtaining the next day's power generation R is: Get weather forecast and historical data; Analyze the power generation of photovoltaic modules in the same weather conditions in history, and summarize and organize the power generation data; Calculate the arithmetic mean of the power generation data; Obtain an average data reflecting the power generation of the photovoltaic module, which is recorded as the average power generation; By obtaining the weather forecast for the next day, the corresponding historical average power generation is used as the predicted power generation R for the next day.

7. The energy storage management system for distributed photovoltaic power generation equipment according to claim 6, characterized in that: It also includes a calculation module, which calculates the error rate between the actual power generation K of the photovoltaic module and the predicted power generation R of the next day according to the actual power generation of the photovoltaic module; According to the formula: Among them, P represents the error rate between the actual power generation K of the photovoltaic module and the power generation R of the next day.

8. The energy storage management system for distributed photovoltaic power generation equipment according to claim 7, characterized in that: The decision module is also used to analyze abnormal situations according to the error rate P; The method for analyzing abnormal conditions according to the error rate P is: Obtain the next day's power generation R, actual power generation K and calculation error rate P; If the error rate P≤5%, the PV module is judged to be normal; If the error rate P>5%, it is judged that the photovoltaic module is suspected to be abnormal.

9. The energy storage management system for distributed photovoltaic power generation equipment according to claim 8, characterized in that: It also includes a monitoring module for monitoring whether there is a shadow area on the photovoltaic component; the monitoring module includes a camera for monitoring the state of the receiving surface of the photovoltaic component.

10. The energy storage management system of a distributed photovoltaic power generation equipment according to claim 9, characterized in that: Based on the error rate P>5%, the monitoring module obtains the surface image of the photovoltaic module through the camera; If there is an obstruction that causes a shadow on the light receiving surface of the photovoltaic module, the photovoltaic module is judged to be abnormal; If there is no obstruction, it is determined that the connection line between the photovoltaic component and the energy storage module is faulty or aged.

Images