Optimized operation method for energy storage system of light storage type charging station

Abstract

The invention relates to the technical field of photovoltaic energy storage, and discloses a method for optimizing operation of an energy storage system of a light storage type charging station, and the method comprises the following steps: 1, carrying out the charging judgment of a vehicle; step 2, optimizing charging distribution; step 3, energy storage optimization; step 4, load optimization; 5, a multi-objective optimization model is established; and 6, real-time scheduling and feedback are carried out. According to the invention, the system preferentially uses the power of the power grid for charging in the valley period with low electricity price, thereby improving the utilization rate of the power grid, reducing the pressure of the power grid in the tip period and the peak period by reasonably allocating the charging power of the power grid and photovoltaic energy storage, and reducing the charging power of the power grid in the tip period and the peak period. The system can effectively reduce the load pressure of the power grid, avoids the impact on the power grid caused by excessive power consumption in the peak period, and achieves the beneficial effect of improving the load of the power grid side and the energy storage side at the same time by dynamically adjusting the charging power proportion # imgabs0 # of the power grid and smoothing the load curve of the power grid.

Description

Technical Field

[0001] The present invention relates to the technical field of photovoltaic energy storage, and in particular to a method for optimizing the operation of a photovoltaic energy storage system of a charging station. Background Art

[0002] As a new charging facility, the photovoltaic storage charging station can realize the on-site integration of renewable energy and electric vehicles and has been widely recognized. As one of the most important components of the photovoltaic storage charging station, the capacity of the energy storage system involved in the operation during the dispatch cycle will directly affect the comprehensive performance of the charging station.

[0003] Prior art CN 112418605 A A method for optimizing the operation of a photovoltaic charging station energy storage system, which analyzes the system structure, operation strategy and load characteristics of the photovoltaic charging station; takes the minimum grid-side load variance, the minimum energy storage system operation and maintenance cost and the minimum power purchase fee from the grid as objective functions, takes the energy storage system power, charge state and grid-side power supply power as constraints, and establishes a multi-objective optimization operation model for the energy storage system; and effectively improves the load fluctuation level on the grid side.

[0004] Although the existing technology has improved the load fluctuation level on the grid side, the photovoltaic storage charging station is powered by a photovoltaic hybrid grid. It converts solar energy into electricity through photovoltaic power generation technology, stores it in energy storage equipment, and provides charging services for electric vehicles when needed. The existing technology can only improve the load fluctuation on the grid side, but cannot improve the energy storage load measurement. At the same time, the mainstream of the existing technology adopts separate charging, that is, the grid mainly charges the car, and energy storage is supplementary. The two switch with each other and do not charge together. Moreover, because the domestic electricity price adopts segmented billing, the peak electricity price in Pinggu is inconsistent, and separate charging is adopted. Even if the energy storage power supply is used alone during the peak electricity price period, it cannot meet the vehicle demand in the power station, which leads to the inability of photovoltaic power generation to reduce the charging cost well. Summary of the invention

[0005] In view of the shortcomings of the prior art, the present invention provides a method for optimizing the operation of a photovoltaic charging station energy storage system, which can improve the grid side and the energy storage load measurement at the same time. The energy storage and the grid are simultaneously involved in car charging to reduce the charging cost of the car owner, thus solving the problems of the above-mentioned technology.

[0006] To achieve the above object, the present invention provides the following technical solution: a method for optimizing the operation of a photovoltaic charging station energy storage system, wherein the photovoltaic charging station energy storage system includes photovoltaic modules, inverters, junction boxes, DC power distribution cabinets, AC power distribution cabinets, photovoltaic storage batteries, and bidirectional DC-DC converters. The optimization method includes the following steps:

[0007] Step 1: Vehicle charging determination: The solar storage charging station detects whether the charging gun is connected to the car for charging. If it is charging, it proceeds to step 2; if not, it proceeds to step 3;

[0008] Step 2, charging distribution optimization: the system switches modes according to the current power grid electricity price, which includes valley, flat, peak and peak. When the electricity price is at the valley price, the power grid current accounts for 100%, when the electricity price is at the flat price, the power grid current accounts for 65%-75%, when the electricity price is at the peak price, the power grid current accounts for 40%-50%, when the electricity price is at the peak price, the power grid current accounts for 0%-10%, and the rest is supplied by photovoltaic storage batteries. When the photovoltaic storage batteries and the power grid are jointly powered, a bidirectional DC-DC converter is used to adjust the voltage;

[0009] Step 3, energy storage optimization: the system reads the remaining power of the photovoltaic storage battery, calculates the full charge time according to the current power generation of the photovoltaic module, and supplements it in combination with the power price of the grid. If the charging period of the photovoltaic energy storage battery overlaps with the valley price and the parity price period, the photovoltaic storage battery will be charged by the grid. When the grid is charging, the grid supply current accounts for 75%-90% when the electricity price is at the valley price, and the grid supply current accounts for 10%-20% when the electricity price is at the parity price. The system does not use the grid to supplement the photovoltaic energy storage battery during the peak price and peak price periods;

[0010] Step 4: Load optimization: Real-time collection of photovoltaic power generation, energy storage system state of charge (SOC), power supply capacity of the grid, and charging demand of electric vehicles. Use a short-term load forecasting model: LSTM neural network to forecast photovoltaic power generation, electric vehicle charging demand, and grid electricity price in the future. Based on the forecast results, dynamically adjust the power supply ratio of the grid and energy storage system to ensure optimal load distribution in different electricity price periods: valley, flat, peak, and peak.

[0011] Step 5. Multi-objective optimization model: Establish a multi-objective optimization model, and the objective functions include: Minimize grid-side load variance: Reduce grid-side load fluctuations by optimizing the power supply ratio between the grid and the energy storage system; Minimize the operation and maintenance cost of the energy storage system: Optimize the charging and discharging strategy of the energy storage system, extend battery life, and reduce maintenance costs; Minimize charging costs: Combined with the segmented electricity price mechanism, give priority to using grid electricity and photovoltaic power generation during valley price periods to charge electric vehicles. Constraints include: power limit and state of charge SOC limit of the energy storage system, power supply limit on the grid side, and fluctuation limit of photovoltaic power generation. Use the NSGA-III algorithm to solve the multi-objective optimization model, obtain the Pareto optimal solution set, and screen out the optimal compromise solution through the fuzzy clustering method;

[0012] Step 6: Real-time dispatch and feedback: The system monitors the changes in photovoltaic power generation, energy storage system charge status, grid electricity prices, and electric vehicle charging demand in real time, dynamically adjusts the power supply ratio between the grid and the energy storage system, and optimizes the charging and discharging strategy according to the actual operating results. If the energy storage system has insufficient discharge capacity during peak electricity price periods, the system adjusts the charging strategy during valley periods and increases the charging capacity of the energy storage system for subsequent use.

[0013] During off-peak hours when electricity prices are lower, the system gives priority to using grid electricity for charging. Car owners can charge when electricity prices are lowest, thereby significantly reducing charging costs.

[0014] During peak hours when electricity prices are higher, the energy storage system can release previously stored electricity to supplement the shortage of the power grid, thereby avoiding direct grid charging during high electricity price periods.

[0015] The charging system intelligently adjusts the charging method according to the real-time electricity price and load conditions, and selects the optimal charging time and method (grid or energy storage). This flexibility allows car owners to charge when the electricity price is lower, further reducing charging costs.

[0016] The system can flexibly decide whether to charge electric vehicles through the grid or energy storage according to the grid load conditions, ensuring optimization of charging costs.

[0017] Energy storage systems store electricity during off-peak electricity price periods, especially during periods of low charging demand (such as at night), and the use of cheap electricity when the burden on transportation and the power grid is reduced can effectively reduce charging costs.

[0018] When the demand for electric vehicle charging peaks (peak electricity prices), the stored electricity is released by the energy storage system, and car owners can avoid charging directly from the grid during periods of high electricity prices.

[0019] By charging the energy storage system through renewable energy such as photovoltaics, car owners can enjoy lower charging costs in the long run and reduce their dependence on traditional power grids.

[0020] Using clean energy to charge not only helps reduce costs, but also enhances the car owner's environmental image and social responsibility.

[0021] When the grid load is too high, the system can help balance the grid load by reducing the amount of charging or limiting charging to the grid, which helps reduce the overall grid operating costs and ultimately passes it back to the car owner's electricity bill.

[0022] Under the demand response mechanism, car owners can choose to charge their cars through energy storage when the grid load is too high, and obtain corresponding subsidies or incentives, thereby further reducing costs.

[0023] Preferably, the charging determination calculation in step 1 is:

[0024]

[0025] in: is a Boolean variable indicating the charging status; Indicates that there is no car charging, the system enters step 3; otherwise It means that the charging gun has been connected to the car for charging.

[0026] Preferably, the charging distribution optimization calculation in step 2 is:

[0027] set up: Indicates the total supply current; Indicates the photovoltaic battery supply current;

[0028] According to the electricity price period, the proportion of grid power supply current The value range of is as follows: Valley price: (100%) Parity: ; Tip price: ; Peak price: ;

[0029] The proportion of power supply current of photovoltaic storage battery is ;

[0030]

[0031]

[0032] in, The value of is based on the electricity price period Sure:

[0033]

[0034] in: is the grid supply current, which is composed of the total current Multiply by the proportion of power supply from the grid get; The value of is based on the electricity price period Dynamic adjustment ensures optimal power supply distribution during different electricity price periods.

[0035] Preferably, the full charge time of the photovoltaic storage battery in step 3 is calculated as:

[0036]

[0037] The proportion of grid charging power in step 3 is calculated as:

[0038]

[0039] in: Indicates the remaining power of the photovoltaic storage battery, unit: kWh; Indicates the charging power of the grid, unit: kW; Indicates the proportion of grid charging power; Indicates the current power grid electricity price period: valley, flat, peak, peak; valley price: ;parity: ; Tip price and peak price: ; The proportion of charging power of photovoltaic storage batteries is .

[0040] Preferably, the proportion of photovoltaic storage battery charging power in step 3 is calculated as:

[0041]

[0042] in: To express the charging power of the photovoltaic storage battery, the unit is kilowatt; is the total charging power;

[0043] The proportion of grid charging power in step 3 The value of is calculated as:

[0044]

[0045] in: The proportion of charging power to the grid.

[0046] Preferably, the total power supply power in step 4 is calculated as:

[0047]

[0048] The proportion of power supplied by the power grid is calculated as: ;

[0049] The power supply ratio of the energy storage system is calculated as: ;

[0050] in: Indicates the photovoltaic module at time The power generation capacity, unit: kW; Indicates the power grid at time Power supply capacity, unit: kW; Indicates the proportion of power supplied by the power grid; Indicates the total power supply, unit: kW.

[0051] Preferably, the power supply ratio of the power grid in step 4 is Dynamic adjustment:

[0052]

[0053] The proportion of power supplied by the energy storage system in step 4 The dynamic adjustment is:

[0054]

[0055] in: Indicates at time When , the proportion of photovoltaic battery power supply to the total power supply;

[0056] In step 4, the electric vehicle charging power is calculated as:

[0057]

[0058] in: Indicates that electric vehicles are Charging power, unit: kW.

[0059] Preferably, the minimum grid load variance in step 5 is calculated as follows:

[0060]

[0061] in, Represents the time series variance of the power supplied by the power grid;

[0062] The minimum operation and maintenance cost of the energy storage system is calculated as:

[0063]

[0064] in: Indicates time The unit maintenance cost of the energy storage system is Indicates time The energy storage system discharge power at Indicates time The energy storage system charging power at

[0065] The minimum charging cost is calculated as:

[0066]

[0067] in: Indicates time The grid electricity price at that time, Indicates time The grid power supply power at that time.

[0068] Preferably, the constraints in step 5 include:

[0069] Energy storage system power limit:

[0070]

[0071]

[0072] in, is the maximum discharge power of the energy storage system, is the maximum charging power of the energy storage system;

[0073] State of Charge (SOC) Limits: ;

[0074] in, and are the minimum and maximum states of charge of the energy storage system, respectively;

[0075] Power supply limit on the grid side:

[0076] in, is the maximum power supply of the power grid

[0077] Limits on the fluctuation of photovoltaic power generation:

[0078] in, is the maximum power generation capacity of the photovoltaic system.

[0079] Preferably, the real-time scheduling model in step 6 is:

[0080]

[0081] in: For time The grid electricity price at that time; For time The energy storage system discharge cost at 10 ...

[0082] The adjustment calculation for insufficient discharge capacity during the peak electricity price period in step 6 is:

[0083] If the energy storage system's discharge capacity is insufficient during peak electricity price periods, the system will adjust the charging strategy during off-peak periods to increase the charging capacity of the energy storage system;

[0084] Increase the amount of charging during off-peak hours:

[0085]

[0086] in: This is the insufficient discharge capacity of the energy storage system during peak electricity price periods;

[0087] Charging power adjustment during the off-peak period:

[0088]

[0089] in: It is the charging power during the adjusted off-peak period.

[0090] Preferably, .

[0091] Compared with the prior art, the present invention provides a method for optimizing the operation of a photovoltaic charging station energy storage system, which has the following beneficial effects:

[0092] 1. The present invention improves the utilization rate of the power grid and balances the load of the power grid by giving priority to using the power grid for charging during the off-peak period when the electricity price is low. By rationally allocating the charging power of the power grid and photovoltaic energy storage, the pressure of the power grid during the peak and peak periods is reduced. During the peak and peak periods, by reducing the charging power of the power grid, the system can effectively reduce the load pressure of the power grid and avoid the impact of excessive electricity consumption on the power grid during peak periods. By dynamically adjusting the proportion of power grid charging power , smooth the grid load curve, the grid reduces power transmission during peak load periods, especially during peak and peak periods, using the photovoltaic energy storage system's own power supply, thereby reducing the load fluctuations of the grid. During peak demand periods, the energy storage system provides rapid response capabilities, instantly supplements the grid's needs, reduces instantaneous fluctuations in grid load, and improves the overall stability of the power system, achieving the beneficial effect of improving both the grid side and the energy storage load at the same time.

[0093] 2. The present invention uses a charging system to intelligently adjust the charging method according to real-time electricity prices and load conditions, and select the optimal charging time and method. The flexibility allows car owners to charge when electricity prices are low, further reducing charging costs. The system can flexibly decide to charge electric vehicles through the power grid or energy storage according to the load conditions of the power grid, ensuring the optimization of charging costs. The energy storage system stores electricity during non-peak electricity price periods, especially during periods of low charging demand. The use of cheap electricity when the burden on transportation and the power grid is reduced can effectively reduce charging costs. When the demand for electric vehicle charging peaks, the stored electricity is released through the energy storage system, and car owners can avoid charging directly from the power grid during periods of high electricity prices, achieving the beneficial effect of both energy storage and the power grid participating in car charging to reduce the charging costs of car owners.

[0094] 3. The present invention equips the photovoltaic charging station with an intelligent management system, which can monitor the power grid, electricity price and photovoltaic power generation status in real time, and automatically select the best charging and discharging strategy. When photovoltaic power generation is insufficient, the system can give priority to the use of electricity provided by the energy storage battery to meet the charging demand, thereby reducing dependence on the power grid and achieving efficient use of energy, achieving the beneficial effect of improving the energy storage waste caused by the lack of power source at night of photovoltaic components. BRIEF DESCRIPTION OF THE DRAWINGS

[0095] Figure 1It is a schematic diagram of the steps of the present invention; DETAILED DESCRIPTION

[0096] 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.

[0097] See also Figure 1 A method for optimizing the operation of a photovoltaic charging station energy storage system, wherein the photovoltaic charging station energy storage system includes photovoltaic modules, inverters, junction boxes, DC power distribution cabinets, AC power distribution cabinets, photovoltaic storage batteries, and bidirectional DC-DC converters. The optimization method includes the following steps:

[0098] Step 1: Vehicle charging determination: The solar storage charging station detects whether the charging gun is connected to the car for charging. If it is charging, it proceeds to step 2; if not, it proceeds to step 3;

[0099] Step 2, charging distribution optimization: the system switches modes according to the current power grid electricity price, which includes valley, flat, peak and peak. When the electricity price is at the valley price, the power grid current accounts for 100%, when the electricity price is at the flat price, the power grid current accounts for 65%-75%, when the electricity price is at the peak price, the power grid current accounts for 40%-50%, when the electricity price is at the peak price, the power grid current accounts for 0%-10%, and the rest is supplied by photovoltaic storage batteries. When the photovoltaic storage batteries and the power grid are jointly powered, a bidirectional DC-DC converter is used to adjust the voltage;

[0100] Step 3, energy storage optimization: the system reads the remaining power of the photovoltaic storage battery, calculates the full charge time according to the current power generation of the photovoltaic module, and supplements it in combination with the power price of the grid. If the charging period of the photovoltaic energy storage battery overlaps with the valley price and the parity price period, the photovoltaic storage battery will be charged by the grid. When the grid is charging, the grid supply current accounts for 75%-90% when the electricity price is at the valley price, and the grid supply current accounts for 10%-20% when the electricity price is at the parity price. The system does not use the grid to supplement the photovoltaic energy storage battery during the peak price and peak price periods;

[0101] Step 4: Load optimization: Real-time collection of photovoltaic power generation, energy storage system state of charge (SOC), power supply capacity of the grid, and charging demand of electric vehicles. Use a short-term load forecasting model: LSTM neural network to forecast photovoltaic power generation, electric vehicle charging demand, and grid electricity price in the future. Based on the forecast results, dynamically adjust the power supply ratio of the grid and energy storage system to ensure optimal load distribution in different electricity price periods: valley, flat, peak, and peak.

[0102] Step 5. Multi-objective optimization model: Establish a multi-objective optimization model, and the objective functions include: Minimize grid-side load variance: Reduce grid-side load fluctuations by optimizing the power supply ratio between the grid and the energy storage system; Minimize the operation and maintenance cost of the energy storage system: Optimize the charging and discharging strategy of the energy storage system, extend battery life, and reduce maintenance costs; Minimize charging costs: Combined with the segmented electricity price mechanism, give priority to using grid electricity and photovoltaic power generation during valley price periods to charge electric vehicles. Constraints include: power limit and state of charge SOC limit of the energy storage system, power supply limit on the grid side, and fluctuation limit of photovoltaic power generation. Use the NSGA-III algorithm to solve the multi-objective optimization model, obtain the Pareto optimal solution set, and screen out the optimal compromise solution through the fuzzy clustering method;

[0103] Step 6: Real-time dispatch and feedback: The system monitors the changes in photovoltaic power generation, energy storage system charge status, grid electricity prices, and electric vehicle charging demand in real time, dynamically adjusts the power supply ratio between the grid and the energy storage system, and optimizes the charging and discharging strategy according to the actual operating results. If the energy storage system has insufficient discharge capacity during peak electricity price periods, the system adjusts the charging strategy during valley periods and increases the charging capacity of the energy storage system for subsequent use.

[0104] During off-peak hours when electricity prices are lower, the system gives priority to using grid power for charging, which improves grid utilization and balances grid load. By rationally allocating the charging power of the grid and photovoltaic energy storage, the pressure on the grid during peak hours is reduced.

[0105] During peak hours, by reducing the charging power of the grid (for example, setting it to 0), the system can effectively reduce the load pressure on the grid and avoid the impact of excessive power consumption on the grid during peak hours.

[0106] The energy storage system releases stored electrical energy when the grid load is high (such as during peak hours), which not only reduces the burden on the energy storage system when it is in a charging state, but also provides additional power for the grid, achieving load balance.

[0107] The photovoltaic power generation system charges the energy storage system during the peak power generation period (usually during the day), and stores excess electricity during the period of lower electricity prices (valley price period), reducing the waste of electricity. This not only optimizes the efficiency of electricity use, but also provides a sustainable energy source for the power grid supply.

[0108] When the electricity price of the grid is low, the energy storage system can be charged, and then release electricity when the electricity price is high (such as peak hours), which improves economic efficiency. Providing electricity during high electricity price periods helps the grid accept less external power input, which helps reduce the burden on the grid and transmission losses.

[0109] By dynamically adjusting the proportion of charging power in the power grid, the load curve of the power grid is smoothed. The power grid reduces power transmission during peak load periods, especially during peak and peak periods, and uses the photovoltaic energy storage system's own power supply, thereby reducing the load fluctuation of the power grid.

[0110] During peak demand periods, energy storage systems provide rapid response capabilities, instantly replenishing grid needs, reducing instantaneous fluctuations in grid load, and improving the overall stability of the power system.

[0111] Example 1: Valley price period

[0112] set up

[0113] Electricity price status: Valley price

[0114] Total supply current : 100A

[0115] Photovoltaic power generation :50kW

[0116] Remaining power of photovoltaic storage battery : 200kWh

[0117] Total charging power: 80 kW

[0118] Grid power supply ratio\(\alpha\): 1

[0119] calculate

[0120] 1. Grid supply current:

[0121]

[0122] 2. Photovoltaic battery supply current:

[0123]

[0124] 3. Photovoltaic storage battery full charge time:

[0125]

[0126] 4. Grid charging power:

[0127]

[0128] 5. Photovoltaic battery charging power:

[0129]

[0130] Example 2: Parity Period

[0131] set up

[0132] Electricity price status: parity

[0133] Total supply current : 100A

[0134] Photovoltaic power generation :50kW

[0135] Remaining power of photovoltaic storage battery : 200kWh

[0136] Total charging power :80kW

[0137] Power grid power supply ratio : Take the middle value of 0.70

[0138] calculate

[0139] 1. Grid supply current:

[0140]

[0141] 2. Photovoltaic battery supply current:

[0142]

[0143] 3. Photovoltaic storage battery full charge time:

[0144]

[0145] 4. Grid charging power:

[0146]

[0147] 5. Photovoltaic battery charging power:

[0148]

[0149] Example 3: Peak Price Period

[0150] set up

[0151] Electricity price status: sharp price

[0152] Total supply current : 100A

[0153] Photovoltaic power generation :50kW

[0154] Remaining power of photovoltaic storage battery : 200kWh

[0155] Total charging power :80kW

[0156] Power grid power supply ratio : Take the middle value 0.45

[0157] calculate

[0158] 1. Grid supply current:

[0159]

[0160] 2. Photovoltaic battery supply current:

[0161]

[0162] 3. Photovoltaic storage battery full charge time:

[0163]

[0164] 4. Grid charging power:

[0165]

[0166] 5. Photovoltaic battery charging power:

[0167]

[0168] Example 4: Peak Price Period

[0169] set up

[0170] Electricity price status: Peak price

[0171] Total supply current : 100A

[0172] Photovoltaic power generation :50kW

[0173] Remaining power of photovoltaic storage battery : 200kWh

[0174] Total charging power :80kW

[0175] Power grid power supply ratio : value 0.05

[0176] 1. Grid supply current:

[0177]

[0178] 2. Photovoltaic battery supply current:

[0179]

[0180] 3. Photovoltaic storage battery full charge time:

[0181]

[0182] 4. Grid charging power:

[0183]

[0184] 5. Photovoltaic battery charging power:

[0185]

[0186] Example 1 (Grain Price):

[0187] Grid supply current: 100A

[0188] Photovoltaic battery supply current: 0A

[0189] Photovoltaic battery full charge time: 4 hours

[0190] Grid charging power: 80kW

[0191] Photovoltaic battery charging power: 0kW

[0192] Example 2 (parity):

[0193] Grid supply current: 70A

[0194] Photovoltaic battery supply current: 30A

[0195] Photovoltaic battery full charge time: 4 hours

[0196] Grid charging power: 8kW

[0197] Photovoltaic battery charging power: 72kW

[0198] Example 3 (sharp price):

[0199] Grid supply current: 45A

[0200] Photovoltaic battery supply current: 55A

[0201] Photovoltaic battery full charge time: 4 hours

[0202] Grid charging power: 0kW

[0203] Photovoltaic battery charging power: 80kW

[0204] Example 4 (peak price):

[0205] Grid supply current: 5A

[0206] Photovoltaic battery supply current: 95A

[0207] Photovoltaic battery full charge time: 4 hours

[0208] Grid charging power: 0kW

[0209] Photovoltaic battery charging power: 80kW

[0210] These embodiments demonstrate how a solar-storage charging station can optimize power distribution and charging efficiency during different electricity price periods.

[0211] Although embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that various changes, modifications, substitutions and alterations may be made to the embodiments without departing from the principles and spirit of the invention, the scope of which is defined by the appended claims and their equivalents.

Claims

1. A method for optimizing the operation of a photovoltaic charging station energy storage system, wherein the photovoltaic charging station energy storage system comprises a photovoltaic module, an inverter, a junction box, a DC distribution cabinet, an AC distribution cabinet, a photovoltaic storage battery, and a bidirectional DC-DC converter, characterized in that: The optimization method comprises the following steps: Step 1: Vehicle charging determination: The solar storage charging station detects whether the charging gun is connected to the car for charging. If it is charging, it proceeds to step 2; if not, it proceeds to step 3; Step 2, charging distribution optimization: the system switches modes according to the current power grid electricity price, which includes valley, flat, peak and peak. When the electricity price is at the valley price, the power grid current accounts for 100%, when the electricity price is at the flat price, the power grid current accounts for 65%-75%, when the electricity price is at the peak price, the power grid current accounts for 40%-50%, when the electricity price is at the peak price, the power grid current accounts for 0%-10%, and the rest is supplied by photovoltaic storage batteries. When the photovoltaic storage batteries and the power grid are jointly powered, a bidirectional DC-DC converter is used to adjust the voltage; Step 3, energy storage optimization: the system reads the remaining power of the photovoltaic storage battery, calculates the full charge time according to the current power generation of the photovoltaic module, and supplements it in combination with the power price of the grid. If the charging period of the photovoltaic energy storage battery overlaps with the valley price and the parity price period, the photovoltaic storage battery will be charged by the grid. When the grid is charging, the grid supply current accounts for 75%-90% when the electricity price is at the valley price, and the grid supply current accounts for 10%-20% when the electricity price is at the parity price. The system does not use the grid to supplement the photovoltaic energy storage battery during the peak price and peak price periods; Step 4: Load optimization: Real-time collection of photovoltaic power generation, energy storage system state of charge (SOC), power supply capacity of the grid, and charging demand of electric vehicles. Use a short-term load forecasting model: LSTM neural network to forecast photovoltaic power generation, electric vehicle charging demand, and grid electricity price in the future. Based on the forecast results, dynamically adjust the power supply ratio of the grid and energy storage system to ensure optimal load distribution in different electricity price periods: valley, flat, peak, and peak. Step 5. Multi-objective optimization model: Establish a multi-objective optimization model, and the objective functions include: Minimize grid-side load variance: Reduce grid-side load fluctuations by optimizing the power supply ratio between the grid and the energy storage system; Minimize the operation and maintenance cost of the energy storage system: Optimize the charging and discharging strategy of the energy storage system, extend battery life, and reduce maintenance costs; Minimize charging costs: Combined with the segmented electricity price mechanism, give priority to using grid electricity and photovoltaic power generation during valley price periods to charge electric vehicles. Constraints include: power limit and state of charge SOC limit of the energy storage system, power supply limit on the grid side, and fluctuation limit of photovoltaic power generation. Use the NSGA-III algorithm to solve the multi-objective optimization model, obtain the Pareto optimal solution set, and screen out the optimal compromise solution through the fuzzy clustering method; Step 6: Real-time dispatch and feedback: The system monitors the changes in photovoltaic power generation, energy storage system charge status, grid electricity prices, and electric vehicle charging demand in real time, dynamically adjusts the power supply ratio between the grid and the energy storage system, and optimizes the charging and discharging strategy according to the actual operating results. If the energy storage system has insufficient discharge capacity during peak electricity price periods, the system adjusts the charging strategy during valley periods and increases the charging capacity of the energy storage system for subsequent use.

2. The method for optimizing the operation of a photovoltaic charging station energy storage system according to claim 1, characterized in that: The calculation of step 1 charging determination is: in: is a Boolean variable indicating the charging status; Indicates that there is no car charging, the system enters step 3; otherwise It means that the charging gun has been connected to the car for charging.

3. The method for optimizing the operation of a photovoltaic charging station energy storage system according to claim 1, characterized in that: The charging distribution optimization calculation in step 2 is: set up: Indicates the total supply current; Indicates the photovoltaic battery supply current; According to the electricity price period, the proportion of grid power supply current The value range of is as follows: Grain price: (100%) Parity: ; Tip price: ; Peak price: ; The proportion of power supply current of photovoltaic storage battery is ; in, The value of is based on the electricity price period Sure: in: is the grid supply current, which is composed of the total current Multiply by the proportion of power supply from the grid get; The value of is based on the electricity price period Dynamic adjustment ensures optimal power supply distribution during different electricity price periods.

4. The method for optimizing the operation of a photovoltaic charging station energy storage system according to claim 1, characterized in that: The photovoltaic storage battery full charge time in step 3 is calculated as: The proportion of grid charging power in step 3 is calculated as: in: Indicates the remaining power of the photovoltaic storage battery, unit: kWh; Indicates the charging power of the power grid, unit: kW; Indicates the proportion of grid charging power; Indicates the current power grid electricity price period: valley, flat, peak, peak; valley price: ;parity: ; Tip price and peak price: ; The proportion of charging power of photovoltaic storage batteries is .

5. The method for optimizing the operation of a photovoltaic charging station energy storage system according to claim 4, characterized in that: The proportion of photovoltaic battery charging power in step 3 is calculated as: in: To express the charging power of the photovoltaic storage battery, the unit is kilowatt; is the total charging power; The proportion of grid charging power in step 3 The value of is calculated as: in: The proportion of charging power to the grid.

6. The method for optimizing the operation of a photovoltaic charging station energy storage system according to claim 1, characterized in that: The total power supply power in step 4 is calculated as: The proportion of power supplied by the power grid is calculated as: ; The power supply ratio of the energy storage system is calculated as: ; in: Indicates the photovoltaic module at time The power generation capacity, unit: kW; Indicates the power grid at time Power supply capacity, unit: kW; Indicates the proportion of power supplied by the power grid; Indicates the total power supply, unit: kW.

7. The method for optimizing the operation of a photovoltaic charging station energy storage system according to claim 6, characterized in that: The proportion of power supply from the power grid in step 4 Dynamic adjustment: The proportion of power supplied by the energy storage system in step 4 The dynamic adjustment is: in: Indicates at time When , the proportion of photovoltaic battery power supply to the total power supply; In step 4, the electric vehicle charging power is calculated as: in: Indicates that electric vehicles are Charging power, unit: kW.

8. The method for optimizing the operation of a photovoltaic charging station energy storage system according to claim 1, characterized in that: The minimum calculation of grid side load variance in step 5 is: in, Represents the time series variance of the power supplied by the power grid; The minimum operation and maintenance cost of the energy storage system is calculated as: in: Indicates time The unit maintenance cost of the energy storage system is Indicates time The energy storage system discharge power at Indicates time The energy storage system charging power at The minimum charging cost is calculated as: in: Indicates time The grid electricity price at that time, Indicates time The grid power supply power at that time.

9. The method for optimizing the operation of a photovoltaic charging station energy storage system according to claim 8, characterized in that: The constraints in step 5 include: Energy storage system power limit: in, is the maximum discharge power of the energy storage system, is the maximum charging power of the energy storage system; State of Charge (SOC) Limits: ; in, and are the minimum and maximum states of charge of the energy storage system, respectively; Power supply limit on the grid side: in, is the maximum power supply of the power grid Limits on the fluctuation of photovoltaic power generation: in, is the maximum power generation capacity of the photovoltaic system.

10. The method for optimizing the operation of a photovoltaic charging station energy storage system according to claim 9, characterized in that: The real-time scheduling model in step 6 is: in: For time The grid electricity price at that time; For time The energy storage system discharge cost at 10 ... The adjustment calculation for insufficient discharge capacity during the peak electricity price period in step 6 is: If the energy storage system's discharge capacity is insufficient during peak electricity price periods, the system will adjust the charging strategy during off-peak periods to increase the amount of energy storage system charged; Increase the amount of charging during off-peak hours: in: This is the insufficient discharge capacity of the energy storage system during peak electricity price periods; Charging power adjustment during the off-peak period: in: It is the charging power during the adjusted off-peak period.

Images