A hybrid energy storage photovoltaic power generation control method and system

Abstract

The present disclosure relates to a hybrid energy storage photovoltaic power generation control method and system, and relates to the field of energy storage technology; based on the capacity change data of the previous power generation cycle, the energy utilization rate is determined, and based on the energy utilization rate, multiple configurable capacities are determined, and combined with a preset particle swarm algorithm, the target photovoltaic power generation unit capacity and the target energy storage unit capacity are determined from the multiple configurable capacities, and then the photovoltaic power generation unit and the energy storage unit of the next power generation cycle are configured according to the target photovoltaic power generation unit capacity and the target energy storage unit capacity. The capacity configuration matches the actual power generation situation, and the particle swarm algorithm is used to achieve the solution of the optimal capacity, thereby improving the efficiency and accuracy of the capacity solution. Therefore, this technical solution can achieve efficient and accurate capacity configuration of photovoltaic power generation units and energy storage units, thereby improving the reliability, stability and economy of hybrid energy storage photovoltaic power generation.

Description

Technical Field

[0001] The present disclosure relates to the field of energy storage technology, and in particular to a hybrid energy storage photovoltaic power generation control method and system. Background Art

[0002] With the development of photovoltaic power generation technology, the application of photovoltaic power generation has also developed. At present, photovoltaic power generation technology can be used in energy storage technology, such as: photovoltaic storage and charging integrated charging station, which is equipped with photovoltaic power generation unit, energy storage unit and charging pile. Among them, photovoltaic power generation unit and energy storage unit can be used as energy storage equipment to realize energy storage of charging station, and then provide electric energy for charging pile, so as to realize reliable and stable operation of photovoltaic storage and charging integrated charging station.

[0003] In the related technologies, the configuration optimization of energy storage systems is mainly considered from the economic aspect, without involving the configuration optimization of capacity. However, excessive configuration of energy storage and photovoltaic capacity for charging stations will cause a waste of social resources. Conservative configuration of energy storage and photovoltaic capacity will only deviate from the actual application performance of building integrated photovoltaic storage and charging stations, and will not be able to achieve the goal of peak shaving and valley filling for the power grid, and may even produce new impacts on the power grid. Therefore, the related technologies lack an effective capacity configuration solution, making it difficult to ensure the economy, reliability and stability of hybrid energy storage photovoltaic power generation. Summary of the invention

[0004] The purpose of the present disclosure is to provide a hybrid energy storage photovoltaic power generation control method and system, which can realize efficient and accurate capacity configuration of photovoltaic power generation units and energy storage units, thereby improving the reliability, stability and economy of hybrid energy storage photovoltaic power generation.

[0005] In order to achieve the above-mentioned purpose, in a first aspect, the present disclosure provides a hybrid energy storage photovoltaic power generation control method, comprising: obtaining capacity change data corresponding to a previous power generation cycle, the capacity change data including photovoltaic power generation unit capacity and energy storage unit capacity corresponding to multiple time points, the photovoltaic power generation unit and the energy storage unit are respectively used to provide electric energy to the charging pile within the power generation cycle; determining the energy utilization rate corresponding to the previous power generation cycle according to the capacity change data; determining multiple configurable capacities according to the energy utilization rate corresponding to the previous power generation cycle, the photovoltaic power generation unit capacity corresponding to the multiple time points, the energy storage unit capacity and a first preset energy utilization rate; determining a target photovoltaic power generation unit capacity and a target energy storage unit capacity from the multiple configurable capacities according to a preset particle swarm algorithm; and configuring the capacity of the photovoltaic power generation unit and the energy storage unit for the next power generation cycle according to the target photovoltaic power generation unit capacity and the target energy storage unit capacity.

[0006] Optionally, determining the energy utilization rate corresponding to the previous power generation cycle according to the capacity change data includes: determining a first capacity consumption value according to the photovoltaic power generation unit capacities corresponding to the multiple time points; determining a second capacity consumption value according to the energy storage unit capacities corresponding to the multiple time points; determining a first energy utilization rate according to the first capacity consumption value and the maximum capacity of the photovoltaic power generation unit capacities corresponding to the multiple time points; determining a second energy utilization rate according to the second capacity consumption value and the maximum capacity of the energy storage unit capacities corresponding to the multiple time points; and determining a final energy utilization rate according to the first energy utilization rate and the second energy utilization rate.

[0007] Optionally, determining the final energy utilization rate based on the first energy utilization rate and the second energy utilization rate includes: determining a first weight and a second weight based on the maximum capacity of the photovoltaic power generation unit capacities corresponding to the multiple time points and the maximum capacity of the energy storage unit capacities corresponding to the multiple time points, the first weight being the weight corresponding to the first energy utilization rate, and the second weight being the weight corresponding to the second energy utilization rate, wherein if the maximum capacity of the photovoltaic power generation unit capacities corresponding to the multiple time points is greater than the maximum capacity of the energy storage unit capacities corresponding to the multiple time points, the first weight is less than the second weight, and if the maximum capacity of the photovoltaic power generation unit capacities corresponding to the multiple time points is less than the maximum capacity of the energy storage unit capacities corresponding to the multiple time points, the first weight is greater than the second weight; determining the final energy utilization rate based on the first weight, the second weight, the first energy utilization rate, and the second energy utilization rate.

[0008] Optionally, the multiple configurable capacities are determined based on the energy utilization rate corresponding to the previous power generation cycle, the photovoltaic power generation unit capacity corresponding to the multiple time points, the energy storage unit capacity and the first preset energy utilization rate, including: if the energy utilization rate corresponding to the previous power generation cycle is greater than or equal to the first preset energy utilization rate, randomly sampling the photovoltaic power generation unit capacity and the energy storage unit capacity corresponding to the multiple time points to obtain multiple randomly sampled capacities; if the energy utilization rate corresponding to the previous power generation cycle is less than the first preset energy utilization rate, sampling the photovoltaic power generation unit capacity and the energy storage unit capacity corresponding to the multiple time points according to preset time point conditions to obtain multiple conditionally sampled capacities, wherein the preset time point conditions are used to limit the conditions that need to be met at the time points corresponding to the sampled capacities; based on the multiple capacities, the multiple configurable capacities are determined.

[0009] Optionally, the hybrid energy storage photovoltaic power generation control method also includes: obtaining expected investment costs and expected operating income; determining an economic impact value based on the expected investment costs and the expected operating income; obtaining a preset corresponding relationship, wherein the preset corresponding relationship is used to characterize the corresponding relationship between the economic impact value and the capacity interval; correspondingly, determining the multiple configurable capacities based on the multiple capacities includes: determining a target capacity interval based on the economic impact value and the preset corresponding relationship; comparing the multiple capacities with the target capacity interval to obtain a comparison result; determining to expand the multiple capacities based on the comparison result; expanding the multiple capacities based on the target capacity interval to obtain multiple expanded capacities; determining the multiple expanded capacities as the multiple configurable capacities.

[0010] Optionally, the method of determining the target photovoltaic power generation unit capacity and the target energy storage unit capacity from the multiple configurable capacities according to a preset particle swarm algorithm includes: obtaining a preset objective function, which is used to characterize the correspondence between the capacity, the photovoltaic unit loss rate and the charging pile loss rate; obtaining preset constraints, which include photovoltaic unit loss rate constraints and charging pile loss rate constraints; determining the target photovoltaic power generation unit capacity and the target energy storage unit capacity from the multiple configurable capacities according to the preset particle swarm algorithm, the preset objective function and the preset constraints; wherein the preset objective function and the preset constraints are used by the preset particle swarm algorithm to evaluate the fitness of particles, and the multiple configurable capacities are particles in the preset particle swarm algorithm.

[0011] Optionally, the hybrid energy storage photovoltaic power generation control method also includes: obtaining a preset simulation system, the preset simulation system is used to simulate the consumption of photovoltaic power generation unit capacity configuration and energy storage unit capacity; inputting the target photovoltaic power generation unit capacity and the target energy storage unit capacity into the preset simulation system to obtain simulated capacity consumption data, the simulated capacity consumption data includes the photovoltaic power generation unit capacity and the energy storage unit capacity corresponding to multiple virtual time points respectively; according to the simulated capacity consumption data, determining the predicted energy utilization rate corresponding to the next power generation cycle; correspondingly, according to the target photovoltaic power generation unit capacity and the target energy storage unit capacity, the capacity of the photovoltaic power generation unit and the energy storage unit for the next power generation cycle is configured, including: comparing the predicted energy utilization rate with the energy utilization rate corresponding to the previous power generation cycle to obtain a comparison result; according to the comparison result, the target photovoltaic power generation unit capacity and the target energy storage unit capacity, the capacity of the photovoltaic power generation unit and the energy storage unit for the next power generation cycle is configured.

[0012] Optionally, the capacity of the photovoltaic power generation unit and the energy storage unit for the next power generation cycle is configured according to the comparison result, the target photovoltaic power generation unit capacity and the target energy storage unit capacity, including: if the predicted energy utilization rate is greater than or equal to the energy utilization rate corresponding to the previous power generation cycle, the initial capacity of the photovoltaic power generation unit for the next power generation cycle is configured as the target photovoltaic power generation unit capacity, and the initial capacity of the energy storage unit for the next power generation cycle is configured as the target energy storage unit capacity; if the predicted energy utilization rate is less than the energy utilization rate corresponding to the previous power generation cycle, the target capacity is determined according to the target photovoltaic power generation unit capacity and the target energy storage unit capacity, and the initial capacity of the photovoltaic power generation unit and the initial capacity of the energy storage unit for the next power generation cycle are both configured as the target capacity.

[0013] Optionally, the hybrid energy storage photovoltaic power generation control method also includes: obtaining capacity change data corresponding to at least two historical power generation cycles; determining the energy utilization rates corresponding to the at least two historical power generation cycles according to the capacity change data corresponding to the at least two historical power generation cycles; determining a capacity configuration evaluation result according to the energy utilization rates corresponding to the at least two historical power generation cycles, the capacity configuration evaluation result is used to characterize whether the capacity configuration is reasonable; if the capacity configuration evaluation result characterizes that the capacity configuration is reasonable, and the maximum energy utilization rate among the energy utilization rates corresponding to the at least two historical power generation cycles is less than a second preset energy utilization rate, generating optimization prompt information and feeding it back, the optimization prompt information is used to indicate optimization of at least one of the photovoltaic power generation unit, the energy storage unit and the charging pile.

[0014] In a second aspect, the present disclosure provides a hybrid energy storage photovoltaic power generation control system, comprising: a charging pile; a photovoltaic power generation unit, connected to the charging pile, for providing electrical energy to the charging pile according to the configured capacity; an energy storage unit, respectively connected to the charging pile and the photovoltaic power generation unit, for providing electrical energy to the charging pile according to the configured capacity; a control unit, respectively connected to the charging pile, the photovoltaic power generation unit and the energy storage unit, for implementing the hybrid energy storage photovoltaic power generation control method as described in the first aspect.

[0015] Through the above technical solution, the energy utilization rate is determined based on the capacity change data of the previous power generation cycle, and based on the energy utilization rate, multiple configurable capacities are determined, and then the target photovoltaic power generation unit capacity and the target energy storage unit capacity are determined from the multiple configurable capacities in combination with the preset particle swarm algorithm, and then the photovoltaic power generation unit and the energy storage unit of the next power generation cycle are configured according to the target photovoltaic power generation unit capacity and the target energy storage unit capacity. On the one hand, the actual capacity data of the previous power generation cycle is used to determine the energy utilization rate, and then the configurable capacity of the next power generation cycle is determined, so that the capacity configuration is more in line with the actual power generation situation. On the other hand, the particle swarm algorithm is used to solve the optimal capacity, thereby improving the efficiency and accuracy of the capacity solution. Therefore, this technical solution can realize efficient and accurate capacity configuration of photovoltaic power generation units and energy storage units, thereby improving the reliability, stability and economy of hybrid energy storage photovoltaic power generation.

[0016] Other features and advantages of the present disclosure will be described in detail in the following detailed description. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] The accompanying drawings are used to provide a further understanding of the present disclosure and constitute a part of the specification. Together with the following specific embodiments, they are used to explain the present disclosure but do not constitute a limitation of the present disclosure. In the accompanying drawings:

[0018] Figure 1 It is a schematic structural diagram of a photovoltaic storage and charging integrated power station according to an exemplary embodiment.

[0019] Figure 2 is an exemplary diagram showing the flow of electric energy according to an exemplary embodiment.

[0020] Figure 3 The present invention is a flow chart of a hybrid energy storage photovoltaic power generation control method according to an exemplary embodiment.

[0021] Figure 4 The figure is a schematic diagram showing an application of a particle algorithm according to an exemplary embodiment.

[0022] Figure 5 It is a block diagram of a hybrid energy storage photovoltaic power generation control device according to an exemplary embodiment.

[0023] Figure 6 It is a block diagram of an electronic device according to an exemplary embodiment. DETAILED DESCRIPTION

[0024] The specific implementation of the present disclosure is described in detail below in conjunction with the accompanying drawings. It should be understood that the specific implementation described herein is only used to illustrate and explain the present disclosure, and is not used to limit the present disclosure.

[0025] In order to facilitate understanding of the technical solutions of the embodiments of the present disclosure, some technologies involved are first introduced below.

[0026] The embodiments of the present disclosure involve photovoltaic power generation, which is mainly divided into the following two types: distributed photovoltaic power generation and centralized photovoltaic power generation. The former is mainly a photovoltaic power generation system below the megawatt level installed on various roofs. The latter is a large ground power station with a capacity of more than tens of megawatts installed on a wide area. In the integrated photovoltaic storage and charging electric vehicle charging facilities, distributed photovoltaic power generation is mainly used.

[0027] Regarding the research on photovoltaic charging, there are currently many studies on photovoltaic power generation subsidies and economic benefits. However, its combination with the construction and operation of charging facilities will involve new issues such as optimal configuration and coordinated operation, which have been less studied.

[0028] The embodiments of the present disclosure also involve energy storage technology, which is an effective way to improve energy utilization efficiency and can solve the contradiction between energy supply and demand in time and space. Current research on various energy storage technologies mainly focuses on two aspects: application planning and economic analysis.

[0029] The disclosed embodiments also involve configuration optimization of integrated photovoltaic, storage and charging charging stations. In the study of the business model of integrated photovoltaic, storage and charging charging stations under energy configuration, existing research mainly focuses on two aspects: First, starting from the integration method of the charging station, a reasonable topology is selected, including the electrical connection method, and the integration from photovoltaic power generation to the energy storage and charging system of the charging station is studied. Taking into account the applicability of photovoltaic power generation to different types of charging infrastructure, the matching characteristics of different charging facilities and photovoltaic power generation are analyzed to realize the configuration of the system. Second, by establishing a mathematical model that meets the optimization goal from the renewable energy power generation system to the energy storage and charging system, the configuration of the integrated photovoltaic, storage and charging charging station is optimized, and it is solved according to a specific algorithm to ensure the reasonable operation of the charging piles, distributed power supplies, energy storage and other equipment in the station, which is also the focus of future research.

[0030] At present, there are two main aspects of research on energy storage system configuration optimization: one is to determine the surplus based on the charging and discharging efficiency and empirical parameters of the energy storage system; the other is to determine the capacity configuration based on peak and valley electricity prices and with the economic operation of the charging station as the main goal.

[0031] However, there are currently more studies on the economic benefits of integrated photovoltaic, storage and charging, but fewer studies on the capacity configuration of photovoltaic units and energy storage units in actual projects.

[0032] The photovoltaic storage and charging integrated charging station is mainly composed of charging piles, photovoltaic power generation units, energy storage units, and corresponding control units. The structural design of the photovoltaic storage and charging integrated power station needs to consider the convenience of power station load charging, the maximum output power of the photovoltaic power station, the battery life of the energy storage power station, the complementarity of photovoltaic storage energy, the complementarity of photovoltaic storage system and grid energy, and the convenience, speed, efficiency, safety and stability of system control.

[0033] The configuration of photovoltaic capacity and energy storage capacity in the photovoltaic storage and charging integrated charging station needs to be determined through reasonable planning. However, there is currently little research on the configuration optimization of photovoltaic storage capacity in photovoltaic storage and charging integrated charging stations. How to fully tap the energy utilization rate of photovoltaic storage and charging integrated charging stations is an issue that needs to be studied and resolved. Excessive configuration of energy storage and photovoltaic capacity in charging stations will only cause a waste of social resources. Conservative configuration of energy storage and photovoltaic capacity will deviate from the actual application performance of building photovoltaic storage and charging integrated charging stations, fail to achieve the goal of peak shaving and valley filling for the power grid, and even produce new impacts on the power grid.

[0034] It can be seen that only by rationally configuring photovoltaics and energy storage at charging stations can higher social and economic benefits be achieved.

[0035] Based on this, an embodiment of the present disclosure provides a technical solution, which is based on an integrated photovoltaic storage and charging power station to solve the optimal photovoltaic power generation unit capacity and energy storage capacity, and improve the reliability, stability and economy of the integrated photovoltaic storage and charging power station.

[0036] Figure 1 is a schematic diagram of a photovoltaic storage and charging integrated power station according to an exemplary embodiment. Figure 1 As shown, the system includes: a charging pile, a photovoltaic power generation unit, an energy storage unit and a control unit.

[0037] Among them, the charging pile can be used to charge electric vehicles. For electric vehicles with charging needs, they can be connected to the charging pile through corresponding charging devices to achieve charging.

[0038] The photovoltaic power generation unit can be connected to the charging pile to provide power to the charging pile according to the configured capacity. The configured capacity can be understood as the power capacity required by the configured charging pile. Therefore, through capacity configuration, the photovoltaic power generation unit can perform more reasonable photovoltaic power generation.

[0039] The energy storage unit is connected to the charging pile and the photovoltaic power generation unit respectively, and is used to provide electric energy to the charging pile according to the configured capacity. The configured capacity can be understood as the electric capacity required by the configured charging pile. Therefore, through capacity configuration, the energy storage unit can perform more reasonable energy storage.

[0040] The photovoltaic power generation unit and the energy storage unit can also be connected to the power grid. The power grid can provide power to the entire charging pile. Since the photovoltaic power generation unit itself has the function of generating electricity, the power provided by the power grid can be mainly used by the energy storage unit. For the photovoltaic power generation unit, it can reversely provide power to the power grid and also provide power to the energy storage unit.

[0041] Figure 2 is an example diagram showing an electric energy flow according to an exemplary embodiment. Figure 2 As shown, there can be electric energy flow between the photovoltaic power generation unit and the energy storage unit, mainly from the photovoltaic power generation unit to the energy storage unit. There can also be electric energy flow between the photovoltaic power generation unit and the power grid, mainly from the photovoltaic power generation unit to the power grid. There can also be electric energy flow between the power grid and the energy storage unit, mainly from the power grid to the energy storage unit. In addition, there is electric energy flow between the photovoltaic power generation unit and the energy storage unit and the charging pile, respectively, both of which flow to the charging pile. Finally, there is electric energy flow between the charging pile and the electric vehicle, from the charging pile to the electric vehicle.

[0042] It can be seen that the photovoltaic power generation unit has many functions in the integrated charging station and can improve various required electric energy. Therefore, the capacity configuration of the photovoltaic power generation unit and the energy storage unit can effectively improve the utilization rate of the photovoltaic power generation unit.

[0043] In the disclosed embodiment, the energy flowing from the photovoltaic power generation unit and the energy storage unit to the charging pile is mainly configured. On the one hand, the photovoltaic power generation unit can effectively distribute the photovoltaic power generation energy; on the other hand, the energy waste of the energy storage unit can be reduced.

[0044] Regarding the control unit, it is connected to the charging pile, photovoltaic power generation unit and energy storage unit respectively, and can be used to realize hybrid energy storage photovoltaic power generation control, and specifically can realize power generation control based on capacity configuration.

[0045] In addition, the integrated photovoltaic storage and charging power station can be understood as a hybrid energy storage photovoltaic power generation system.

[0046] Figure 3 The present invention is a flow chart of a hybrid energy storage photovoltaic power generation control method according to an exemplary embodiment. The method can be applied to the above-mentioned control unit. The method includes the following steps:

[0047] Step S31, obtaining the capacity change data corresponding to the previous power generation cycle, the capacity change data including the photovoltaic power generation unit capacity and the energy storage unit capacity corresponding to multiple time points, the photovoltaic power generation unit and the energy storage unit are used to provide power to the charging pile during the power generation cycle.

[0048] Step S32, determining the energy utilization rate corresponding to the previous power generation cycle according to the capacity change data.

[0049] Step S33, determining a plurality of configurable capacities according to the energy utilization rate corresponding to the previous power generation cycle, the photovoltaic power generation unit capacity corresponding to a plurality of time points, the energy storage unit capacity and the first preset energy utilization rate.

[0050] Step S34, according to a preset particle swarm algorithm, a target photovoltaic power generation unit capacity and a target energy storage unit capacity are determined from a plurality of configurable capacities.

[0051] Step S35, according to the target photovoltaic power generation unit capacity and the target energy storage unit capacity, the photovoltaic power generation unit and the energy storage unit are configured with respect to the capacity of the next power generation cycle.

[0052] The power generation cycle can be understood as the charging cycle of the charging pile. For example, 24 hours a day is a power generation cycle. For the photovoltaic power generation unit and the energy storage unit, the power generation cycle can be understood as the cycle of providing power to the charging pile.

[0053] In step S31, the multiple time points may be understood as multiple time points in the previous power generation cycle, and the time intervals between the multiple time points may be the same, for example: one hour.

[0054] It is understandable that in each power generation cycle, the capacities of the photovoltaic power generation unit and the energy storage unit may change at any time, so the capacity data of these changes can be obtained.

[0055] In some embodiments, the photovoltaic power generation unit and the energy storage unit each have a capacity monitoring function, and the corresponding capacity data can be obtained at any time.

[0056] In some embodiments, since the capacity configuration is performed using the capacity change data of the previous power generation cycle, the capacity configuration can be performed before the end of the previous power generation cycle and before the start of the next power generation cycle.

[0057] In step S32, the energy utilization rate corresponding to the previous power generation cycle is determined based on the capacity change data.

[0058] As an optional implementation, step S32 includes: determining a first capacity consumption value according to the photovoltaic power generation unit capacities corresponding to multiple time points; determining a second capacity consumption value according to the energy storage unit capacities corresponding to multiple time points; determining a first energy utilization rate according to the first capacity consumption value and the maximum capacity of the photovoltaic power generation unit capacities corresponding to multiple time points; determining a second energy utilization rate according to the second capacity consumption value and the maximum capacity of the energy storage unit capacities corresponding to multiple time points; and determining a final energy utilization rate according to the first energy utilization rate and the second energy utilization rate.

[0059] In some embodiments, the capacity consumption value may be the difference between the maximum capacity and the minimum capacity; or, it may be the difference between the capacity at the first time point and the capacity at the last time point; or, the capacity change law may be statistically analyzed, two time points may be determined according to the capacity change law, and the capacity consumption value may be determined according to the capacity values ​​at the two time points. Therefore, both the first capacity consumption value and the second capacity consumption value may be calculated according to these feasible implementation methods.

[0060] In some embodiments, energy utilization rate=(capacity consumption value / maximum capacity)×100%.

[0061] In some embodiments, determining the final energy utilization rate based on the first energy utilization rate and the second energy utilization rate may include: determining a first weight and a second weight based on the maximum capacity of the photovoltaic power generation unit capacity corresponding to multiple time points and the maximum capacity of the energy storage unit capacity corresponding to multiple time points, the first weight being the weight corresponding to the first energy utilization rate, and the second weight being the weight corresponding to the second energy utilization rate, wherein if the maximum capacity of the photovoltaic power generation unit capacity corresponding to multiple time points is greater than the maximum capacity of the energy storage unit capacity corresponding to multiple time points, the first weight is less than the second weight, and if the maximum capacity of the photovoltaic power generation unit capacity corresponding to multiple time points is less than the maximum capacity of the energy storage unit capacity corresponding to multiple time points, the first weight is greater than the second weight; determining the final energy utilization rate based on the first weight, the second weight, the first energy utilization rate, and the second energy utilization rate.

[0062] In this embodiment, the two energy utilization rates are integrated using weight values. Among them, if the maximum capacity of the photovoltaic power generation unit capacity corresponding to multiple time points is greater than the maximum capacity of the energy storage unit capacity corresponding to multiple time points, it means that the power supply capacity of photovoltaic power generation is greater than the energy storage unit, and the weight of the photovoltaic unit energy utilization rate can be made greater than the weight of the energy storage unit energy utilization rate. If the maximum capacity of the photovoltaic power generation unit capacity corresponding to multiple time points is less than the maximum capacity of the energy storage unit capacity corresponding to multiple time points, it means that the power supply capacity of photovoltaic power generation is less than the energy storage unit, and the weight of the photovoltaic unit energy utilization rate can be made less than the weight of the energy storage unit energy utilization rate.

[0063] In some embodiments, if the maximum capacity of the photovoltaic power generation unit capacities corresponding to multiple time points is equal to the maximum capacity of the energy storage unit capacities corresponding to multiple time points, the first weight can be equal to the second weight, for example, both are 0.5.

[0064] In some embodiments, the sum of the first weight and the second weight is 1, and the first weight and the second weight can be determined by making a reasonable allocation according to the size relationship. For example, the greater the difference between the two maximum capacities, the greater the difference between the first weight and the second weight.

[0065] Furthermore, the final energy utilization rate may be: first weight×first energy utilization rate+second weight×second energy utilization rate.

[0066] In step S33, a plurality of configurable capacities are determined according to the energy utilization rate corresponding to the previous power generation cycle, the photovoltaic power generation unit capacity corresponding to a plurality of time points, the energy storage unit capacity and the first preset energy utilization rate.

[0067] In some embodiments, a plurality of configurable capacities may be determined from capacity change data corresponding to a previous power generation cycle.

[0068] As an optional implementation, step S33 includes: if the energy utilization rate corresponding to the previous power generation cycle is greater than or equal to the first preset energy utilization rate, randomly sampling the photovoltaic power generation unit capacity and the energy storage unit capacity corresponding to multiple time points respectively, to obtain multiple randomly sampled capacities; if the energy utilization rate corresponding to the previous power generation cycle is less than the first preset energy utilization rate, sampling the photovoltaic power generation unit capacity and the energy storage unit capacity corresponding to multiple time points respectively according to preset time point conditions, to obtain multiple conditionally sampled capacities, wherein the preset time point conditions are used to limit the conditions that must be met at the time points corresponding to the sampled capacities; based on the multiple capacities, determining multiple configurable capacities.

[0069] In this embodiment, the first preset energy utilization rate can be a preset utilization rate that can ensure economy. The first preset energy utilization rate can be configured according to the scale of the charging station. The larger the scale, the higher the first preset energy utilization rate. The scale configuration of the charging station can be determined by the number of photovoltaic power generation units and the number of charging piles.

[0070] Therefore, if the energy utilization rate corresponding to the previous power generation cycle is greater than or equal to the first preset energy utilization rate, it means that the current capacity configuration can meet the economical energy utilization requirements, and random sampling can be directly performed from the photovoltaic power generation unit capacity and energy storage unit capacity corresponding to multiple time points to obtain multiple randomly sampled capacities.

[0071] If the energy utilization rate corresponding to the previous power generation cycle is less than the first preset energy utilization rate, it means that the current capacity configuration cannot meet the economic energy utilization requirement. Sampling can be performed according to the preset time point conditions, that is, conditional sampling can be performed to obtain multiple capacities.

[0072] In some embodiments, the conditions that the time point corresponding to the sampled capacity needs to meet may be: being in the early or late stage of the entire power generation cycle, or being at a critical point of capacity change, such as: a jump point where the capacity changes significantly.

[0073] Further, based on the multiple capacities, multiple configurable capacities may be determined.

[0074] In some embodiments, multiple capacities may be directly determined as configurable capacities.

[0075] In other embodiments, the capacity may be expanded and then the configurable capacity may be determined.

[0076] Therefore, as an optional implementation, the method further includes: obtaining expected investment costs and expected operating income; and determining the economic impact value based on the expected investment costs and expected operating income.

[0077] And also includes: obtaining a preset corresponding relationship, the preset corresponding relationship is used to characterize the corresponding relationship between the economic impact value and the capacity interval.

[0078] Correspondingly, determining multiple configurable capacities based on multiple capacities may include: determining a target capacity interval based on an economic impact value and a preset corresponding relationship; comparing the multiple capacities with the target capacity interval to obtain a comparison result; determining to expand the multiple capacities based on the comparison result; expanding the multiple capacities based on the target capacity interval to obtain multiple expanded capacities; (determining the expanded capacity value from the target capacity interval) determining the multiple expanded capacities as multiple configurable capacities.

[0079] In some embodiments, the difference between the expected investment cost and the expected operating income is determined and converted into an economic impact value. Generally speaking, the expected operating income is greater than the expected investment cost, so the difference can be the expected operating income minus the expected investment cost.

[0080] For example, the economic impact value can be a value between 1 and 5. The larger the value, the higher the economic impact and the higher the economic requirements. After determining the difference between the expected investment cost and the expected operating income, the appropriate economic impact value is determined from 1 to 5 according to the proportion of the difference to the expected operating income. For example, the higher the proportion, the greater the economic impact value.

[0081] In some embodiments, the preset corresponding relationship can be determined based on a large amount of prior data statistics. For example, an economic capacity mathematical model is established to count the actual configured capacity values ​​under different economic impact values, and determine the reasonable capacity interval corresponding to each economic impact value, so that the capacity within the capacity interval can basically adapt to the economic requirements required by the economic impact value.

[0082] In some embodiments, based on the current economic impact value and a preset correspondence, a target capacity interval that matches the current economic impact value may be determined.

[0083] In some embodiments, multiple capacities are compared with the target capacity interval, and the capacities in the target capacity interval that are the same as the multiple capacities are determined. If the frequency of the larger capacity value is low among the same capacities, it is determined that expansion is required. If the frequency of the larger capacity value is high among the same capacities, it is determined that expansion is not required.

[0084] In some embodiments, an expanded capacity value is determined from the target capacity interval, and the expanded capacity value and the multiple capacities are integrated into multiple expanded capacities. Furthermore, the multiple expanded capacities are determined as multiple configurable capacities.

[0085] In some embodiments, a high capacity value is preferentially selected from the target capacity interval, then a low capacity value is selected, and finally a middle capacity value is selected.

[0086] In step S34, according to a preset particle swarm algorithm, a target photovoltaic power generation unit capacity and a target energy storage unit capacity are determined from a plurality of configurable capacities.

[0087] The particle swarm algorithm can be understood as an optimal solution algorithm, which regards multiple candidate solutions as particles and then performs particle search to find the optimal solution. For a detailed introduction to the particle swarm algorithm, please refer to the mature technology in this field.

[0088] Based on the particle swarm algorithm, if you want to apply it, you need to define the parameters. Based on the parameter definition, you can use the particle swarm algorithm to achieve the optimal solution.

[0089] Therefore, as an optional implementation, step S34 includes: obtaining a preset objective function, which is used to characterize the correspondence between capacity, photovoltaic unit loss rate and charging pile loss rate; obtaining preset constraints, which include photovoltaic unit loss rate constraints and charging pile loss rate constraints; determining the target photovoltaic power generation unit capacity and the target energy storage unit capacity from multiple configurable capacities according to a preset particle swarm algorithm, a preset objective function and a preset constraint; wherein the preset objective function and the preset constraint are used by the preset particle swarm algorithm to evaluate the fitness of particles, and the multiple configurable capacities are particles in the preset particle swarm algorithm.

[0090] In this implementation, the particle fitness can be regarded as a condition for the particle to stop searching. If the particle fitness reaches the corresponding condition, it is regarded as finding the optimal solution. Multiple configurable capacities are regarded as particles (candidate solutions), so it is necessary to calculate the fitness of the particles based on the preset objective function and the preset constraints, so as to find the optimal solution from multiple candidate solutions.

[0091] Regarding the preset objective function, the corresponding relationship between the capacity, the photovoltaic unit loss rate and the charging pile loss rate can be characterized. According to the preset objective function, the photovoltaic unit loss rate and the charging pile loss rate of the candidate solution can be determined. Regarding the preset constraints, including the photovoltaic unit loss rate constraint and the charging pile loss rate constraint, according to the constraint, it can be determined whether the photovoltaic unit loss rate and the charging pile loss rate of the candidate solution meet the constraint.

[0092] In some embodiments, the preset constraints may be reasonably configured according to the requirements of capacity configuration.

[0093] In some embodiments, the preset objective function can be determined by counting a large amount of prior data, for example: counting the capacity data of different power generation cycles, the actual photovoltaic unit loss rate and the charging pile loss rate, and constructing them into a corresponding mathematical model to determine the objective function.

[0094] In some embodiments, the particle swarm algorithm may further add more definitions and constraints, which are not limited here.

[0095] Furthermore, in step S35, the capacity of the photovoltaic power generation unit and the energy storage unit is configured for the next power generation cycle according to the target photovoltaic power generation unit capacity and the target energy storage unit capacity.

[0096] Before executing step S35, simulation verification may be performed to determine the executable capacity configuration.

[0097] Therefore, the method may also include: obtaining a preset simulation system, the preset simulation system is used to simulate the consumption of photovoltaic power generation unit capacity configuration and energy storage unit capacity; inputting the target photovoltaic power generation unit capacity and the target energy storage unit capacity into the preset simulation system to obtain simulated capacity consumption data, the simulated capacity consumption data includes the photovoltaic power generation unit capacity and the energy storage unit capacity corresponding to multiple virtual time points respectively; according to the simulated capacity consumption data, determining the predicted energy utilization rate corresponding to the next power generation cycle.

[0098] Correspondingly, step S35 may include: comparing the predicted energy utilization rate with the energy utilization rate corresponding to the previous power generation cycle to obtain a comparison result; and configuring the capacity of the photovoltaic power generation unit and the energy storage unit for the next power generation cycle based on the comparison result, the target photovoltaic power generation unit capacity and the target energy storage unit capacity.

[0099] In this embodiment, the construction method of the preset simulation system can refer to the mature power grid simulation system construction method in the field, which can construct a virtual model of the charging station. The virtual model can be simulated based on the corresponding data to simulate the actual operation of the charging station.

[0100] Therefore, the target photovoltaic power generation unit capacity and the target energy storage unit capacity are input into the simulation system as configuration parameters to obtain the simulated capacity consumption data. The simulated capacity consumption data includes the photovoltaic power generation unit capacity and the energy storage unit capacity corresponding to multiple virtual time points. According to the aforementioned method for determining the energy utilization rate, the predicted energy utilization rate can be determined.

[0101] Furthermore, the predicted energy utilization rate is compared with the energy utilization rate corresponding to the previous power generation cycle, and the capacity configuration for the next power generation cycle can be performed based on the comparison result.

[0102] Figure 4 is a schematic diagram of an application of a particle algorithm according to an exemplary embodiment. Figure 4 As shown in the figure, regarding the application of particle algorithms, it is necessary to propose objective functions and constraints in the early stage. Based on the objective functions and constraints, the particle swarm algorithm can be used to solve the problem. After the solution is found, simulation verification is performed, so that the solution can be effectively applied according to the simulation verification results.

[0103] In some embodiments, the capacity of the photovoltaic power generation unit and the energy storage unit is configured for the next power generation cycle based on the comparison result, the target photovoltaic power generation unit capacity, and the target energy storage unit capacity, which may include: if the predicted energy utilization rate is greater than or equal to the energy utilization rate corresponding to the previous power generation cycle, the initial capacity of the photovoltaic power generation unit for the next power generation cycle is configured as the target photovoltaic power generation unit capacity, and the initial capacity of the energy storage unit for the next power generation cycle is configured as the target energy storage unit capacity; if the predicted energy utilization rate is less than the energy utilization rate corresponding to the previous power generation cycle, the target capacity is determined based on the target photovoltaic power generation unit capacity and the target energy storage unit capacity, and the initial capacity of the photovoltaic power generation unit and the initial capacity of the energy storage unit for the next power generation cycle are both configured as the target capacity.

[0104] In this embodiment, if the predicted energy utilization rate remains unchanged or increases compared to the energy utilization rate corresponding to the previous power generation cycle, the initial capacity of the photovoltaic power generation unit in the next power generation cycle can be directly configured as the target photovoltaic power generation unit capacity, and the initial capacity of the energy storage unit in the next power generation cycle can be configured as the target energy storage unit capacity.

[0105] If the predicted energy utilization rate is lower than the energy utilization rate corresponding to the previous power generation cycle, the target capacity is determined based on the target photovoltaic power generation unit capacity and the target energy storage unit capacity, and the initial capacity of the photovoltaic power generation unit and the initial capacity of the energy storage unit in one power generation cycle are configured as the target capacity.

[0106] In some embodiments, in addition to configuring the initial capacity, the maximum allowed capacity can also be configured. Generally speaking, the initial capacity is the maximum allowed capacity. In some cases, the initial capacity may not be the maximum allowed capacity. It can be flexibly configured according to actual conditions.

[0107] In some embodiments, the target capacity may be an average value of the target photovoltaic power generation unit capacity and the target energy storage unit capacity, or a minimum value thereof.

[0108] Through capacity configuration, hybrid energy storage photovoltaic power generation control can be achieved. For example, after configuring the capacity, the energy conversion of photovoltaic power generation can be realized based on the capacity, which will not cause waste of resources.

[0109] In some embodiments, the method may further include: obtaining capacity change data corresponding to at least two historical power generation cycles; determining energy utilization rates corresponding to at least two historical power generation cycles based on the capacity change data corresponding to at least two historical power generation cycles; determining a capacity configuration evaluation result based on the energy utilization rates corresponding to at least two historical power generation cycles, the capacity configuration evaluation result being used to characterize whether the capacity configuration is reasonable; if the capacity configuration evaluation result characterizes that the capacity configuration is reasonable, and the maximum energy utilization rate among the energy utilization rates corresponding to at least two historical power generation cycles is less than a second preset energy utilization rate, generating optimization prompt information and feeding it back, the optimization prompt information being used to indicate optimization of at least one of the photovoltaic power generation unit, the energy storage unit and the charging pile.

[0110] In this implementation, when the capacity change data gradually increases, the capacity change data corresponding to at least two historical power generation cycles can be analyzed to determine the energy utilization rate corresponding to at least two historical power generation cycles. The calculation method of the energy utilization rate here can refer to the above embodiment.

[0111] Furthermore, if the energy utilization rate corresponding to at least two historical power generation cycles gradually increases or remains basically unchanged, it can be characterized as reasonable capacity configuration. In other cases, it can be regarded as unreasonable capacity configuration. That is, the capacity configuration plays a role in balancing or improving energy utilization.

[0112] In some embodiments, when the capacity configuration is reasonable, it is determined whether the maximum energy utilization rate in the energy utilization rate is less than the second preset energy utilization rate. If it is less than, it indicates that other aspects may need to be optimized. In other cases, no optimization is required.

[0113] The second preset energy utilization rate may be smaller than the first preset energy utilization rate, and the second preset energy utilization rate represents the minimum economic requirement.

[0114] In some embodiments, at least one of the photovoltaic power generation unit, the energy storage unit, and the charging pile is optimized, which may be the optimization of quantity, the optimization of hardware configuration, etc.

[0115] In some embodiments, the optimization prompt information may be fed back to the management side of the charging station so that the management side may refer to the optimization prompt information for optimization.

[0116] In some embodiments, if the capacity configuration evaluation result indicates that the capacity configuration is unreasonable, a prompt message may be fed back to the R&D personnel, and the prompt message may be used to indicate how to optimize the capacity configuration, for example, optimizing the objective function or constraint conditions of the particle swarm algorithm.

[0117] In the embodiment of the present disclosure, the capacity of the first power generation cycle can be configured by relevant management personnel because there is no data of the reference power generation cycle.

[0118] Through the above technical solution, the energy utilization rate is determined based on the capacity change data of the previous power generation cycle, and based on the energy utilization rate, multiple configurable capacities are determined, and then the target photovoltaic power generation unit capacity and the target energy storage unit capacity are determined from the multiple configurable capacities in combination with the preset particle swarm algorithm, and then the photovoltaic power generation unit and the energy storage unit of the next power generation cycle are configured according to the target photovoltaic power generation unit capacity and the target energy storage unit capacity. On the one hand, the actual capacity data of the previous power generation cycle is used to determine the energy utilization rate, and then the configurable capacity of the next power generation cycle is determined, so that the capacity configuration is more in line with the actual power generation situation. On the other hand, the particle swarm algorithm is used to solve the optimal capacity, thereby improving the efficiency and accuracy of the capacity solution. Therefore, this technical solution can realize efficient and accurate capacity configuration of photovoltaic power generation units and energy storage units, thereby improving the reliability, stability and economy of hybrid energy storage photovoltaic power generation.

[0119] Figure 5 is a block diagram of a hybrid energy storage photovoltaic power generation control device 500 according to an exemplary embodiment. Figure 5 As shown, the device comprises:

[0120] The acquisition module 501 is configured to: acquire the capacity change data corresponding to the previous power generation cycle, and the capacity change data includes the photovoltaic power generation unit capacity and the energy storage unit capacity corresponding to multiple time points respectively. The photovoltaic power generation unit and the energy storage unit are used to provide electrical energy to the charging pile during the power generation cycle.

[0121] The capacity configuration module 502 is configured to: determine the energy utilization rate corresponding to the previous power generation cycle according to the capacity change data; determine multiple configurable capacities according to the energy utilization rate corresponding to the previous power generation cycle, the photovoltaic power generation unit capacity corresponding to the multiple time points, the energy storage unit capacity and the first preset energy utilization rate; determine the target photovoltaic power generation unit capacity and the target energy storage unit capacity from the multiple configurable capacities according to a preset particle swarm algorithm; and perform capacity configuration for the photovoltaic power generation unit and the energy storage unit for the next power generation cycle according to the target photovoltaic power generation unit capacity and the target energy storage unit capacity.

[0122] Regarding the device in the above embodiment, the specific manner in which each module performs operations has been described in detail in the embodiment of the method, and will not be elaborated here.

[0123] Figure 6 is a block diagram of an electronic device 600 according to an exemplary embodiment, and the electronic device 600 can be used as the aforementioned control unit. Figure 6 As shown, the electronic device 600 may include: a processor 601 , a memory 602 . The electronic device 600 may also include one or more of a multimedia component 603 , an input / output (I / O) interface 604 , and a communication component 605 .

[0124] Among them, the processor 601 is used to control the overall operation of the electronic device 600 to complete all or part of the steps in the above-mentioned hybrid energy storage photovoltaic power generation control method. The memory 602 is used to store various types of data to support the operation of the electronic device 600, and these data may include, for example, instructions for any application or method used to operate on the electronic device 600, and application-related data, such as contact data, messages sent and received, pictures, audio, video, etc. The memory 602 can be implemented by any type of volatile or non-volatile storage device or a combination thereof, such as static random access memory (Static Random Access Memory, referred to as SRAM), electrically erasable programmable read-only memory (Electrically Erasable Programmable Read-Only Memory, referred to as EEPROM), erasable programmable read-only memory (Erasable Programmable Read-Only Memory, referred to as EPROM), programmable read-only memory (Programmable Read-Only Memory, referred to as PROM), read-only memory (Read-Only Memory, referred to as ROM), magnetic memory, flash memory, disk or optical disk. The multimedia component 603 may include a screen and an audio component. The screen may be, for example, a touch screen, and the audio component is used to output and / or input audio signals. For example, the audio component may include a microphone for receiving external audio signals. The received audio signal may be further stored in the memory 602 or sent through the communication component 605. The audio component also includes at least one speaker for outputting audio signals. The I / O interface 604 provides an interface between the processor 601 and other interface modules, and the above-mentioned other interface modules may be a keyboard, a mouse, buttons, etc. These buttons may be virtual buttons or physical buttons. The communication component 605 is used for wired or wireless communication between the electronic device 600 and other devices. Wireless communication, such as Wi-Fi, Bluetooth, Near Field Communication (NFC), 2G, 3G or 4G, or a combination of one or more of them, so the corresponding communication component 605 may include: Wi-Fi module, Bluetooth module, NFC module.

[0125] In an exemplary embodiment, the electronic device 600 may be implemented by one or more application specific integrated circuits (ASIC), digital signal processors (DSP), digital signal processing devices (DSPD), programmable logic devices (PLD), field programmable gate arrays (FPGA), controllers, microcontrollers, microprocessors or other electronic components to execute the above-mentioned XXXX method.

[0126] In another exemplary embodiment, a computer-readable storage medium including program instructions is also provided, and when the program instructions are executed by a processor, the steps of the hybrid energy storage photovoltaic power generation control method described above are implemented. For example, the computer-readable storage medium may be the memory 602 including the program instructions described above, and the program instructions may be executed by the processor 601 of the electronic device 600 to complete the hybrid energy storage photovoltaic power generation control method described above.

[0127] In another exemplary embodiment, a computer program product is also provided. The computer program product includes a computer program that can be executed by a processor. When the computer program is executed by the processor, the steps of the hybrid energy storage photovoltaic power generation control method described above are implemented.

[0128] The preferred embodiments of the present disclosure are described in detail above in conjunction with the accompanying drawings; however, the present disclosure is not limited to the specific details in the above embodiments. Within the technical concept of the present disclosure, a variety of simple modifications can be made to the technical solution of the present disclosure, and these simple modifications all fall within the protection scope of the present disclosure.

[0129] It should also be noted that the various specific technical features described in the above specific embodiments can be combined in any suitable manner without contradiction. In order to avoid unnecessary repetition, the present disclosure will not further describe various possible combinations.

[0130] In addition, various embodiments of the present disclosure may be arbitrarily combined, and as long as they do not violate the concept of the present disclosure, they should also be regarded as the contents disclosed by the present disclosure.

Claims

1. A hybrid energy storage photovoltaic power generation control method, characterized in that: include: Acquire capacity change data corresponding to the previous power generation cycle, wherein the capacity change data includes the photovoltaic power generation unit capacity and the energy storage unit capacity corresponding to multiple time points, respectively, wherein the photovoltaic power generation unit and the energy storage unit are respectively used to provide electric energy to the charging pile during the power generation cycle; Determining the energy utilization rate corresponding to the previous power generation cycle according to the capacity change data; Determine multiple configurable capacities according to the energy utilization rate corresponding to the previous power generation cycle, the photovoltaic power generation unit capacities corresponding to the multiple time points, the energy storage unit capacity and the first preset energy utilization rate; According to a preset particle swarm algorithm, determining a target photovoltaic power generation unit capacity and a target energy storage unit capacity from the multiple configurable capacities; According to the target photovoltaic power generation unit capacity and the target energy storage unit capacity, the photovoltaic power generation unit and the energy storage unit are configured with capacity for the next power generation cycle; The determining of multiple configurable capacities according to the energy utilization rate corresponding to the previous power generation cycle, the photovoltaic power generation unit capacities corresponding to the multiple time points, the energy storage unit capacity and the first preset energy utilization rate includes: If the energy utilization rate corresponding to the previous power generation cycle is greater than or equal to the first preset energy utilization rate, randomly sampling the photovoltaic power generation unit capacity and the energy storage unit capacity corresponding to the multiple time points respectively to obtain multiple randomly sampled capacities; If the energy utilization rate corresponding to the previous power generation cycle is less than the first preset energy utilization rate, the photovoltaic power generation unit capacity and the energy storage unit capacity corresponding to the multiple time points are sampled according to the preset time point conditions to obtain multiple capacities of conditional sampling, wherein the preset time point conditions are used to limit the conditions that need to be met at the time points corresponding to the sampled capacities; The plurality of configurable capacities are determined according to the plurality of capacities.

2. The hybrid energy storage photovoltaic power generation control method according to claim 1, characterized in that: Determining the energy utilization rate corresponding to the previous power generation cycle according to the capacity change data includes: Determining a first capacity consumption value according to the photovoltaic power generation unit capacities corresponding to the multiple time points respectively; Determining a second capacity consumption value according to the energy storage unit capacities corresponding to the multiple time points respectively; determining a first energy utilization rate according to the first capacity consumption value and the maximum capacity of the photovoltaic power generation unit capacities corresponding to the multiple time points; Determine a second energy utilization rate according to the second capacity consumption value and the maximum capacity of the energy storage unit capacities corresponding to the multiple time points respectively; A final energy utilization rate is determined according to the first energy utilization rate and the second energy utilization rate.

3. The hybrid energy storage photovoltaic power generation control method according to claim 2, characterized in that: The determining a final energy utilization rate according to the first energy utilization rate and the second energy utilization rate includes: Determine a first weight and a second weight according to the maximum capacity of the photovoltaic power generation unit capacities corresponding to the multiple time points and the maximum capacity of the energy storage unit capacities corresponding to the multiple time points, wherein the first weight is the weight corresponding to the first energy utilization rate, and the second weight is the weight corresponding to the second energy utilization rate, wherein if the maximum capacity of the photovoltaic power generation unit capacities corresponding to the multiple time points is greater than the maximum capacity of the energy storage unit capacities corresponding to the multiple time points, then the first weight is less than the second weight, and if the maximum capacity of the photovoltaic power generation unit capacities corresponding to the multiple time points is less than the maximum capacity of the energy storage unit capacities corresponding to the multiple time points, then the first weight is greater than the second weight; A final energy utilization rate is determined according to the first weight, the second weight, the first energy utilization rate, and the second energy utilization rate.

4. The hybrid energy storage photovoltaic power generation control method according to claim 1, characterized in that: The hybrid energy storage photovoltaic power generation control method further includes: Obtain expected investment costs and expected operating benefits; Determining an economic impact value based on the expected investment cost and the expected operating income; Acquire a preset corresponding relationship, where the preset corresponding relationship is used to characterize the corresponding relationship between the economic impact value and the capacity interval; Correspondingly, determining the multiple configurable capacities according to the multiple capacities includes: Determining a target capacity range according to the economic impact value and the preset corresponding relationship; Comparing the multiple capacities with the target capacity interval to obtain a comparison result; Determining, according to the comparison result, to expand the multiple capacities; Expanding the multiple capacities according to the target capacity interval to obtain multiple expanded capacities; The expanded multiple capacities are determined as the multiple configurable capacities.

5. The hybrid energy storage photovoltaic power generation control method according to claim 1, characterized in that: The method of determining the target photovoltaic power generation unit capacity and the target energy storage unit capacity from the multiple configurable capacities according to the preset particle swarm algorithm includes: Obtaining a preset objective function, wherein the preset objective function is used to characterize the corresponding relationship between the capacity, the photovoltaic unit loss rate, and the charging pile loss rate; Obtaining preset constraint conditions, wherein the preset constraint conditions include a photovoltaic unit loss rate constraint condition and a charging pile loss rate condition; According to the preset particle swarm algorithm, the preset objective function and the preset constraints, the target photovoltaic power generation unit capacity and the target energy storage unit capacity are determined from the multiple configurable capacities; wherein the preset objective function and the preset constraints are used by the preset particle swarm algorithm to evaluate the fitness of particles, and the multiple configurable capacities are particles in the preset particle swarm algorithm.

6. The hybrid energy storage photovoltaic power generation control method according to claim 1, characterized in that: The hybrid energy storage photovoltaic power generation control method further includes: Obtaining a preset simulation system, wherein the preset simulation system is used to perform consumption simulation on the photovoltaic power generation unit capacity configuration and the energy storage unit capacity; Inputting the target photovoltaic power generation unit capacity and the target energy storage unit capacity into the preset simulation system to obtain simulation capacity consumption data, wherein the simulation capacity consumption data includes the photovoltaic power generation unit capacity and the energy storage unit capacity corresponding to a plurality of virtual time points respectively; Determining a predicted energy utilization rate corresponding to a next power generation cycle according to the simulated capacity consumption data; Correspondingly, the configuration of the capacity of the photovoltaic power generation unit and the energy storage unit for the next power generation cycle according to the target photovoltaic power generation unit capacity and the target energy storage unit capacity includes: Comparing the predicted energy utilization rate with the energy utilization rate corresponding to the previous power generation cycle to obtain a comparison result; According to the comparison result, the target photovoltaic power generation unit capacity and the target energy storage unit capacity, the photovoltaic power generation unit and the energy storage unit are configured for capacity in the next power generation cycle.

7. The hybrid energy storage photovoltaic power generation control method according to claim 6, characterized in that: The step of configuring the capacity of the photovoltaic power generation unit and the energy storage unit for the next power generation cycle according to the comparison result, the target photovoltaic power generation unit capacity, and the target energy storage unit capacity includes: If the predicted energy utilization rate is greater than or equal to the energy utilization rate corresponding to the previous power generation cycle, the initial capacity of the photovoltaic power generation unit of the next power generation cycle is configured as the target photovoltaic power generation unit capacity, and the initial capacity of the energy storage unit of the next power generation cycle is configured as the target energy storage unit capacity; If the predicted energy utilization rate is less than the energy utilization rate corresponding to the previous power generation cycle, the target capacity is determined according to the target photovoltaic power generation unit capacity and the target energy storage unit capacity, and the initial capacity of the photovoltaic power generation unit and the initial capacity of the energy storage unit of the next power generation cycle are both configured as the target capacity.

8. The hybrid energy storage photovoltaic power generation control method according to claim 1, characterized in that: The hybrid energy storage photovoltaic power generation control method also includes: Obtain capacity change data corresponding to at least two historical power generation cycles; Determining energy utilization rates corresponding to the at least two historical power generation cycles respectively according to the capacity change data corresponding to the at least two historical power generation cycles respectively; Determining a capacity configuration evaluation result according to the energy utilization rates respectively corresponding to the at least two historical power generation cycles, wherein the capacity configuration evaluation result is used to indicate whether the capacity configuration is reasonable; If the capacity configuration evaluation result indicates that the capacity configuration is reasonable, and the maximum energy utilization rate among the energy utilization rates corresponding to the at least two historical power generation cycles is less than the second preset energy utilization rate, optimization prompt information is generated and fed back, and the optimization prompt information is used to indicate the optimization of at least one of the photovoltaic power generation unit, the energy storage unit and the charging pile.

9. A hybrid energy storage photovoltaic power generation control system, characterized in that: include: Charging stations; A photovoltaic power generation unit, connected to the charging pile, for providing electric energy to the charging pile according to the configured capacity; An energy storage unit, connected to the charging pile and the photovoltaic power generation unit respectively, for providing electric energy to the charging pile according to the configured capacity; A control unit is connected to the charging pile, the photovoltaic power generation unit and the energy storage unit respectively, and is used to implement the hybrid energy storage photovoltaic power generation control method as described in any one of claims 1 to 8.

Images