Control method, device and equipment of light storage and charging integrated system and medium

Abstract

The invention relates to the technical field of energy management and intelligent control, and discloses a control method, device and equipment of an optical storage and charging integrated system and a medium, and the method comprises the steps: obtaining a mapping relation between the total operation cost of the optical storage and charging integrated system and the active power of a power grid and the active power of energy storage in a prediction time period, the total operation cost is configured to be power grid electricity taking cost and energy storage operation cost; minimizing the total operation cost under the constraint of the constraint condition to obtain the target power grid active power and the target energy storage active power of each prediction time point in the prediction time period; and based on the target energy storage active power and the target power grid active power corresponding to each prediction time point, controlling the photovoltaic storage and charging integrated system. By implementing the method provided by the invention, the overall operation cost of the optical storage and charging integrated system can be optimized.

Description

Technical Field

[0001] This invention relates to the field of energy management and intelligent control technology, specifically to control methods, devices, equipment, and media for integrated photovoltaic, energy storage, and charging systems. Background Technology

[0002] With the rapid development of renewable energy and the widespread adoption of electric vehicles, integrated photovoltaic, energy storage, and charging systems are increasingly being used in industrial and commercial sectors. These systems integrate photovoltaic systems, energy storage systems, and charging piles, enabling coordinated operation of multiple systems.

[0003] However, existing energy storage system charging and discharging strategies only consider the cost of purchasing electricity from the grid, without taking into account the cost of battery losses in the energy storage system, making it difficult to achieve the goal of optimizing the overall cost of the integrated photovoltaic-storage-charging system. Summary of the Invention

[0004] This invention provides a control method, device, equipment, and medium for an integrated photovoltaic, energy storage, and charging system, in order to solve the problem of achieving the optimal overall cost of the integrated photovoltaic, energy storage, and charging system.

[0005] In a first aspect, the present invention provides a control method for an integrated photovoltaic-storage-charging system, comprising: obtaining a mapping relationship between the total operating cost of the integrated photovoltaic-storage-charging system and the active power of the power grid and the active power of the energy storage during a predicted time period, wherein the total operating cost is configured as the power grid extraction cost and the energy storage operating cost; minimizing the total operating cost under constraints to obtain the target active power of the power grid and the target active power of the energy storage at each predicted time point during the predicted time period; and controlling the integrated photovoltaic-storage-charging system based on the target active power of the energy storage and the target active power of the power grid at each predicted time point; wherein the constraints are configured as follows: the total output power of the integrated photovoltaic-storage-charging system is the same as the predicted total load power at each predicted time point; the remaining battery capacity of the energy storage system is less than or equal to the maximum remaining battery capacity and greater than or equal to the minimum remaining battery capacity at each predicted time point; the remaining battery capacity at the last predicted time point is greater than or equal to a battery remaining capacity threshold; and the total charging amount of the energy storage system during the predicted time period is less than the maximum total charging amount and the total discharging amount is less than the maximum total discharging amount.

[0006] The control method for the integrated photovoltaic-storage-charging system provided in this embodiment incorporates the operating cost of the energy storage system and the energy storage operating cost into the construction of the total operating cost of the integrated photovoltaic-storage-charging system. By minimizing the total operating cost, the active power of the grid and the active power of the energy storage and photovoltaic at each predicted time point in the predicted time period are determined. The operation of the integrated photovoltaic-storage-charging system is controlled by the active power of the grid and the active power of the energy storage at each predicted time point, so that the overall operating cost of the integrated photovoltaic-storage-charging system in the predicted time period reaches the optimum.

[0007] In one optional implementation, the process of constructing the total operating cost includes: constructing the grid power extraction cost based on the fusion of the grid active power and the grid power extraction unit cost within the predicted time period; constructing the energy storage operating cost based on the fusion of the energy storage active power and the energy storage operating unit cost within the predicted time period; and constructing the total operating cost based on the fusion of the grid power extraction cost and the energy storage operating cost.

[0008] By combining the grid power extraction cost and the energy storage operation cost, the total operating cost of the energy storage system can be accurately characterized. This allows for subsequent minimization of the total operating cost, enabling a more accurate determination of the target grid active power and target energy storage active power at each predicted time point.

[0009] In one optional implementation, the unit cost of energy storage operation is configured as the unit cost of battery degradation, the unit cost of model incentives, and the unit cost of power switching; the energy storage operation cost is constructed based on the fusion of the active power of energy storage and the unit cost of energy storage operation within the prediction period, including: based on Construct a prediction of battery degradation costs over a given time period. Used to represent the cost of battery degradation. Used to represent the active power of energy storage at the predicted time point t. Used to represent the unit cost of battery degradation, T is used to represent the last prediction time point; based on Construct the model incentive cost within the prediction period. Used to represent the model incentive cost Used to represent the model incentive unit cost at the predicted time point t; based on Construct the power switching cost within the predicted time period. Used to represent power switching costs The unit cost of power switching is used to represent the energy storage operating cost, which is configured as battery degradation cost, model incentive cost, and power switching cost.

[0010] By combining battery degradation costs, model incentive costs, and power switching costs, the energy storage operating costs of an energy storage system can be characterized more accurately. This not only comprehensively covers the battery losses during the use of the energy storage system, but also fits the time-sharing operation characteristics of the energy storage system, achieving a high degree of matching between cost accounting and the actual operating state of the energy storage.

[0011] In one optional implementation, the total output power of the integrated photovoltaic-storage-charging system at each predicted time point is the same as the predicted total load power, including: based on This ensures that the total output power at the predicted time point t is the same as the predicted total load power; where, Used to represent the predicted total load power at prediction time point t. Used to represent the predicted active power of photovoltaic power at prediction time t. Used to represent the active power of energy storage at the predicted time point t. Used to represent the active power of the power grid at the predicted time point t; where... Subject to , Subject to ;in, Used to indicate the maximum discharge power of an energy storage system Used to indicate the maximum charging power of an energy storage system Used to represent the maximum active power of the power grid.

[0012] pass Limiting the overall supply and demand balance of the photovoltaic-storage-charging integrated system and imposing corresponding constraints on the active power of energy storage and the active power of the grid can regulate the safe operation boundary of the energy storage system and the grid. In turn, it can achieve the stable and safe operation of the photovoltaic-storage-charging integrated system and the grid, promote the full consumption of photovoltaic power, and maximize the self-consumption rate of photovoltaic power.

[0013] In one optional implementation, the total charging amount of the energy storage system during the predicted time period is less than the maximum total charging amount and the total discharging amount is less than the maximum total discharging amount, including: based on , Make the total charge amount less than the maximum total charge amount; based on , To ensure that the total discharge is less than the maximum total discharge; where, This represents the charging power of the energy storage system at the predicted time point t. Used to represent the time interval between two predicted time points. Used to indicate the number of full charge and discharge cycles of the energy storage system within a predicted time period. Used to indicate the charging efficiency of an energy storage system. Used to characterize the battery capacity of energy storage systems SoH Used to indicate battery health. Used to represent the discharge power of the energy storage system at the predicted time point t. The value is used to represent the discharge efficiency of the energy storage system, and n represents the total number of prediction time points.

[0014] By limiting the total charge of the energy storage system's batteries within a predicted time period to be less than the maximum total charge, the number of times the batteries in the energy storage system can be fully charged within the predicted time period is limited. Similarly, by limiting the total discharge of the energy storage system's batteries within a predicted time period to be less than the maximum total discharge, the number of times the batteries in the energy storage system can be fully discharged within the predicted time period is limited. In this way, by limiting the number of times the batteries in the energy storage system can be fully charged and discharged, the service life of the energy storage system's batteries can be extended.

[0015] In an alternative implementation, the constraints further include: If satisfied as well as Based on Determine the actual active power of photovoltaic power at the predicted time point t, and based on Determine the photovoltaic curtailment power at the predicted time point t; and / or, based on This allows the integrated photovoltaic, energy storage, and charging system to draw power from the grid; among which, Used to represent the remaining battery charge at the predicted time point t. Used to indicate the maximum remaining battery capacity. Used to represent the predicted active power of photovoltaic power at prediction time t. Used to represent the predicted total load power at prediction time t. Used to represent the maximum charging power of the energy storage system at the predicted time point t. Used to represent the actual active power of photovoltaic power at the predicted time point t. Used to represent the photovoltaic curtailment power at the predicted time point t. Used to represent the active power of the power grid at the predicted time point t.

[0016] pass It can accurately determine the actual active power of a photovoltaic system, reducing unnecessary energy waste. Furthermore, through... It can accurately and reasonably determine the curtailment power of the photovoltaic system, avoiding the impact of excessive output of the photovoltaic system on the load of the photovoltaic-storage-charging integrated system, the energy storage system and the grid side.

[0017] By setting P_grid(t)≥0, the photovoltaic-storage-charging integrated system can be restricted from supplying power to the grid, and can only draw power from the grid. This avoids risks such as grid voltage fluctuations and grid connection protection malfunctions caused by reverse power supply, and ensures the safety of the grid connection side and the grid.

[0018] In one alternative implementation, the method further includes: based on Determine the remaining battery capacity of the energy storage system at the predicted time point t+1. Used to determine the target grid active power and target energy storage active power at the prediction time point t+1; where, Used to represent the remaining battery charge at the predicted time point t. Used to represent the remaining battery power at the predicted time point t+1. Used to represent the active power of energy storage at the predicted time point t. Used to represent the average charge and discharge efficiency of an energy storage system. Used to represent the time interval between two predicted time points. Used to characterize the battery capacity of energy storage systems.

[0019] By using the remaining battery power and target energy storage active power at prediction time t, the remaining battery power at prediction time t+1 can be accurately determined. Subsequently, the target grid active power and target energy storage active power at prediction time t+1 can be determined by using the remaining battery power at prediction time t+1. In this way, closed-loop prediction of the target grid active power and target energy storage active power at each prediction time within the prediction period can be achieved.

[0020] Secondly, the present invention provides a control device for an integrated photovoltaic-storage-charging system. The device includes: an acquisition module for acquiring the mapping relationship between the total operating cost of the integrated photovoltaic-storage-charging system and the active power of the power grid and the active power of energy storage within a predicted time period, wherein the total operating cost is configured as the power grid extraction cost and the energy storage operating cost; a processing module for minimizing the total operating cost under constraints to obtain the target active power of the power grid and the target active power of energy storage at each predicted time point within the predicted time period; and a control module for controlling the integrated photovoltaic-storage-charging system based on the target active power of energy storage and the target active power of the power grid at each predicted time point. The constraints are configured as follows: the total output power of the integrated photovoltaic-storage-charging system is the same as the predicted total load power at each predicted time point; the remaining battery capacity of the energy storage system is less than or equal to the maximum remaining battery capacity and greater than or equal to the minimum remaining battery capacity at each predicted time point; the remaining battery capacity at the last predicted time point is greater than or equal to a battery remaining capacity threshold; and the total charging amount of the energy storage system within the predicted time period is less than the maximum total charging amount and the total discharging amount is less than the maximum total discharging amount.

[0021] Thirdly, the present invention provides an electronic device, comprising: a memory and a processor, wherein the memory and the processor are communicatively connected to each other, the memory stores computer instructions, and the processor executes the computer instructions to perform the control method of the integrated optical storage and charging system of the first aspect or any corresponding embodiment described above.

[0022] Fourthly, the present invention provides a computer-readable storage medium storing computer instructions for causing a computer to execute the control method of the integrated optical storage and charging system described in the first aspect or any corresponding embodiment.

[0023] Fifthly, the present invention provides a computer program product, including computer instructions, which are used to cause a computer to execute the control method of the integrated photovoltaic storage and charging system described in the first aspect or any corresponding embodiment. Attached Figure Description

[0024] To more clearly illustrate the specific embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the specific embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of the present invention. For those skilled in the art, other drawings can be obtained from these drawings without creative effort.

[0025] Figure 1 This is a schematic diagram showing the connection between the photovoltaic, energy storage, and charging integrated system and the power grid; Figure 2 This is a schematic diagram of an application scenario according to an embodiment of the present invention; Figure 3 This is a schematic flowchart of the first type of control method for an integrated photovoltaic, energy storage and charging system according to an embodiment of the present invention; Figure 4 This is a second flowchart illustrating the control method of the integrated photovoltaic, energy storage, and charging system according to an embodiment of the present invention. Figure 5 This is a schematic diagram of the control system of an integrated photovoltaic storage and charging system according to an embodiment of the present invention; Figure 6 This is a flowchart of a control method for an integrated photovoltaic, energy storage, and charging system according to an embodiment of the present invention; Figure 7 This is a structural block diagram of the control device for an integrated photovoltaic, energy storage, and charging system according to an embodiment of the present invention; Figure 8 This is a schematic diagram of the hardware structure of an electronic device according to an embodiment of the present invention. Detailed Implementation

[0026] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0027] It is understood that before using the technical solutions disclosed in the various embodiments of the present invention, users should be informed of the types, scope of use, and usage scenarios of the personal information involved in the present invention and their authorization should be obtained in accordance with relevant laws and regulations through appropriate means.

[0028] The terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of technical features indicated. Thus, a feature defined as "first" or "second" may explicitly or implicitly include one or more of that feature. In the description of this invention, "a plurality of" means two or more, unless otherwise explicitly specified.

[0029] With the rapid development of renewable energy and the widespread adoption of electric vehicles, integrated photovoltaic, energy storage, and charging systems are increasingly being used in industrial and commercial sectors. For example... Figure 1 As shown, the photovoltaic-storage-charging integrated system integrates a photovoltaic system, an energy storage system, a charging pile, and other loads such as air conditioners. The photovoltaic system, energy storage system, charging pile, and other loads operate collaboratively under the control of the photovoltaic-storage-charging integrated system controller.

[0030] For example, such as Figure 1 As shown, the electricity generated by the photovoltaic system can be used by the energy storage system, charging piles, and other loads. The energy storage system can draw power from the grid or supply power to the grid, and it can also be used by charging piles and other loads. The integrated photovoltaic-energy storage-charging system controller can communicate with the grid to obtain the unit cost of grid power; the integrated photovoltaic-energy storage-charging system controller can also communicate with the integrated photovoltaic-energy storage-charging system and control the operation of the integrated photovoltaic-energy storage-charging system according to corresponding control strategies such as the active power of the grid and the active power of the energy storage.

[0031] However, the charging and discharging strategies of existing energy storage systems only consider the cost of purchasing electricity from the grid, without incorporating factors such as battery loss costs and reverse current prevention into the formulation of the charging and discharging strategies. This makes it difficult to achieve the goal of optimizing the overall cost of the integrated photovoltaic-storage-charging system.

[0032] In view of this, this application proposes a control method for an integrated photovoltaic-energy storage-charging system. This method incorporates the battery degradation cost, power switching cost, and model incentive cost generated by off-peak charging and peak discharge strategies into the total operating cost of the integrated photovoltaic-energy storage-charging system. By minimizing the total operating cost, the method determines the grid active power and energy storage active power at each predicted time point within the predicted time period, where the total operating cost is minimized. The method then controls the operation of the integrated photovoltaic-energy storage-charging system based on the grid active power and energy storage active power at each predicted time point, thereby optimizing the overall operating cost of the integrated photovoltaic-energy storage-charging system.

[0033] As an optional application scenario of this invention, such as Figure 2 As shown, the control system of this integrated photovoltaic, energy storage, and charging system may include at least one terminal device and at least one server. Figure 2 The system is illustrated in the example, which includes a computer 101, a mobile terminal 102, and a server 103, and the terminal devices such as the computer 101 and the mobile terminal 102 are connected to the server 103 through a network 110.

[0034] Specifically, the terminal device can be a smartphone, tablet, laptop, PDA, desktop computer, game console, smart TV, smart wearable device, in-vehicle terminal, VR (Virtual Reality) device, AR (Augmented Reality) device, etc. Server 103 can be a standalone physical server, a server cluster, a distributed system, or a cloud server providing cloud services. Network 110 can be a wired or wireless network, examples of which include, but are not limited to, the Internet, corporate intranet, local area network, wide area network, mobile communication network, and combinations thereof.

[0035] According to an embodiment of the present invention, a control method embodiment for an integrated photovoltaic storage and charging system is provided. It should be noted that the steps shown in the flowchart in the accompanying drawings can be executed in a computer system such as a set of computer-executable instructions. Furthermore, although a logical order is shown in the flowchart, in some cases, the steps shown or described may be executed in a different order than that shown here.

[0036] This embodiment provides a control method for an integrated photovoltaic, energy storage, and charging system, which can be used in terminal equipment. Figure 3 This is a flowchart of a control method for an integrated photovoltaic, energy storage, and charging system according to an embodiment of the present invention, such as... Figure 3 As shown, the process includes the following steps: Step S301: Obtain the mapping relationship between the total operating cost of the photovoltaic-storage-charging integrated system and the active power of the power grid and the active power of the energy storage during the predicted time period. The total operating cost is configured as the power grid extraction cost and the energy storage operating cost.

[0037] The predicted time period here can be one day, such as 0:00 to 24:00, or multiple days; this application does not make a specific limitation on this.

[0038] The active power of the power grid can be defined as the bidirectional active power between the photovoltaic-storage-charging integrated system and the power grid during the predicted time period. When the active power of the power grid is positive, it indicates that the photovoltaic-storage-charging integrated system is drawing power from the power grid; when the active power of the power grid is negative, it indicates that the photovoltaic-storage-charging integrated system is supplying power to the power grid.

[0039] Energy storage active power can be defined as the active power during the charging and discharging process of the energy storage system within a predicted time period. When the energy storage active power is positive, it represents the charging active power of the energy storage system; when the energy storage active power is negative, it represents the discharging active power of the energy storage system.

[0040] The mapping relationship can be a quantitative relationship between the total operating cost of the photovoltaic-storage-charging integrated system and the active power of the grid and the active power of the energy storage system within the predicted time period. Among them, the active power of the grid can affect the grid power extraction cost in the total operating cost; the active power of the energy storage can affect the energy storage operating cost in the total operating cost, and the energy storage operating cost can be the operating cost of the energy storage system in the photovoltaic-storage-charging integrated system.

[0041] As a specific example, the total operating cost can be a cost function with the grid active power and the energy storage active power as independent variables.

[0042] As a specific example, the sum of the grid power extraction cost and the energy storage operation cost can be the total operating cost of the integrated photovoltaic-storage-charging system. Alternatively, the total operating cost of the integrated photovoltaic-storage-charging system can be obtained by weighted averaging the grid power extraction cost and the energy storage operation cost.

[0043] Here, the target file located at the preset storage location can be read to obtain the mapping relationship between the total operating cost of the photovoltaic-storage-charging integrated system and the active power of the power grid and the active power of energy storage.

[0044] Step S302: Minimize the total operating cost under the constraints to obtain the target grid active power and target energy storage active power at each prediction time point in the prediction period. The constraints are configured as follows: at each prediction time point, the total output power of the photovoltaic-storage-charging integrated system is the same as the predicted total load power; at each prediction time point, the remaining battery capacity of the energy storage system is less than or equal to the maximum remaining battery capacity and greater than or equal to the minimum remaining battery capacity; at the last prediction time point, the remaining battery capacity is greater than or equal to the remaining battery capacity threshold; and during the prediction period, the total charging amount of the energy storage system is less than the maximum total charging amount and the total discharging amount is less than the maximum total discharging amount.

[0045] Here, an optimization algorithm can be used to minimize the total operating cost to obtain the target grid active power and target energy storage active power at each predicted time point. The optimization algorithm can be a convex optimization algorithm, a particle swarm optimization algorithm, or a genetic algorithm, etc., and this application does not specifically limit it.

[0046] The prediction time points can be discrete time-series nodes obtained by dividing the entire prediction period into fixed time intervals. For example, if the prediction period is set to 0:00 to 24:00 in a day and the fixed time interval is set to 0.25 hours, then the prediction time points will be 0:00, 0.25, 0.5, ..., 24:00.

[0047] The predicted total load power can be the total load power of the integrated photovoltaic-storage-charging system at each predicted time point, output by the load prediction model. The total load power can include the active power of the charging piles and the active power of other loads such as air conditioners. The load prediction model can be trained based on a large language model architecture, a machine learning model architecture, or even a combination of multiple model architectures. No specific limitations are imposed here, as long as the model can predict the total load power of the integrated photovoltaic-storage-charging system at each predicted time point.

[0048] As a specific example, load forecasting models can predict the total load power at each forecast time point based on information such as historical load sequences, time characteristics of the forecast time point, meteorological data, and whether there is a planned power outage.

[0049] Here, the remaining battery capacity of the energy storage system at the predicted time point being less than or equal to the maximum remaining battery capacity and greater than or equal to the minimum remaining battery capacity can be expressed as follows: By setting maximum and minimum limits on the remaining battery capacity of the energy storage system, overcharging and over-discharging of the energy storage battery can be effectively prevented. Therefore, the safe operation of the energy storage system and the service life of the energy storage battery can be extended.

[0050] Here, the battery remaining capacity at the last predicted time point being greater than or equal to the battery remaining capacity threshold can be expressed as: Where C represents the battery's remaining power threshold. By limiting the remaining battery power of the energy storage system at the last prediction time point, it is possible to ensure that the energy storage system's battery has a minimum reserve power after the prediction period ends. This reserves a basic power for the stable start-up and continuous operation of the photovoltaic-storage-charging integrated system in the next prediction period, while also avoiding the aging risk of batteries being left idle for a long time with low power.

[0051] By limiting the total charging and discharging amount of the energy storage system within the predicted time period, i.e., limiting the number of full charging and discharging cycles of the energy storage system within the predicted time period, the rate of battery degradation in the energy storage system can be slowed down, thereby extending the service life of the batteries in the energy storage system.

[0052] Step S303: Control the photovoltaic-storage-charging integrated system based on the target energy storage active power and the target grid active power corresponding to each predicted time point.

[0053] Following the previous example, the control method of this application is set to be executed before 0:00 to obtain the target energy storage active power and the target grid active power at predicted time points such as 0:00, 0.25, and 0.5:00. Then, the photovoltaic-storage-charging integrated system is controlled to operate according to the target energy storage active power and the target grid active power corresponding to 0:00 during the time period from 0:00 to 0.25:00.

[0054] However, if the actual total load power of the photovoltaic-storage-charging integrated system at point 0.25 differs from the predicted total load power output by the load prediction model, the actual total load power at point 0.25 can be used to continue executing the control method of this application to obtain the target energy storage active power and target grid active power at points 0.25, 0.5, etc., in a new round. The operation of the photovoltaic-storage-charging integrated system can then be controlled according to the target energy storage active power and target grid active power at each prediction time point in the new round. By repeating this process, the photovoltaic-storage-charging integrated system can be continuously optimized, thereby achieving the optimal overall cost of the photovoltaic-storage-charging integrated system within the prediction time period.

[0055] The control method for the integrated photovoltaic-storage-charging system provided in this embodiment incorporates the operating cost of the energy storage system and the energy storage operating cost into the construction of the total operating cost of the integrated photovoltaic-storage-charging system. By minimizing the total operating cost, the active power of the grid and the active power of the energy storage and photovoltaic at each predicted time point in the predicted time period are determined. The operation of the integrated photovoltaic-storage-charging system is controlled by the active power of the grid and the active power of the energy storage at each predicted time point, so that the overall operating cost of the integrated photovoltaic-storage-charging system in the predicted time period reaches the optimum.

[0056] This embodiment provides a control method for an integrated photovoltaic, energy storage, and charging system, which can be used in terminal equipment. Figure 4 This is a flowchart of a control method for an integrated photovoltaic, energy storage, and charging system according to an embodiment of the present invention, such as... Figure 4 As shown, the process includes the following steps: Step S401: Obtain the mapping relationship between the total operating cost of the photovoltaic-storage-charging integrated system and the active power of the power grid and the active power of the energy storage during the predicted time period. The total operating cost is configured as the power grid extraction cost and the energy storage operating cost.

[0057] Specifically, the process of constructing the total operating cost in step S401 above includes: Step S4011: Based on the fusion of the active power of the power grid and the unit cost of power grid extraction within the predicted time period, construct the power grid extraction cost.

[0058] This is where you can pass This indicates the cost of electricity extraction from the power grid during the predicted time period. Used to represent the cost of electricity from the power grid during the predicted time period. Used to represent the active power of the power grid at the predicted time point t. Used to represent the unit cost of electricity taken from the power grid at the predicted time point t.

[0059] Step S4012: Based on the fusion of the active power of energy storage and the unit cost of energy storage operation within the predicted time period, construct the energy storage operation cost.

[0060] The unit cost of energy storage operation here can include the unit cost of battery degradation, the unit cost of model incentives, and the unit cost of power switching.

[0061] Here, the unit cost of energy storage operation can be obtained by weighted fusion of the unit cost of battery degradation, the unit cost of model incentive, and the unit cost of power switching; then, based on the fusion of the active power of energy storage and the unit cost of energy storage operation within the prediction period, the energy storage operation cost can be constructed.

[0062] Of course, in some alternative implementations, step S4012 may include: Step a1, based on Construct a prediction of battery degradation costs over a given time period. Used to represent the cost of battery degradation. Used to represent the active power of energy storage at the predicted time point t. The unit cost of battery degradation is used to represent the cost per unit of battery degradation, and T is used to represent the last predicted time point.

[0063] Step a2, based on Construct the model incentive cost within the prediction period. Used to represent the model incentive cost This is used to represent the unit cost of the model incentive at the predicted time point t.

[0064] Step a3, based on Construct the power switching cost within the predicted time period. Used to represent power switching costs The unit cost of power switching is used to represent the energy storage operating cost, which is configured as battery degradation cost, model incentive cost, and power switching cost.

[0065] As a specific example, we can first obtain the total cost of the battery in the energy storage system and the total number of full charge and discharge cycles of the battery during its life cycle; then, based on the total cost of the battery and the total number of full charge and discharge cycles, we can determine the unit cost of the battery for one full charge or full discharge cycle; furthermore, based on the power and unit cost of one full charge or full discharge cycle, we can determine the cost corresponding to the unit power, that is, obtain the unit cost of battery degradation.

[0066] As a specific example, if If the cost is less than or equal to the unit cost of electricity drawn from the grid during off-peak hours, then ;like If it is greater than or equal to the peak-hour grid power extraction unit cost, then ;in, This is used to represent the cost incentive coefficient, and the cost incentive coefficient can be flexibly set according to the actual situation. This application does not make specific limitations on it.

[0067] In addition, incorporating power switching costs into energy storage operation costs can effectively avoid ineffective charging and discharging behavior in the energy storage system, prevent the batteries in the energy storage system from frequently switching between charging and discharging, which would cause meaningless losses and age degradation, and suppress the oscillation of the target grid active power and the target energy storage active power at each prediction time point within the prediction period. This prevents frequent and large fluctuations in power from causing instability in the operation of the entire photovoltaic-storage-charging integrated system, and ensures the smoothness and feasibility of the predicted target grid active power and the target energy storage active power.

[0068] Here, the battery degradation cost, model incentive cost, and power switching cost can be directly added together to obtain the energy storage operating cost. For example, Where C represents the operating cost of energy storage.

[0069] Of course, the energy storage operating cost can also be obtained by weighting and fusing the battery degradation cost, model incentive cost, and power switching cost.

[0070] By combining battery degradation costs, model incentive costs, and power switching costs, the energy storage operating costs of an energy storage system can be characterized more accurately. This not only comprehensively covers the battery losses during the use of the energy storage system, but also fits the time-sharing operation characteristics of the energy storage system, achieving a high degree of matching between cost accounting and the actual operating state of the energy storage.

[0071] Step S4013: Based on the integration of grid power extraction cost and energy storage operation cost, construct the total operating cost.

[0072] As a specific example, the power grid extraction cost and energy storage operation cost can be weighted and integrated, or the power grid extraction cost and energy storage operation cost can be directly integrated to obtain the total operating cost.

[0073] Step S4014: Obtain the mapping relationship between the total operating cost of the integrated photovoltaic-storage-charging system and the active power of the power grid and the active power of energy storage during the predicted time period. For details, please refer to [link to relevant documentation]. Figure 3 Step S301 of the illustrated embodiment will not be described again here.

[0074] By combining the grid power extraction cost and the energy storage operation cost, the total operating cost of the energy storage system can be accurately characterized. This allows for subsequent minimization of the total operating cost, enabling a more accurate determination of the target grid active power and target energy storage active power at each predicted time point.

[0075] Step S402: Minimize the total operating cost under the constraints to obtain the target grid active power and target energy storage active power at each prediction time point in the prediction period. The constraints are configured as follows: at each prediction time point, the total output power of the photovoltaic-storage-charging integrated system is the same as the predicted total load power; at each prediction time point, the remaining battery capacity of the energy storage system is less than or equal to the maximum remaining battery capacity and greater than or equal to the minimum remaining battery capacity; at the last prediction time point, the remaining battery capacity is greater than or equal to the remaining battery capacity threshold; and during the prediction period, the total charging amount of the energy storage system is less than the maximum total charging amount and the total discharging amount is less than the maximum total discharging amount.

[0076] In some optional implementations, ensuring that the total output power of the integrated photovoltaic-storage-charging system is the same as the predicted total load power at each predicted time point includes: Step b1, based on This ensures that the total output power at the predicted time point t is the same as the predicted total load power; where, Used to represent the predicted total load power at prediction time point t. Used to represent the predicted active power of photovoltaic power at prediction time t. Used to represent the active power of energy storage at the predicted time point t. Used to represent the active power of the power grid at the predicted time point t; where... Subject to , Subject to ;in, Used to indicate the maximum discharge power of an energy storage system Used to indicate the maximum charging power of an energy storage system Used to represent the maximum active power of the power grid.

[0077] The photovoltaic (PV) predicted active power can be the active power of the PV system in the integrated PV-storage-charging system at various predicted time points, output by the PV prediction model. The PV prediction model can be trained based on a large language model architecture, a machine learning model architecture, or a combination of multiple model architectures. No specific limitation is made here, as long as it can predict the active power of the PV system at various predicted time points.

[0078] As a specific example, information such as the historical active power sequence of the photovoltaic system, meteorological data, the location of the photovoltaic system, and various prediction time points can be input into the photovoltaic prediction model, so that the photovoltaic prediction model can output the photovoltaic predicted active power at each prediction time point.

[0079] This setting limits the total output power of the photovoltaic-storage-charging integrated system to be the same as the predicted total load power. This can achieve a supply-demand balance for the photovoltaic-storage-charging integrated system, ensuring reliable power supply to the load of the system while maximizing the absorption of the electricity generated by the photovoltaic system, thereby maximizing the self-consumption rate of photovoltaics and improving the operating efficiency and economy of the photovoltaic-storage-charging integrated system.

[0080] This section discusses the active power of energy storage. By imposing constraints, the risk of overcharging caused by over-power charging of the energy storage system can be avoided, as well as the damage caused by over-discharging of the energy storage system. This can extend the service life of the energy storage system and prevent the failure of the energy storage system from affecting the power supply of the photovoltaic-energy storage-charging integrated system, thus ensuring the safe and stable operation of the energy storage system.

[0081] This is achieved through restrictions This can prevent excessive power from being drawn from the grid, which could cause large fluctuations in grid voltage and lead to equipment failures on the grid side.

[0082] pass Limiting the overall supply and demand balance of the photovoltaic-storage-charging integrated system and imposing corresponding constraints on the active power of energy storage and the active power of the grid can regulate the safe operation boundary of the energy storage system and the grid. In turn, it can achieve the stable and safe operation of the photovoltaic-storage-charging integrated system and the grid, promote the full consumption of photovoltaic power, and maximize the self-consumption rate of photovoltaic power.

[0083] In some optional implementations, the total charging amount of the energy storage system during the predicted time period is less than the maximum total charging amount and the total discharging amount is less than the maximum total discharging amount, including: Step c1, based on , Make the total charge amount less than the maximum total charge amount.

[0084] Step c2, based on , To ensure that the total discharge is less than the maximum total discharge; where, This represents the charging power of the energy storage system at the predicted time point t. Used to represent the time interval between two predicted time points. Used to indicate the number of full charge and discharge cycles of the energy storage system within a predicted time period. Used to indicate the charging efficiency of an energy storage system. Used to characterize the battery capacity of energy storage systems SoH Used to indicate battery health. Used to represent the discharge power of the energy storage system at the predicted time point t. The value is used to represent the discharge efficiency of the energy storage system, and n represents the total number of prediction time points.

[0085] By limiting the total charge of the energy storage system's batteries within a predicted time period to be less than the maximum total charge, the number of times the batteries in the energy storage system can be fully charged within the predicted time period is limited. Similarly, by limiting the total discharge of the energy storage system's batteries within a predicted time period to be less than the maximum total discharge, the number of times the batteries in the energy storage system can be fully discharged within the predicted time period is limited. In this way, by limiting the number of times the batteries in the energy storage system can be fully charged and discharged, the service life of the energy storage system's batteries can be extended.

[0086] In some alternative implementations, the constraints also include: Step d1, If satisfied as well as Based on Determine the actual active power of photovoltaic power at the predicted time point t, and based on Determine the photovoltaic curtailment power at the predicted time point t; where, Used to represent the remaining battery charge at the predicted time point t. Used to indicate the maximum remaining battery capacity. Used to represent the predicted active power of photovoltaic power at prediction time t. Used to represent the predicted total load power at prediction time t. Used to represent the maximum charging power of the energy storage system at the predicted time point t. Used to represent the actual active power of photovoltaic power at the predicted time point t. Used to represent the photovoltaic curtailment power at the predicted time point t.

[0087] As mentioned above, restrictions have been imposed. And here are the restrictions Therefore, only when Only then will both of the above constraints be satisfied simultaneously, and This indicates that at the predicted time point t, the remaining battery capacity of the energy storage system has reached its maximum remaining capacity, meaning the battery is fully charged. At this point, through... It can accurately identify scenarios where the power generation of the photovoltaic system exceeds the sum of the load demand of the photovoltaic-storage-charging integrated system and the maximum charging power of the energy storage system, that is, identify scenarios where the photovoltaic system generates excess power.

[0088] Accordingly, through It can accurately determine the actual active power of a photovoltaic system, reducing unnecessary energy waste. Furthermore, through... It can accurately and reasonably determine the curtailment power of the photovoltaic system, avoiding the impact of excessive output of the photovoltaic system on the load of the photovoltaic-storage-charging integrated system, the energy storage system and the grid side.

[0089] In some alternative implementations, the constraints also include: Step e1, based on P_grid(t)≥0, enables the integrated photovoltaic-storage-charging system to draw power from the grid; where, Used to represent the active power of the power grid at the predicted time point t.

[0090] By setting P_grid(t)≥0, the photovoltaic-storage-charging integrated system can be restricted from supplying power to the grid, and can only draw power from the grid. This avoids risks such as grid voltage fluctuations and grid connection protection malfunctions caused by reverse power supply, and ensures the safety of the grid connection side and the grid.

[0091] Step S403: Based on the target energy storage active power and target grid active power at each predicted time point, control the integrated photovoltaic-storage-charging system. For details, please refer to [link to relevant documentation]. Figure 3 Step S303 of the illustrated embodiment will not be described again here.

[0092] In some alternative implementations, the method further includes: Step f1, based on Determine the remaining battery capacity of the energy storage system at the predicted time point t+1. Used to determine the target grid active power and target energy storage active power at the prediction time point t+1; where, Used to represent the remaining battery charge at the predicted time point t. Used to represent the remaining battery power at the predicted time point t+1. Used to represent the active power of energy storage at the predicted time point t. Used to represent the average charge and discharge efficiency of an energy storage system. Used to represent the time interval between two predicted time points. Used to characterize the battery capacity of energy storage systems.

[0093] By using the remaining battery power and target energy storage active power at prediction time t, the remaining battery power at prediction time t+1 can be accurately determined. Subsequently, the target grid active power and target energy storage active power at prediction time t+1 can be determined by using the remaining battery power at prediction time t+1. In this way, closed-loop prediction of the target grid active power and target energy storage active power at each prediction time within the prediction period can be achieved.

[0094] The control method for the integrated photovoltaic-storage-charging system provided in this embodiment can accurately characterize the overall operating cost of the integrated photovoltaic-storage-charging system from two dimensions: grid power extraction cost and energy storage operating cost. By constructing constraints from dimensions such as the overall supply and demand balance of the integrated photovoltaic-storage-charging system, the remaining battery power of the energy storage system, and the active power of the grid, the target grid active power and target energy storage active power at each predicted time point can be accurately determined. Furthermore, by controlling the integrated photovoltaic-storage-charging system based on the target grid active power and target energy storage active power at each predicted time point, the overall cost of the integrated photovoltaic-storage-charging system can be optimized.

[0095] As a specific application embodiment of the present invention, such as Figure 5 and Figure 6 As shown, the integrated photovoltaic-storage-charging control system can obtain the photovoltaic predicted active power of the photovoltaic system at each prediction time point, the predicted total load power of the integrated photovoltaic-storage-charging system at each prediction time point, and the grid extraction unit cost at each prediction time point, as output by the photovoltaic prediction model and output by the electricity price prediction model. The integrated photovoltaic-storage-charging control system obtains the mapping relationship between the total operating cost of the integrated photovoltaic-storage-charging system and the grid active power and energy storage active power. Then, based on the obtained photovoltaic predicted active power, predicted total load power, and grid extraction unit cost, the total operating cost is minimized to obtain the target grid active power, target energy storage active power, and actual active power of the photovoltaic system at each prediction time point. Furthermore, the grid connection point can be controlled based on the target grid active power, the photovoltaic system can be controlled based on the actual active power, and the energy storage system can be controlled based on the target energy storage active power.

[0096] This embodiment also provides a control device for an integrated photovoltaic, energy storage, and charging system. This device is used to implement the above embodiments and preferred embodiments, and details already described will not be repeated. As used below, the term "module" can refer to a combination of software and / or hardware that performs a predetermined function. Although the device described in the following embodiments is preferably implemented in software, hardware implementation, or a combination of software and hardware, is also possible and contemplated.

[0097] This embodiment provides a control device for an integrated photovoltaic, energy storage, and charging system, such as... Figure 7 As shown, it includes: The acquisition module 701 is used to acquire the mapping relationship between the total operating cost of the photovoltaic-storage-charging integrated system and the active power of the power grid and the active power of the energy storage during the predicted time period. The total operating cost is configured as the power grid extraction cost and the energy storage operating cost.

[0098] The processing module 702 is used to minimize the total operating cost under the constraints of the constraints, and obtain the target grid active power and target energy storage active power at each prediction time point in the prediction period. The constraints are configured as follows: the total output power of the photovoltaic-storage-charging integrated system is the same as the predicted total load power at each prediction time point; the remaining battery capacity of the energy storage system is less than or equal to the maximum remaining battery capacity and greater than or equal to the minimum remaining battery capacity at each prediction time point; the remaining battery capacity at the last prediction time point is greater than or equal to the remaining battery capacity threshold; and the total charging amount of the energy storage system during the prediction period is less than the maximum total charging amount and the total discharging amount is less than the maximum total discharging amount.

[0099] The control module 703 is used to control the photovoltaic-storage-charging integrated system based on the target energy storage active power and the target grid active power corresponding to each predicted time point.

[0100] In some alternative implementations, the construction apparatus for total operating cost includes: The first construction module is used to construct the grid power extraction cost based on the fusion of the grid active power and the grid power extraction unit cost within the predicted time period.

[0101] The second module is used to construct the energy storage operating cost based on the fusion of the active power of energy storage and the unit cost of energy storage operation within the predicted time period.

[0102] The third module is used to construct the total operating cost based on the integration of grid power extraction cost and energy storage operation cost.

[0103] In some optional implementations, the unit cost of energy storage operation is configured as the unit cost of battery degradation, the unit cost of model incentives, and the unit cost of power switching; the second building module is also used for... Construct a prediction of battery degradation costs over a given time period. Used to represent the cost of battery degradation. Used to represent the active power of energy storage at the predicted time point t. Used to represent the unit cost of battery degradation, T is used to represent the last prediction time point; based on Construct the model incentive cost within the prediction period. Used to represent the model incentive cost Used to represent the model incentive unit cost at the predicted time point t; based on Construct the power switching cost within the predicted time period. Used to represent power switching costs The unit cost of power switching is used to represent the energy storage operating cost, which is configured as battery degradation cost, model incentive cost, and power switching cost.

[0104] In some alternative implementations, the processing module 702 is further used for based on This ensures that the total output power at the predicted time point t is the same as the predicted total load power; where, Used to represent the predicted total load power at prediction time point t. Used to represent the predicted active power of photovoltaic power at prediction time t. Used to represent the active power of energy storage at the predicted time point t. Used to represent the active power of the power grid at the predicted time point t; where... Subject to , Subject to ;in, Used to indicate the maximum discharge power of an energy storage system Used to indicate the maximum discharge power of an energy storage system Used to represent the maximum active power of the power grid.

[0105] In some alternative implementations, the processing module 702 is further used for based on , Make the total charge amount less than the maximum total charge amount; based on , To ensure that the total discharge is less than the maximum total discharge; where, This represents the charging power of the energy storage system at the predicted time point t. Used to represent the time interval between two predicted time points. Used to indicate the number of full charge and discharge cycles of the energy storage system within a predicted time period. Used to indicate the charging efficiency of an energy storage system. Used to characterize the battery capacity of energy storage systems SoH Used to indicate battery health. Used to represent the discharge power of the energy storage system at the predicted time point t. Used to indicate the discharge efficiency of an energy storage system.

[0106] In some alternative implementations, the processing module 702 is further used for If satisfied as well as Based on Determine the actual active power of photovoltaic power at the predicted time point t, and, Determine the photovoltaic curtailment power at the predicted time point t; and / or, based on This allows the integrated photovoltaic, energy storage, and charging system to draw power from the grid; among which, Used to represent the remaining battery charge at the predicted time point t. Used to indicate the maximum remaining battery capacity. Used to represent the predicted active power of photovoltaic power at prediction time t. Used to represent the predicted total load power at prediction time t. Used to represent the maximum charging power of the energy storage system at the predicted time point t. Used to represent the actual active power of photovoltaic power at the predicted time point t. Used to represent the photovoltaic curtailment power at the predicted time point t. Used to represent the active power of the power grid at the predicted time point t.

[0107] In some alternative embodiments, the device further includes: Determine module, used for based on Determine the remaining battery capacity of the energy storage system at the predicted time point t+1. Used to determine the target grid active power and target energy storage active power at the prediction time point t+1; where, Used to represent the remaining battery charge at the predicted time point t. Used to represent the remaining battery power at the predicted time point t+1. Used to represent the active power of energy storage at the predicted time point t. Used to represent the average charge and discharge efficiency of an energy storage system. Used to represent the time interval between two predicted time points. Used to characterize the battery capacity of energy storage systems.

[0108] The control device for the integrated photovoltaic-storage-charging system provided in this embodiment of the invention can execute the control method for the integrated photovoltaic-storage-charging system provided in any embodiment of the invention, and has the corresponding functional modules and beneficial effects for executing the method. Further functional descriptions of the above modules and units are the same as those in the corresponding embodiments described above, and will not be repeated here.

[0109] Figure 8 This is a schematic diagram of the structure of an electronic device provided in an embodiment of the present invention.

[0110] The following is a detailed reference. Figure 8This diagram illustrates a suitable structural schematic for implementing an electronic device according to embodiments of the present invention. The electronic device may include a processor (e.g., a central processing unit, graphics processor, etc.) 801, which can perform various appropriate actions and processes based on a program stored in read-only memory (ROM) 802 or a program loaded from memory 808 into random access memory (RAM) 803. The RAM 803 also stores various programs and data required for the operation of the electronic device. The processor 801, ROM 802, and RAM 803 are interconnected via a bus 804. An input / output (I / O) interface 805 is also connected to the bus 804.

[0111] Typically, the following devices can be connected to I / O interface 805: input devices 806 including, for example, touchscreens, touchpads, keyboards, mice, cameras, microphones, accelerometers, gyroscopes, etc.; output devices 807 including, for example, liquid crystal displays (LCDs), speakers, vibrators, etc.; memory devices 808 including, for example, magnetic tapes, hard disks, etc.; and communication devices 809. Communication device 809 allows electronic devices to communicate wirelessly or wiredly with other devices to exchange data. Although Figure 8 Electronic devices with various devices are shown, but it should be understood that it is not required to implement or have all of the devices shown, and more or fewer devices may be implemented or have instead.

[0112] In particular, according to embodiments of the present invention, the processes described above with reference to the flowcharts can be implemented as computer software programs. For example, embodiments of the present invention include a computer program product comprising a computer program carried on a non-transitory computer-readable medium, the computer program containing program code for performing the methods shown in the flowcharts. In such embodiments, the computer program can be downloaded and installed from a network via a communication device 809, or installed from a memory 808, or installed from a ROM 802. When the computer program is executed by the processor 801, it performs the functions defined in the control method of the integrated optical storage and charging system of the embodiments of the present invention.

[0113] Figure 8 The electronic device shown is merely an example and should not be construed as limiting the functionality and scope of use of the embodiments of the present invention.

[0114] This invention also provides a computer-readable storage medium. The methods described above according to embodiments of the invention can be implemented in hardware or firmware, or implemented as computer code that can be recorded on a storage medium, or implemented as computer code downloaded via a network and originally stored on a remote storage medium or a non-transitory machine-readable storage medium and then stored on a local storage medium. Thus, the methods described herein can be processed by software stored on a storage medium using a general-purpose computer, a dedicated processor, or programmable or dedicated hardware. The storage medium can be a magnetic disk, optical disk, read-only memory, random access memory, flash memory, hard disk, or solid-state drive, etc.; further, the storage medium can also include combinations of the above types of memory. It is understood that computers, processors, microprocessor controllers, or programmable hardware include storage components capable of storing or receiving software or computer code. When the software or computer code is accessed and executed by the computer, processor, or hardware, the control method of the integrated optical storage and charging system shown in the above embodiments is implemented.

[0115] A portion of this invention can be applied as a computer program product, such as computer program instructions, which, when executed by a computer, can invoke or provide the methods and / or technical solutions according to the invention through the operation of the computer. Those skilled in the art will understand that the forms in which computer program instructions exist in a computer-readable medium include, but are not limited to, source files, executable files, installation package files, etc. Correspondingly, the ways in which computer program instructions are executed by a computer include, but are not limited to: the computer directly executing the instructions, or the computer compiling the instructions and then executing the corresponding compiled program, or the computer reading and executing the instructions, or the computer reading and installing the instructions and then executing the corresponding installed program. Here, the computer-readable medium can be any available computer-readable storage medium or communication medium accessible to a computer.

[0116] Although embodiments of the invention have been described in conjunction with the accompanying drawings, those skilled in the art can make various modifications and variations without departing from the spirit and scope of the invention, and such modifications and variations all fall within the scope defined by the appended claims.

Claims

1. A control method for an integrated photovoltaic, energy storage, and charging system, characterized in that, The method includes: Obtain the mapping relationship between the total operating cost of the photovoltaic-storage-charging integrated system and the active power of the grid and the active power of the energy storage during the predicted time period. The total operating cost is configured as the grid power extraction cost and the energy storage operating cost. The total operating cost is minimized under the constraints to obtain the target grid active power and target energy storage active power at each prediction time point in the prediction period. The photovoltaic-storage-charging integrated system is controlled based on the target energy storage active power and the target power grid active power corresponding to each of the predicted time points. The constraints are configured such that the total output power of the photovoltaic-storage-charging integrated system is the same as the predicted total load power at each of the predicted time points; the remaining battery capacity of the energy storage system is less than or equal to the maximum remaining battery capacity and greater than or equal to the minimum remaining battery capacity at each of the predicted time points; the remaining battery capacity at the last predicted time point is greater than or equal to the remaining battery capacity threshold; and the total charging amount of the energy storage system during the predicted time period is less than the maximum total charging amount and the total discharging amount is less than the maximum total discharging amount.

2. The method according to claim 1, characterized in that, The process of constructing the total operating cost includes: The power grid extraction cost is constructed based on the fusion of the active power of the power grid and the unit cost of power grid extraction during the predicted time period. The energy storage operating cost is constructed based on the fusion of the energy storage active power and the energy storage operating unit cost within the predicted time period. The total operating cost is constructed by integrating the grid power extraction cost and the energy storage operation cost.

3. The method according to claim 2, characterized in that, The unit cost of energy storage operation is configured as the unit cost of battery degradation, the unit cost of model incentive, and the unit cost of power switching; the construction of the energy storage operation cost based on the fusion of the energy storage active power and the unit cost of energy storage operation within the prediction time period includes: based on Construct the battery degradation cost within the predicted time period. Used to represent the battery degradation cost. Used to represent the active power of energy storage at the predicted time point t. The unit cost of battery degradation is used to represent the cost of the battery degradation, and T is used to represent the last predicted time point; based on Construct the model incentive cost for the predicted time period. Used to represent the incentive cost of the model. The model incentive unit cost is used to represent the prediction time point t. based on Construct the power switching cost within the predicted time period. Used to represent the power switching cost The energy storage operating cost is configured to represent the unit cost of power switching, which includes the battery degradation cost, the model incentive cost, and the power switching cost.

4. The method according to claim 1, characterized in that, The statement that the total output power of the integrated photovoltaic-storage-charging system is the same as the predicted total load power at each of the predicted time points includes: based on This ensures that the total output power at the predicted time point t is the same as the predicted total load power. in, The predicted total load power used to represent the predicted time point t. Used to represent the predicted active power of photovoltaic power at prediction time t. The energy storage active power is used to represent the energy storage active power at the predicted time point t. The active power of the power grid is used to represent the predicted time point t; in, Subject to , Subject to ; in, Used to represent the maximum discharge power of the energy storage system. Used to indicate the maximum charging power of the energy storage system. Used to represent the maximum active power of the power grid.

5. The method according to claim 1, characterized in that, The total charging amount of the energy storage system during the predicted time period is less than the maximum total charging amount and the total discharging amount is less than the maximum total discharging amount, including: based on ， Make the total charging amount less than the maximum total charging amount; based on ， Make the total discharge amount less than the maximum total discharge amount; in, This represents the charging power of the energy storage system at the predicted time point t. Used to represent the time interval between two predicted time points. This is used to represent the number of full-charge and discharge cycles of the energy storage system within the predicted time period. Used to represent the charging efficiency of the energy storage system. Used to characterize the battery capacity of the energy storage system SoH Used to indicate battery health. The discharge power of the energy storage system at the predicted time point t is used to represent the discharge power of the energy storage system. The value n represents the discharge efficiency of the energy storage system, and n represents the total number of predicted time points.

6. The method according to any one of claims 1 to 5, characterized in that, The constraints also include: If satisfied as well as Based on Determine the actual active power of photovoltaic power at the predicted time point t, and based on Determine the amount of solar power curtailed at the predicted time point t; And / or, based on This allows the integrated photovoltaic, energy storage, and charging system to draw power from the power grid. in, The remaining battery charge at the predicted time point t is used to represent the remaining battery charge. Used to indicate the maximum remaining battery capacity. Used to represent the predicted active power of photovoltaic power at prediction time t. The predicted total load power is used to represent the predicted time point t. This is used to represent the maximum charging power of the energy storage system at the predicted time point t. The actual active power of the photovoltaic system used to represent the predicted time point t. The photovoltaic curtailment power used to represent the predicted time point t. The active power of the power grid is used to represent the predicted time point t.

7. The method according to any one of claims 1 to 5, characterized in that, The method further includes: based on Determine the remaining battery capacity of the energy storage system at the predicted time point t+1. Used to determine the target grid active power and target energy storage active power at the t+1 prediction time point; in, The remaining battery charge at the predicted time point t is used to represent the remaining battery charge. The remaining battery charge is used to represent the remaining battery charge at the predicted time point t+1. The energy storage active power is used to represent the energy storage active power at the predicted time point t. Used to represent the average charge and discharge efficiency of the energy storage system. Used to represent the time interval between two predicted time points. Used to characterize the battery capacity of the energy storage system.

8. A control device for an integrated photovoltaic, energy storage, and charging system, characterized in that, The device includes: The acquisition module is used to acquire the mapping relationship between the total operating cost of the photovoltaic-storage-charging integrated system and the active power of the power grid and the active power of energy storage within the predicted time period. The total operating cost is configured as the power grid extraction cost and the energy storage operating cost. The processing module is used to minimize the total operating cost under the constraints of the constraints, and to obtain the target grid active power and target energy storage active power at each prediction time point in the prediction time period. The control module is used to control the photovoltaic-storage-charging integrated system based on the target energy storage active power and the target grid active power corresponding to each of the predicted time points; The constraints are configured such that the total output power of the photovoltaic-storage-charging integrated system is the same as the predicted total load power at each of the predicted time points; the remaining battery capacity of the energy storage system is less than or equal to the maximum remaining battery capacity and greater than or equal to the minimum remaining battery capacity at each of the predicted time points; the remaining battery capacity at the last predicted time point is greater than or equal to the remaining battery capacity threshold; and the total charging amount of the energy storage system during the predicted time period is less than the maximum total charging amount and the total discharging amount is less than the maximum total discharging amount.

9. An electronic device, characterized in that, include: The system includes a memory and a processor, which are interconnected. The memory stores computer instructions, and the processor executes the computer instructions to perform the control method of the integrated optical storage and charging system according to any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores computer instructions for causing the computer to execute the control method of the integrated photovoltaic storage and charging system according to any one of claims 1 to 7.

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