Charging and discharging control method and device of energy storage system, electronic equipment and storage medium

Abstract

The invention provides a charging and discharging control method and device for an energy storage system, electronic equipment and a storage medium, and relates to the technical field of electric energy storage, and the method comprises the steps: determining a control objective function based on a future predicted power load, a future predicted electricity price and operation cost; determining a charge-discharge power constraint condition and a charge state constraint condition; the charge state constraint condition comprises an adjustment parameter, and the adjustment parameter is used for adjusting the charge state value so as to reduce the change speed of the charge state value; and performing charge and discharge control on the energy storage system according to the control objective function, the charge and discharge power constraint condition and the charge state constraint condition. In the embodiment of the invention, charging and discharging control is performed on the energy storage system according to the control objective function, the charging and discharging power constraint condition and the state-of-charge constraint condition, and the state-of-charge value is adjusted through the adjustment parameter in the state-of-charge constraint condition, so that the change speed of the state-of-charge value is reduced; the problem of incomplete charging and discharging of the energy storage system is avoided to a certain extent, and earnings are increased.

Description

Technical Field

[0001] The present application relates to the field of electric energy storage technology, and in particular to a charge and discharge control method, device, electronic device, and storage medium for an energy storage system. Background Art

[0002] With the development of new power systems, energy storage systems are widely used in all aspects of power generation, transmission, and consumption. Most load-side users use energy storage charging and discharging control strategies to reduce peak loads and fill valleys based on fixed time-of-use electricity prices, thereby reducing electricity costs.

[0003] Currently, charging and discharging are controlled based on a fixed charging and discharging strategy, i.e., charging and discharging at a fixed power during fixed periods. However, due to fluctuations in charging and discharging efficiency caused by user load fluctuations, operating conditions changes, and energy storage losses, the energy storage system cannot fully complete charging and discharging, resulting in insufficient benefits. Summary of the Invention

[0004] The embodiments of the present application provide a charge and discharge control method, device, electronic device, and storage medium for an energy storage system to solve the problem that the energy storage system cannot fully complete charge and discharge, resulting in insufficient benefits.

[0005] In a first aspect, an embodiment of the present application provides a method for controlling charging and discharging of an energy storage system, the method comprising: obtaining a future predicted power load, a future predicted electricity price, and an operating cost of the energy storage system; determining a control objective function based on the future predicted power load, the future predicted electricity price, and the operating cost; determining a charging and discharging power constraint and a state of charge constraint; the state of charge constraint comprising an adjustment parameter, the adjustment parameter being used to adjust the state of charge value to reduce the rate of change of the state of charge value; and controlling charging and discharging of the energy storage system according to the control objective function, the charging and discharging power constraint, and the state of charge constraint.

[0006] In a second aspect, an embodiment of the present application provides a charge and discharge control device for an energy storage system, the device comprising: an acquisition module for acquiring future predicted power load, future predicted electricity price and operating cost of the energy storage system; a first determination module for determining a control objective function based on the future predicted power load, future predicted electricity price and operating cost; a second determination module for determining a charge and discharge power constraint and a state of charge constraint; the state of charge constraint comprises an adjustment parameter, the adjustment parameter being used to adjust the state of charge value to reduce the rate of change of the state of charge value; and a control module for controlling the charge and discharge of the energy storage system according to the control objective function, the charge and discharge power constraint and the state of charge constraint.

[0007] In a third aspect, an embodiment of the present application provides an electronic device, comprising a memory, a processor, and a computer program stored in the memory, wherein the processor implements any of the above methods when executing the computer program.

[0008] In a fourth aspect, an embodiment of the present application provides a computer-readable storage medium, in which a computer program is stored. When the computer program is executed by a processor, any of the above methods is implemented.

[0009] In a fifth aspect, an embodiment of the present application provides a computer program product, which includes a computer program, and when the computer program is executed by a processor, it implements any of the above methods.

[0010] Compared with the prior art, this application has the following advantages:

[0011] The present application provides a method, device, electronic device and storage medium for charge and discharge control of an energy storage system. First, the future predicted power load, the future predicted electricity price and the operating cost of the energy storage system are obtained; then, based on the future predicted power load, the future predicted electricity price and the operating cost, a control objective function is determined; the charge and discharge power constraint and the state of charge constraint are determined; the state of charge constraint includes an adjustment parameter, and the adjustment parameter is used to adjust the state of charge value to reduce the rate of change of the state of charge value; finally, the energy storage system is charged and discharged according to the control objective function, the charge and discharge power constraint and the state of charge constraint. In an embodiment of the present application, the energy storage system is charged and discharged according to the control objective function, the charge and discharge power constraint and the state of charge constraint, and the state of charge value is adjusted by the adjustment parameter in the state of charge constraint to reduce the rate of change of the state of charge value, thereby avoiding the problem of incomplete charge and discharge of the energy storage system to a certain extent and increasing revenue.

[0012] The above description is only an overview of the technical solution of this application. In order to more clearly understand the technical means of this application, it can be implemented in accordance with the contents of the specification. In order to make the above and other purposes, features and advantages of this application more obvious and easy to understand, the specific implementation methods of this application are listed below. BRIEF DESCRIPTION OF THE DRAWINGS

[0013] In the accompanying drawings, unless otherwise specified, the same reference numerals throughout the multiple drawings represent the same or similar components or elements. These drawings are not necessarily drawn to scale. It should be understood that these drawings only depict some embodiments according to the present application and should not be regarded as limiting the scope of the present application.

[0014] Figure 1 This is a flowchart of an application scenario of the charge and discharge control method for the energy storage system provided in this application.

[0015] Figure 2 This is a schematic diagram of the changes in energy storage SOC and energy storage power over time according to an embodiment of the present application.

[0016] Figure 3 This is a schematic diagram of the energy storage SOC and energy storage power changing with time according to an embodiment of the present application.

[0017] Figure 4 This is a flow chart of a charge and discharge control method for an energy storage system according to an embodiment of the present application.

[0018] Figure 5 This is a structural block diagram of a charge and discharge control device for an energy storage system according to an embodiment of the present application.

[0019] Figure 6 A block diagram of an electronic device used to implement an embodiment of the present application. DETAILED DESCRIPTION

[0020] Hereinafter, only certain exemplary embodiments are briefly described. As will be appreciated by those skilled in the art, the described embodiments may be modified in various ways without departing from the spirit or scope of the present application. Therefore, the drawings and description are to be regarded as illustrative in nature and not restrictive.

[0021] To facilitate understanding of the technical solutions of the embodiments of the present application, the following describes the related technologies of the embodiments of the present application. The following related technologies can be combined with the technical solutions of the embodiments of the present application as optional solutions, and all of them fall within the scope of protection of the embodiments of the present application.

[0022] It should be noted that the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data used for analysis, stored data, displayed data, etc.) involved in this application are all information and data authorized by the user or fully authorized by all parties, and the collection, use and processing of relevant data must comply with the relevant laws, regulations and standards of relevant countries and regions, and provide corresponding operation entrances for users to choose to authorize or refuse.

[0023] Figure 1 This is a flow chart of an application scenario of the method for controlling the charge and discharge of an energy storage system provided in this application. In this embodiment, the energy storage system includes an energy storage battery, and the charge and discharge control of the energy storage system includes controlling the charging power or discharging power of the energy storage battery. Figure 1 As shown, this embodiment includes the following steps:

[0024] Step S101: Obtain future predicted power load.

[0025] For example, obtaining the predicted power load of a user, park, or factory for a specific day in the future, and the power load curve, will directly influence the charge and discharge control strategy of the energy storage system. Power load refers to the total power drawn from the power system by electrical equipment at a specific moment.

[0026] Optionally, historically measured power load and weather forecast information are obtained and input into a power load forecasting model, which then outputs a predicted future power load. The power load forecasting model can be a pre-trained machine learning model, a deep learning model, or the like. Because power load is temperature-dependent, for example, high air conditioning usage in the summer leads to higher power load. Therefore, weather factors are taken into account when forecasting future power load.

[0027] Step S102: Obtain the future predicted electricity price.

[0028] For example, obtain the predicted electricity price for a user, park, or factory on a certain day in the future.

[0029] Future electricity price forecasts include two scenarios: fixed and floating. In the fixed-price scenario, the electricity price remains unchanged, and the future price is the current price. In the floating-price scenario, the varying prices of electricity over time directly impact the energy storage system's charge and discharge control strategy. Historical electricity prices and price adjustment information published by the power market are collected and input into the price forecast model, which then outputs the predicted future price. This model can be a pre-trained machine learning model, a deep learning model, or other similar model.

[0030] Step S103: Obtain static parameters of the energy storage system.

[0031] Among them, static parameters characterize the inherent properties of the energy storage system. The values of static parameters can be obtained from the factory instructions of the energy storage batteries of the energy storage system. Static parameters include but are not limited to: charging or discharging efficiency of the energy storage system, capacity of the energy storage system, number of energy storage design cycles, etc.

[0032] Step S104: Acquire the operating boundary parameters of the energy storage system.

[0033] Based on the specific requirements of users, parks, or factories for the use of energy storage systems, obtain the pre-configured operating boundary parameters of the energy storage system. The operating boundary parameters include the boundary values of the energy storage system for charging or discharging. The operating boundary parameters of the energy storage system include but are not limited to: the maximum or minimum charging power of the energy storage system, the maximum or minimum discharging power of the energy storage system, the maximum or minimum daily charging times, the maximum or minimum daily discharging times, the maximum or minimum mains load, etc.

[0034] Step S105: constructing a control strategy optimization model for the energy storage system.

[0035] The control strategy optimization model includes a control objective function and constraints. The control objective function is determined based on the future predicted electricity load, future predicted electricity price, and operating costs. Constraints include charge and discharge power constraints and state of charge constraints. The charge and discharge power constraints are determined based on the operating boundary parameters; the state of charge constraints are determined based on the static parameters, operating boundary parameters, and adjustment parameters. The state of charge (SOC) is the ratio of the current capacity of the battery to the rated capacity, and its value range is 0 to 1. When SOC = 0, the battery is fully discharged, and when SOC = 1, the battery is fully charged.

[0036] In this embodiment, the control objective function is as follows:

[0037]

[0038] The control objective of the control objective function is to minimize the electricity charges paid by the user within the period T. T represents the period of optimal scheduling; P load (t) represents the predicted power load at time t; P ch (t) represents the charging power at time t; P dis (t) represents the discharge power at time t; Δt represents the time interval, for example, it can be 15 minutes or 1 hour; C(t) represents the predicted electricity price at time t; f(t) cost represents the operating cost of the energy storage system at time t.

[0039] f(t) cost =a(t)+K(t)·(P ch (t)+P dis (t)) (2)

[0040] Here, a(t) represents the fixed operating cost of the energy storage system at time t, such as the loss from charge and discharge cycles. K(t) represents the time penalty coefficient at time t, i.e., the dynamic operating cost, which is proportional to time. K(t) = k*t, where k is a positive number. Within the same electricity usage period, the later the energy storage system starts charging or discharging, the higher the dynamic operating cost. The price per kilowatt-hour remains the same at different times within the same electricity usage period.

[0041] The introduction of dynamic operating costs aims to ensure early profit generation when multiple optimal solutions exist. For example, if the peak electricity price remains the same from 1:00 PM to 5:00 PM, the energy storage system will generate the same profit using Strategy 1 (discharging between 1:00 PM and 3:00 PM) and Strategy 2 (discharging between 3:00 PM and 5:00 PM), corresponding to the optimal strategy. However, actual production processes often involve significant production uncertainty. If the energy storage system decides to discharge between 3:00 PM and 5:00 PM, and a fault or special situation occurs at the factory at 3:30 PM, the energy storage system may not be able to discharge normally at 3:30 PM as planned, resulting in a loss of profit. On the other hand, if the energy storage system discharges between 1:00 PM and 3:00 PM, even if an emergency situation causes the current discharge to be terminated, there is still room for continued discharge with the same profit margin, reducing the risk of future abnormalities and thus ensuring profit.

[0042] The charge and discharge power constraints are as follows:

[0043] P dis,min ≤P dis (t)≤P dis,max (3)

[0044] P ch,min ≤P ch (t)≤P ch,max (4)

[0045] P dis (t)*P ch (t)=0 (5)

[0046] Among them, P dis,min Indicates the minimum discharge power of the energy storage system; P dis,max Indicates the maximum discharge power of the energy storage system; P ch,min Indicates the minimum charging power of the energy storage system; P ch,max represents the maximum charging power of the energy storage system; formula (5) represents the charging or discharging of the energy storage system at the same time t.

[0047] In one example, the state of charge constraints are as follows:

[0048]

[0049] S min ≤S(t)≤S max (7)

[0050] Where S(t) represents the SOC value at time t; t = 1, 2, ..., T; δ represents the self-discharge rate of the energy storage system; η c Indicates charging efficiency; η d Indicates discharge efficiency; E max Indicates the current maximum capacity of the energy storage system, in kWh or MWh; S minIndicates the minimum value of SOC, which can be 0 or greater than 0; S max Indicates the maximum value of SOC, which can be 1 or less than 1.

[0051] The control strategy optimization model constructed by formulas (1)-(7) is used for calculation. The change process of SOC value and energy storage power (charging power in this embodiment) over time is as follows: Figure 2 As shown, Figure 2 The vertical axis on the left (vertical axis values are 0, 0.1...1) represents the SOC value, the vertical axis on the right (vertical axis values are -2500, -2000...0) represents the charging power, and the horizontal axis represents time. It should be noted that the charging power and discharging power output by the control strategy optimization model are both positive numbers. In order to meet the display needs, Figure 2 The charging power output of the control strategy optimization model is multiplied by -1 to display it as a negative number. The energy storage system can be fully charged at 2000 kW between 0:00 and 2:30, and the corresponding SOC value reaches its upper limit. However, in reality, between 0:00 and 2:30, due to voltage fluctuations and battery aging, parameters such as charging efficiency, discharge efficiency, and current maximum capacity fluctuate and change. As a result, the battery is not fully charged after charging at 2:30 according to the 2000 kW charging plan. During the off-peak electricity price period from 2:30 to 4:00, the battery is not charged, wasting charging space and reducing energy storage benefits.

[0052] Based on this, the introduction of an adjustment coefficient into the SOC constraint condition and the combination of the energy storage system's own protection mechanism can make the optimal energy storage strategy more robust against fluctuations in some parameters. The improved SOC constraint condition is as follows:

[0053]

[0054] S min ≤S′(t)≤S max (9)

[0055] Wherein, S′(t) represents the SOC value at time t; R(t) represents the adjustment coefficient at time t, which can be set according to specific needs and can range from 0 to 1.

[0056] By introducing the adjustment coefficient, the state of charge value is adjusted to reduce the speed of change of the state of charge value, that is, when charging, P ch (t)·R(t) will become smaller, which will slow down the growth of SOC value during charging and tend to charge more. When discharging, P dis (t)·R(t) will become smaller, which will slow down the decrease of SOC value during discharge and tend to discharge more electricity.

[0057] The energy storage system can continue to charge or discharge if there is suitable charging or discharging space in the future, such as Figure 3 As shown, charging can continue between 2:30 and 3:15 (as shown in Figure 3 ), thereby increasing revenue and avoiding revenue loss due to fluctuations in operating conditions, voltage, or efficiency.

[0058] Step S106: Determine the energy storage charging and discharging control strategy.

[0059] According to the control strategy optimization model obtained by formulas (1)-(5), (8) and (9), the charging time, charging power, discharging time, discharging power and SOC value of the energy storage system at multiple times are determined.

[0060] Step S107: using the energy storage protection mechanism to perform overcharge and overdischarge protection.

[0061] The energy storage protection mechanism includes overcharge protection and over-discharge protection. Overcharge protection: If the SOC value reaches the first preset threshold, that is, the maximum SOC value, the charging instruction is stopped or the charging power is set to zero. Over-discharge protection: If the SOC value reaches the second preset threshold, that is, the minimum SOC value, the discharge instruction is stopped or the discharge power is set to zero.

[0062] Step S108: determining the actual charging and discharging power of the energy storage.

[0063] If the SOC value is between the maximum and minimum values, the charge and discharge power output by the control strategy optimization model is used as the actual charge and discharge power for charging and discharging.

[0064] This embodiment optimizes the energy storage system model and introduces an adjustment coefficient to avoid incomplete charging or discharging. Dynamic operating costs are also introduced to automatically determine the strategy that maximizes returns in scenarios where multiple theoretically optimal strategies exist, thereby mitigating future profit risks. Based on the adjustment coefficient and dynamic operating costs, the energy storage system's charge and discharge control strategy is more robust and resistant to interference.

[0065] The embodiment of the present application provides a method for controlling the charge and discharge of an energy storage system. The method in this embodiment can be applied to a computing device, which may include a server, a user terminal, etc. Figure 4 FIG. 1 is a flow chart of a method for controlling charge and discharge of an energy storage system according to an embodiment of the present application, including:

[0066] Step S401: Obtain the future predicted electricity load, the future predicted electricity price, and the operating cost of the energy storage system.

[0067] Step S402: determining a control objective function based on the future predicted electricity load, the future predicted electricity price and the operating cost.

[0068] Step S403 , determining the charge and discharge power constraint conditions and the state of charge constraint conditions; the state of charge constraint conditions include adjustment parameters, and the adjustment parameters are used to adjust the state of charge value to reduce the change rate of the state of charge value.

[0069] Step S404 , controlling the charge and discharge of the energy storage system according to the control objective function, the charge and discharge power constraints, and the state of charge constraints.

[0070] Electricity load refers to the total amount of power consumed by electrical equipment in the power system at a given moment. Prediction models can be used to obtain forecasted future electricity load and electricity prices. For example, they can be used to obtain forecasted electricity load and electricity prices for a user, park, or factory for a specific day in the future.

[0071] The state of charge (SOC) is the ratio of the current capacity of the battery to the rated capacity, and its value range is 0 to 1. When SOC=0, it means that the battery is fully discharged, and when SOC=1, it means that the battery is fully charged.

[0072] The SOC constraint includes an adjustment coefficient, which is used to adjust the SOC value to reduce the rate of change of the SOC value. This allows the energy storage system to continue charging or discharging if there is still suitable charging or discharging space in the future, thereby increasing revenue and avoiding revenue losses caused by operating conditions, voltage or efficiency fluctuations.

[0073] The charge and discharge power constraints include charging power constraints and discharging power constraints. Based on the control objective function, the charge and discharge power constraints, and the state of charge constraints, a control strategy optimization model for the energy storage system is constructed. This control strategy optimization model is then used to control the charge and discharge of the energy storage system.

[0074] The charge and discharge control method of the energy storage system provided in the embodiment of the present application first obtains the future predicted power load, the future predicted electricity price and the operating cost of the energy storage system; then, based on the future predicted power load, the future predicted electricity price and the operating cost, determines the control objective function; determines the charge and discharge power constraint condition and the state of charge constraint condition; the state of charge constraint condition includes an adjustment parameter, and the adjustment parameter is used to adjust the state of charge value to reduce the rate of change of the state of charge value; finally, the energy storage system is charged and discharged according to the control objective function, the charge and discharge power constraint condition and the state of charge constraint condition. In the embodiment of the present application, the energy storage system is charged and discharged according to the control objective function, the charge and discharge power constraint condition and the state of charge constraint condition, and the state of charge value is adjusted by the adjustment parameter in the state of charge constraint condition to reduce the rate of change of the state of charge value, thereby avoiding the problem of incomplete charge and discharge of the energy storage system to a certain extent and increasing the profit.

[0075] In one implementation, the control objective of the control objective function includes minimizing the operating cost of the energy storage system; the operating cost of the energy storage system includes the operating cost; the operating cost includes a fixed operating cost and a dynamic operating cost. In the same electricity consumption period, the later the energy storage system starts charging or discharging, the higher the dynamic operating cost.

[0076] Fixed operating costs can be the depreciation cost of the energy storage system's batteries, such as the loss from charge and discharge cycles. Dynamic operating costs change dynamically; during the same electricity usage period, the later the energy storage system starts charging or discharging, the higher the dynamic operating cost.

[0077] In this embodiment, dynamic operating costs are introduced to ensure that profits can be obtained as early as possible when there are multiple optimal solutions. For example, if the peak electricity price is the same from 13:00 to 17:00 in the afternoon, the energy storage system will obtain the same profit under Strategy 1 (discharging from 13:00 to 15:00) and Strategy 2 (discharging from 15:00 to 17:00), and both correspond to the optimal strategy. However, the actual production process is often accompanied by large production uncertainties. If the energy storage system decides to discharge from 15:00 to 17:00, and the factory encounters individual faults or special circumstances at 15:30, the energy storage system will not be able to discharge normally at 15:30 as planned, resulting in loss of profit. On the other hand, if the energy storage system discharges from 13:00 to 15:00, even if some unexpected circumstances cause the current discharge to be terminated, there is still room for continued discharge with the same profit, reducing the risk of future abnormalities and thus ensuring profit.

[0078] In one implementation, determining the charge and discharge power constraints and the state of charge constraints includes: obtaining static parameters and operating boundary parameters of the energy storage system; the static parameters characterize inherent properties of the energy storage system; the operating boundary parameters include boundary values for charging or discharging the energy storage system; determining the charge and discharge power constraints based on the operating boundary parameters; and determining the state of charge constraints based on the static parameters, the operating boundary parameters, and the adjustment parameters.

[0079] Among them, static parameters characterize the inherent properties of the energy storage system. The values of static parameters can be obtained from the factory instructions of the energy storage batteries of the energy storage system. Static parameters include but are not limited to: charging or discharging efficiency of the energy storage system, capacity of the energy storage system, number of energy storage design cycles, etc.

[0080] The operating boundary parameters include the boundary values for charging or discharging the energy storage system. The pre-configured operating boundary parameters of the energy storage system can be obtained based on the specific requirements of the user, park or factory for the use of the energy storage system. The operating boundary parameters include but are not limited to: the maximum or minimum charging power of the energy storage system, the maximum or minimum discharging power of the energy storage system, the maximum or minimum daily charging times, the maximum or minimum daily discharging times, the maximum or minimum mains load, etc.

[0081] In one implementation, the energy storage system is charged and discharged according to a control objective function, a charge and discharge power constraint, and a state of charge constraint. This includes determining a charge time, a charge power, a discharge time, a discharge power, and a state of charge value of the energy storage system according to the control objective function, the charge and discharge power constraint, and the state of charge constraint.

[0082] According to the control objective function, charging and discharging power constraints and state of charge constraints, a mixed integer linear programming model is obtained as the control strategy optimization model, which outputs the charging time, charging power, discharging time, discharging power and state of charge value of the energy storage system at each charging moment or discharging moment.

[0083] In one implementation, the charge and discharge control method of the energy storage system further includes: if the state of charge value reaches a first preset threshold, stopping the execution of the charging instruction, or determining the charging power to be zero; if the state of charge value reaches a second preset threshold, stopping the execution of the discharging instruction, or determining the discharging power to be zero; wherein the first preset threshold is greater than the second preset threshold.

[0084] The energy storage protection mechanism is used to protect against overcharge and overdischarge. This mechanism includes overcharge protection and overdischarge protection. Overcharge protection: If the SOC value reaches the first preset threshold, that is, the maximum SOC value, the charging instruction is stopped or the charging power is set to zero. Overdischarge protection: If the SOC value reaches the second preset threshold, that is, the minimum SOC value, the discharge instruction is stopped or the discharge power is set to zero.

[0085] In one implementation, obtaining the future predicted electricity load includes: obtaining historical measured electricity load and weather forecast information; inputting the historical measured electricity load and weather forecast information into an electricity load prediction model, and using the electricity load prediction model to output the future predicted electricity load.

[0086] For example, obtaining the predicted electricity load of users, parks or factories on a certain day in the future, the electricity load curve will directly affect the charging and discharging control strategy of the energy storage system.

[0087] The electricity load forecasting model can be a pre-trained machine learning model, deep learning model, etc. Since electricity load is related to temperature, for example, when the temperature is high in the summer, air conditioning usage is high, resulting in a higher electricity load. Therefore, weather factors are taken into account when predicting future electricity consumption.

[0088] In one implementation, obtaining the future predicted electricity price includes: obtaining historical electricity prices and electricity price adjustment information released by the electricity market; inputting the historical electricity prices and electricity price adjustment information into an electricity price prediction model, and using the electricity price prediction model to output the future predicted electricity price.

[0089] For example, obtain the predicted electricity price for a user, park, or factory on a certain day in the future.

[0090] Future electricity price forecasts include two scenarios: fixed and floating. In the fixed-price scenario, the electricity price remains unchanged, and the future price is the current price. In the floating-price scenario, the varying prices of electricity over time directly impact the energy storage system's charge and discharge control strategy. Historical electricity prices and price adjustment information published by the power market are collected and input into the price forecast model, which then outputs the predicted future price. This model can be a pre-trained machine learning model, a deep learning model, or other similar model.

[0091] Corresponding to the application scenario and method of the method provided in the embodiment of the present application, the embodiment of the present application also provides a charge and discharge control device for an energy storage system. Figure 5 FIG2 is a block diagram of a charge and discharge control device for an energy storage system according to an embodiment of the present application, wherein the device includes:

[0092] The acquisition module 501 is used to obtain the future predicted electricity load, the future predicted electricity price and the operating cost of the energy storage system.

[0093] The first determination module 502 is configured to determine a control objective function based on the future predicted electricity load, the future predicted electricity price, and the operating cost.

[0094] The second determination module 503 is used to determine the charge and discharge power constraint conditions and the state of charge constraint conditions; the state of charge constraint conditions include adjustment parameters, and the adjustment parameters are used to adjust the state of charge value to reduce the change rate of the state of charge value.

[0095] The control module 504 is used to control the charging and discharging of the energy storage system according to the control objective function, the charging and discharging power constraints and the state of charge constraints.

[0096] The charge and discharge control device for the energy storage system provided in the embodiment of the present application first obtains the future predicted electricity load, the future predicted electricity price and the operating cost of the energy storage system; then, based on the future predicted electricity load, the future predicted electricity price and the operating cost, determines the control objective function; determines the charge and discharge power constraint conditions and the state of charge constraint conditions; the state of charge constraint conditions include adjustment parameters, and the adjustment parameters are used to adjust the state of charge value to reduce the rate of change of the state of charge value; finally, the energy storage system is charged and discharged according to the control objective function, the charge and discharge power constraint conditions and the state of charge constraint conditions. In the embodiment of the present application, the energy storage system is charged and discharged according to the control objective function, the charge and discharge power constraint conditions and the state of charge constraint conditions, and the state of charge value is adjusted by the adjustment parameters in the state of charge constraint conditions to reduce the rate of change of the state of charge value, thereby avoiding the problem of incomplete charging and discharging of the energy storage system to a certain extent and increasing revenue.

[0097] In one implementation, the control objective of the control objective function includes minimizing the operating cost of the energy storage system; the operating cost of the energy storage system includes the operating cost; the operating cost includes a fixed operating cost and a dynamic operating cost. In the same electricity consumption period, the later the energy storage system starts charging or discharging, the higher the dynamic operating cost.

[0098] In one implementation, the second determination module 503 is used to: obtain static parameters and operating boundary parameters of the energy storage system; the static parameters represent inherent properties of the energy storage system; the operating boundary parameters include boundary values for charging or discharging the energy storage system; determine charging and discharging power constraints based on the operating boundary parameters; and determine the state of charge constraints based on the static parameters, the operating boundary parameters, and the adjustment parameters.

[0099] In one implementation, the control module 504 is configured to determine the charging time, charging power, discharging time, discharging power, and state of charge value of the energy storage system according to the control objective function, the charging and discharging power constraints, and the state of charge constraints.

[0100] In one implementation, the device is further configured to: stop executing the charging instruction or determine the charging power to be zero if the state of charge value reaches a first preset threshold; stop executing the discharging instruction or determine the discharging power to be zero if the state of charge value reaches a second preset threshold; wherein the first preset threshold is greater than the second preset threshold.

[0101] In one implementation, the acquisition module 501 is used to: acquire historical measured power load and weather forecast information; input the historical measured power load and weather forecast information into a power load prediction model, and use the power load prediction model to output future predicted power load.

[0102] In one implementation, the acquisition module 501 is used to: acquire historical electricity prices and electricity price adjustment information released by the electricity market; input the historical electricity prices and electricity price adjustment information into an electricity price prediction model, and use the electricity price prediction model to output future predicted electricity prices.

[0103] The functions of each module in the embodiment of the present application can be referred to the corresponding description in the above method, and have corresponding beneficial effects, which will not be repeated here.

[0104] Figure 6 FIG. 1 is a block diagram of an electronic device for implementing an embodiment of the present application. Figure 6 As shown, the electronic device includes: a memory 610 and a processor 620. The memory 610 stores a computer program that can be run on the processor 620. When the processor 620 executes the computer program, the method in the above embodiment is implemented. The number of the memory 610 and the processor 620 can be one or more.

[0105] The electronic device also includes:

[0106] The communication interface 630 is used to communicate with external devices and perform data exchange transmission.

[0107] If the memory 610, processor 620, and communication interface 630 are implemented independently, the memory 610, processor 620, and communication interface 630 can be connected to each other via a bus and communicate with each other. The bus can be an Industry Standard Architecture (ISA) bus, a Peripheral Component Interconnect (PCI) bus, or an Extended Industry Standard Architecture (EISA) bus. The bus can be divided into an address bus, a data bus, a control bus, etc. For ease of representation, Figure 6 Only one thick line is used in the diagram, but this does not mean that there is only one bus or one type of bus.

[0108] Optionally, in a specific implementation, if the memory 610, the processor 620 and the communication interface 630 are integrated on a chip, the memory 610, the processor 620 and the communication interface 630 can communicate with each other through an internal interface.

[0109] An embodiment of the present application provides a computer-readable storage medium storing a computer program, which implements the method provided in the embodiment of the present application when the program is executed by a processor.

[0110] An embodiment of the present application provides a computer program product, which includes a computer program. When the computer program is executed by a processor, the method provided in the embodiment of the present application is implemented.

[0111] An embodiment of the present application also provides a chip, which includes a processor for calling and executing instructions stored in the memory from the memory, so that a communication device equipped with the chip executes the method provided in the embodiment of the present application.

[0112] An embodiment of the present application also provides a chip, including: an input interface, an output interface, a processor and a memory. The input interface, the output interface, the processor and the memory are connected through an internal connection path. The processor is used to execute the code in the memory. When the code is executed, the processor is used to execute the method provided in the embodiment of the application.

[0113] It should be understood that the processor may be a central processing unit (CPU), or other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASIC), field-programmable gate arrays (FPGA), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. A general-purpose processor may be a microprocessor or any conventional processor, etc. It is worth noting that the processor may be a processor that supports the Advanced RISC Machines (ARM) architecture.

[0114] Furthermore, optionally, the above-mentioned memory may include a read-only memory and a random access memory. The memory may be a volatile memory or a non-volatile memory, or may include both volatile and non-volatile memories. Among them, the non-volatile memory may include a read-only memory (ROM), a programmable read-only memory (PROM), an erasable programmable read-only memory (EPROM), an electrically erasable programmable read-only memory (EEPROM), or a flash memory. The volatile memory may include a random access memory (RAM), which is used as an external cache. By way of example but not limitation, many forms of RAM are available. For example, static random access memory (SRAM), dynamic random access memory (DRAM), synchronous dynamic random access memory (SDRAM), double data rate synchronous dynamic random access memory (DDR SDRAM), enhanced synchronous dynamic random access memory (ESDRAM), synchronous link DRAM (SLDRAM) and direct memory bus random access memory (DR RAM).

[0115] In the above embodiments, all or part of the embodiments may be implemented using software, hardware, firmware, or any combination thereof. When implemented using software, all or part of the embodiments may be implemented in the form of a computer program product. A computer program product includes one or more computer instructions. When the computer program instructions are loaded and executed on a computer, the processes or functions according to the present application are generated in whole or in part. The computer may be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. The computer instructions may be stored in a computer-readable storage medium or transferred from one computer-readable storage medium to another.

[0116] In the description of this specification, the reference terms "one embodiment," "some embodiments," "example," "specific example," or "some examples" mean that the specific features, structures, materials, or characteristics described in conjunction with the embodiment or example are included in at least one embodiment or example of the present application. Moreover, the specific features, structures, materials, or characteristics described may be combined in any appropriate manner in any one or more embodiments or examples. In addition, those skilled in the art may combine and combine different embodiments or examples described in this specification, as well as features of different embodiments or examples, unless they are mutually inconsistent.

[0117] Furthermore, 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 being referred to. Thus, a feature defined as "first" or "second" may explicitly or implicitly include at least one such feature. Throughout the description of this application, "plurality" means two or more, unless otherwise specifically defined.

[0118] Any process or method described in the flowchart or otherwise described herein can be understood to represent a module, segment or portion of code comprising one or more executable instructions for implementing the steps of a specific logical function or process. The scope of the preferred embodiments of the present application includes other implementations in which the functions may be performed in a different order than shown or discussed, including performing the functions substantially simultaneously or in reverse order depending on the functions involved.

[0119] The logic and / or steps described in the flowchart or otherwise described herein, for example, can be considered as an ordered list of executable instructions for implementing logical functions, and can be embodied in any computer-readable medium for use by an instruction execution system, apparatus or device (such as a computer-based system, a system including a processor or other system that can fetch instructions from an instruction execution system, apparatus or device and execute instructions), or used in combination with such instruction execution systems, apparatuses or devices.

[0120] It should be understood that various parts of the present application can be implemented using hardware, software, firmware, or a combination thereof. In the above embodiments, multiple steps or methods can be implemented using software or firmware stored in a memory and executed by a suitable instruction execution system. All or part of the steps of the above embodiment method can be completed by instructing the relevant hardware through a program, which can be stored in a computer-readable storage medium. When the program is executed, it includes one or a combination of the steps of the method embodiment.

[0121] In addition, the functional units in the various embodiments of the present application may be integrated into a single processing module, or each unit may exist physically separately, or two or more units may be integrated into a single module. The aforementioned integrated modules may be implemented in the form of hardware or in the form of software functional modules. If the aforementioned integrated modules are implemented in the form of software functional modules and sold or used as independent products, they may also be stored in a computer-readable storage medium. The storage medium may be a read-only memory, a magnetic disk, or an optical disk, etc.

[0122] The above is merely an exemplary embodiment of the present application, but the scope of protection of the present application is not limited thereto. Any person skilled in the art can easily conceive of various modifications or substitutions within the technical scope described in this application, and such modifications or substitutions should be included in the scope of protection of the present application. Therefore, the scope of protection of the present application should be based on the scope of protection of the claims.

Claims

1. A charge and discharge control method for an energy storage system, characterized in that: The method comprises: Obtain future forecasted electricity load, future forecasted electricity price, and energy storage system operating costs; determining a control objective function based on the future predicted electricity load, the future predicted electricity price, and the operating cost; Determining a charge and discharge power constraint and a state of charge constraint; the state of charge constraint includes an adjustment parameter, the adjustment parameter being used to adjust the state of charge value to reduce a rate of change of the state of charge value; The energy storage system is controlled to charge and discharge according to the control objective function, the charge and discharge power constraint condition, and the state of charge constraint condition.

2. The method according to claim 1, characterized in that The control objectives of the control objective function include minimizing the operating cost of the energy storage system; the operating cost of the energy storage system includes the operating cost; the operating cost includes fixed operating cost and dynamic operating cost. In the same electricity consumption period, the later the energy storage system starts charging or discharging, the higher the dynamic operating cost.

3. The method according to claim 1, characterized in that Determining the charge and discharge power constraint conditions and the state of charge constraint conditions includes: Obtaining static parameters and operating boundary parameters of the energy storage system; the static parameters characterize inherent properties of the energy storage system; the operating boundary parameters include boundary values for charging or discharging the energy storage system; Determining the charge and discharge power constraint condition according to the operation boundary parameter; The state of charge constraint condition is determined according to the static parameter, the operating boundary parameter and the adjustment parameter.

4. The method according to any one of claims 1 to 3, characterized in that The controlling the charging and discharging of the energy storage system according to the control objective function, the charging and discharging power constraint condition, and the state of charge constraint condition includes: The charging time, charging power, discharging time, discharging power and state of charge value of the energy storage system are determined according to the control objective function, the charging and discharging power constraint conditions and the state of charge constraint conditions.

5. The method according to claim 4, characterized in that The method further comprises: If the state of charge value reaches a first preset threshold, stopping execution of the charging instruction, or determining the charging power to be zero; If the state of charge value reaches a second preset threshold, stopping execution of the discharge instruction, or determining the discharge power to be zero; The first preset threshold is greater than the second preset threshold.

6. The method according to any one of claims 1 to 3, characterized in that The obtaining of the future predicted electricity load includes: Obtain historical measured electricity load and weather forecast information; The historically measured power load and the weather forecast information are input into a power load prediction model, and the power load prediction model is used to output the future predicted power load.

7. The method according to any one of claims 1 to 3, characterized in that The obtaining of the future predicted electricity price includes: Obtain historical electricity prices and electricity price adjustment information released by the electricity market; The historical electricity price and the electricity price adjustment information are input into an electricity price prediction model, and the future predicted electricity price is output using the electricity price prediction model.

8. A charge and discharge control device for an energy storage system, characterized in that: The device comprises: An acquisition module is used to obtain the future predicted electricity load, the future predicted electricity price and the operating cost of the energy storage system; A first determining module is configured to determine a control objective function based on the future predicted electricity load, the future predicted electricity price, and the operating cost; a second determining module, configured to determine a charge / discharge power constraint condition and a state of charge constraint condition; the state of charge constraint condition including an adjustment parameter, the adjustment parameter being configured to adjust the state of charge value to reduce a rate of change of the state of charge value; A control module is used to control the charge and discharge of the energy storage system according to the control objective function, the charge and discharge power constraint condition and the state of charge constraint condition.

9. An electronic device, characterized in that: The electronic device includes a memory, a processor, and a computer program stored in the memory, and the processor implements the method according to any one of claims 1 to 7 when executing the computer program.

10. A computer-readable storage medium, characterized in that The computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the method according to any one of claims 1 to 7 is implemented.

11. A computer program product, characterized in that The computer program product comprises a computer program, and when the computer program is executed by a processor, the method according to any one of claims 1 to 7 is implemented.

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