Energy storage control method, system and electronic equipment

Abstract

The present application provides an energy storage control method, system and electronic device. The method includes: determining the minimum reserved power of the energy storage device according to the historical data of the power grid frequency regulation; determining the load change threshold corresponding to the maximum user benefit value according to the incentive mechanism; the load change includes the difference between the incentive load and the load baseline, and the incentive load and the load baseline respectively include the power load of the energy storage device within a predetermined time with and without the incentive mechanism; if the current power grid is not in a frequency regulation state, and the current reserved power of the energy storage device is less than the minimum reserved power, or if the current power grid is not in a frequency regulation state, and the current reserved power of the energy storage device is not less than the minimum reserved power, and the current load change is greater than the load change threshold, and the current electricity price is less than the preset electricity price threshold, then control the energy storage device to charge; otherwise, control the energy storage device not to charge. The method of the present application is used to maintain sufficient power supply during power grid frequency regulation.

Description

Technical Field

[0001] The present application relates to energy storage technology, and in particular to an energy storage control method, system and electronic equipment. Background Art

[0002] The distributed energy storage system is a new type of technological equipment that can effectively utilize electrical energy. It uses advanced energy storage technology to store electricity in the power grid close to the user side for user use, thereby improving the stability and reliability of the power supply of the power grid.

[0003] In related technologies, distributed energy storage systems only charge when electricity prices are low and discharge when electricity prices are high, and the control strategy is relatively simple. When the grid frequency is adjusted, the energy storage cabinet needs to supply power to the grid, and the amount of electricity stored in the energy storage device may not be able to meet the grid demand. Summary of the invention

[0004] The present application provides an energy storage control method, system and electronic equipment for maintaining sufficient power supply during power grid frequency modulation.

[0005] On the one hand, the present application provides an energy storage control method, comprising:

[0006] Determine the minimum reserved power for energy storage equipment based on historical data of grid frequency regulation;

[0007] According to the incentive mechanism, determine the load change threshold corresponding to the maximum user benefit value; wherein the load change includes the difference between the incentive load and the load baseline, the incentive load includes the power load of the energy storage device within a predetermined time when there is an incentive mechanism, and the load baseline includes the power load of the energy storage device within a predetermined time when there is no incentive mechanism;

[0008] If the current power grid is not in frequency regulation state, and the current reserved power of the energy storage device is less than the minimum reserved power,

[0009] Alternatively, if the current power grid is not in a frequency modulation state, and the current reserved power of the energy storage device is not less than the minimum reserved power, and the current load change is greater than the load change threshold, and the current electricity price is less than the preset electricity price threshold, then the energy storage device is controlled to charge;

[0010] Otherwise, the energy storage device is controlled not to be charged.

[0011] In a possible implementation, determining the minimum reserved power of the energy storage device according to the historical data of power grid frequency regulation includes:

[0012] Based on the historical data of power grid frequency regulation, the multiple frequency regulation times and the single maximum frequency regulation power of the power grid are predicted;

[0013] The minimum reserved power of the energy storage device is determined according to the multiple frequency modulation times and the single maximum frequency modulation power.

[0014] In a possible implementation, determining the minimum reserved power of the energy storage device according to the multiple frequency modulation times and the single maximum frequency modulation power includes:

[0015] Calculating a minimum frequency modulation interval according to the multiple frequency modulation times;

[0016] If the energy storage device can be charged to the single maximum frequency modulation power within the minimum frequency modulation interval, the minimum reserved power is determined to be the first power, and the first power is not less than the single maximum frequency modulation power.

[0017] In a possible implementation, the method further includes:

[0018] If the energy storage device cannot be charged to the single maximum frequency modulation capacity within the minimum frequency modulation interval, and the next frequency modulation time interval corresponding to the current time is greater than the minimum frequency modulation interval, then determining that the current minimum reserved capacity is the first capacity;

[0019] If the energy storage device cannot be charged to the single maximum frequency modulation power within the minimum frequency modulation interval, and the next frequency modulation time interval corresponding to the current time is not greater than the minimum frequency modulation interval, the current minimum reserved power is determined to be the second power, and the second power is not less than twice the single maximum frequency modulation power.

[0020] In a possible implementation, the first power is the product of one plus the sum of preset redundancy and the single maximum frequency modulation power, and the second power is the product of two plus the sum of preset redundancy and the single maximum frequency modulation power.

[0021] In a possible implementation, determining the load change threshold corresponding to the maximum user benefit value according to the incentive mechanism includes:

[0022] According to the incentive mechanism, the corresponding relationship between user benefit and load change is determined, and the load change value corresponding to the maximum user benefit value is used as the load change threshold.

[0023] The load change satisfies a grid balance condition, and the grid balance condition includes:

[0024] The absolute value of the demand load minus the grid power generation minus the load change is not greater than the preset load deviation threshold; the demand load includes the power load target of the energy storage device within the predetermined time, and the grid power generation includes the power generation of the grid within the second preset time.

[0025] In a possible implementation, determining the corresponding relationship between user benefits and load changes according to the incentive mechanism includes:

[0026] According to the incentive mechanism, determining the corresponding relationship between the compensation amount and the load change; and determining the corresponding relationship between the change cost and the load change;

[0027] The difference between the compensation amount and the change cost is taken as the user benefit, thereby obtaining the corresponding relationship between the user benefit and the load change.

[0028] In a possible implementation, the compensation amount is proportional to the load change.

[0029] In a possible implementation, the change cost is proportional to the square of the load change.

[0030] In a possible implementation, the preset electricity price threshold is a valley electricity price.

[0031] In a possible implementation, the predicting of multiple frequency regulation times and a single maximum frequency regulation power according to the historical data of power grid frequency regulation includes:

[0032] The power grid frequency modulation historical data is input into a trained machine learning model and / or a linear regression model to obtain the multiple frequency modulation times and the single maximum frequency modulation power output by the machine learning model and / or the linear regression model.

[0033] On the other hand, the present application provides an energy storage control system, including: a data center, an edge computing node, and an energy storage device;

[0034] The data center is used to determine the load change threshold corresponding to the maximum user benefit value according to the incentive mechanism; wherein the load change includes the difference between the incentive load and the load baseline, the incentive load includes the power load of the energy storage device within a predetermined time when there is an incentive mechanism, and the load baseline includes the power load of the energy storage device within a predetermined time when there is no incentive mechanism; and, according to whether the current power grid is in a frequency modulation state, the current reserved power of the energy storage device, the current load change and the current electricity price, send a control instruction to the edge computing node;

[0035] The edge computing node is used to control the energy storage device to charge or not charge according to the control instruction.

[0036] On the other hand, the present application provides an electronic device, comprising: a processor, and a memory communicatively connected to the processor; the memory stores computer-executable instructions; the processor executes the computer-executable instructions stored in the memory to implement the method described above.

[0037] On the other hand, the present application provides a computer-readable storage medium, wherein the computer-readable storage medium stores computer-executable instructions, and when the computer-executable instructions are executed by a processor, they are used to implement the method as described above.

[0038] In yet another aspect, the present application provides a computer program product, comprising a computer program, wherein the computer program is used to implement the above-mentioned method when executed by a processor.

[0039] In the energy storage control method, system and electronic device provided by the present application, the minimum reserved power of the energy storage device is determined according to the historical data of the power grid frequency modulation, and the load change threshold corresponding to the maximum user benefit value is determined according to the incentive mechanism; when the current power grid is not in the frequency modulation state, and the current reserved power of the energy storage device is less than the minimum reserved power, the energy storage device is controlled to charge, so that the energy storage device can be charged in time to a state where the power is not less than the minimum reserved power, so that when the power grid frequency modulation reduces the power supply, the power grid can be effectively powered, the power grid frequency is maintained stable, and the stability and reliability of the power supply are effectively improved; when the current power grid is not in the frequency modulation state, and the current reserved power of the energy storage device is not less than the minimum reserved power, and the current load change is greater than the load change threshold, and the current electricity price is less than the preset electricity price threshold, the energy storage device is controlled to charge, so that when the reserved power of the energy storage device is maintained sufficient, the power grid pressure is further alleviated by adjusting the user's electricity consumption behavior, and the user's benefits can be improved, thereby realizing intelligent control of the charging of the energy storage device. BRIEF DESCRIPTION OF THE DRAWINGS

[0040] The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the present application and, together with the description, serve to explain the principles of the present application.

[0041] Figure 1 A schematic diagram of a flow chart of an energy storage control method provided in an embodiment of the present application is exemplarily shown in FIG.

[0042] Figure 2 A schematic diagram of a flow chart of another energy storage control method provided in an embodiment of the present application is exemplarily shown in FIG.

[0043] Figure 3 A schematic diagram of a flow chart of another energy storage control method provided in an embodiment of the present application is exemplarily shown in FIG.

[0044] Figure 4 A schematic diagram of a flow chart of another energy storage control method provided in an embodiment of the present application is exemplarily shown in FIG.

[0045] Figure 5 The schematic diagram of the structure of the energy storage control system provided by the embodiment of the present application is exemplarily shown in FIG.

[0046] Figure 6 A structural schematic diagram of an electronic device provided in an embodiment of the present application is exemplarily shown in FIG.

[0047] The above drawings have shown clear embodiments of the present application, which will be described in more detail later. These drawings and text descriptions are not intended to limit the scope of the present application in any way, but to illustrate the concept of the present application to those skilled in the art by referring to specific embodiments. DETAILED DESCRIPTION

[0048] Exemplary embodiments will be described in detail herein, examples of which are shown in the accompanying drawings. When the following description refers to the drawings, the same numbers in different drawings represent the same or similar elements unless otherwise indicated. The implementations described in the following exemplary embodiments do not represent all implementations consistent with the present application. Instead, they are merely examples of devices and methods consistent with some aspects of the present application as detailed in the appended claims.

[0049] The module in this application refers to a functional module or a logical module. It can be in software form, and its functions are realized by executing program code by a processor; it can also be in hardware form. "And / or" describes the association relationship of associated objects, indicating that three relationships can exist. For example, A and / or B can represent: A exists alone, A and B exist at the same time, and B exists alone. The character " / " generally indicates that the related objects before and after are in an "or" relationship.

[0050] First, the terms involved in this application are explained:

[0051] Grid frequency modulation: refers to the automatic control process in which the control system of the units in the grid automatically controls the increase or decrease of the active power of the units, limits the change of grid frequency, and maintains a stable grid frequency when the grid frequency deviates from the rated value.

[0052] The distributed energy storage system is a new type of technological equipment that can effectively utilize electrical energy. It uses advanced energy storage technology to store electricity in the power grid close to the user side for user use, thereby improving the stability and reliability of the power supply of the power grid.

[0053] In related technologies, distributed energy storage systems only charge when electricity prices are low and discharge when electricity prices are high, and the control strategy is relatively simple. When the grid frequency is adjusted, the energy storage cabinet needs to supply power to the grid, and the amount of electricity stored in the energy storage device may not be able to meet the grid frequency adjustment requirements.

[0054] The technical solution of the present application is illustrated below with specific embodiments. The following specific embodiments can be combined with each other, and the same or similar concepts or processes may not be described in detail in some embodiments.

[0055] Embodiment 1

[0056] Figure 1 The flowchart of the energy storage control method provided in the embodiment of the present application is shown in FIG. The execution subject of the method may be an energy storage control system. Figure 1 As shown, the energy storage control method provided in this embodiment may include:

[0057] S101. Determine the minimum reserved power of the energy storage device based on the historical data of power grid frequency regulation;

[0058] S102. Determine a load change threshold corresponding to the maximum user benefit value according to an incentive mechanism; wherein the load change includes the difference between the incentive load and the load baseline, the incentive load includes the power load of the energy storage device within a predetermined time when there is an incentive mechanism, and the load baseline includes the power load of the energy storage device within a predetermined time when there is no incentive mechanism;

[0059] S103: If the current power grid is not in frequency regulation state, and the current reserved power of the energy storage device is less than the minimum reserved power,

[0060] Alternatively, if the current power grid is not in a frequency modulation state, and the current reserved power of the energy storage device is not less than the minimum reserved power, and the current load change is greater than the load change threshold, and the current electricity price is less than the preset electricity price threshold, then the energy storage device is controlled to charge;

[0061] Otherwise, the energy storage device is controlled not to be charged.

[0062] In the specific implementation, the frequency regulation of the power grid can be predicted based on the historical data of the power grid frequency regulation, so as to determine the minimum reserved power of the energy storage device. When the power grid is not in the frequency regulation state, it is determined whether the current reserved power of the energy storage device is less than the minimum reserved power. If the current reserved power of the energy storage device is less than the minimum reserved power, the energy storage device is controlled to charge so that the energy storage device can be charged in time to a state where the power is not less than the minimum reserved power. When the power grid frequency is regulated, the energy storage device can provide sufficient power supply for the power grid, and the frequency balance of the power grid is effectively maintained through the power grid frequency regulation strategy, thereby improving the stability of the power grid.

[0063] Furthermore, while the power grid frequency is being modulated, the power demand during peak hours can be reduced by adjusting the user's power consumption behavior, thereby reducing the peak-shaving pressure of the power system and improving the operating efficiency of the power system. In order to encourage users to adjust their power consumption behavior, the power grid company will provide economic compensation or implement other incentives. Therefore, on the basis of satisfying the power grid frequency modulation strategy, the demand response strategy can be further implemented. When the current power grid is not in a frequency modulation state and the current reserved power of the energy storage device is not less than the minimum reserved power, it is determined whether the current load change is greater than the load change threshold. If the current load change is greater than the load change threshold, the energy storage device is controlled to charge, so that the load change is reduced, so that the load change is closer to the load change threshold, and the user's benefit value becomes larger; if the current load change is not greater than the load change threshold, the energy storage device is controlled not to charge. By further combining the user's benefit brought by the load change when the power grid is not frequency modulated and the energy storage device has sufficient energy storage, it is decided whether to charge or not, and the pressure on the power grid is further alleviated by adjusting the user's power consumption behavior, so as to achieve a balance between power grid supply and demand and increase user benefits.

[0064] Furthermore, it is also possible to decide whether to control the energy storage device to charge in combination with the electricity price strategy. Specifically, when the current power grid is not in a frequency modulation state, and the current reserved power of the energy storage device is not less than the minimum reserved power, and the current load change is greater than the load change threshold, it is judged that the current electricity price is less than the preset electricity price threshold. If the current electricity price is less than the preset electricity price threshold, the energy storage device is controlled to charge; if the current electricity price is not less than the preset electricity price threshold, the energy storage device is controlled not to charge, so that it can meet the premise of the power grid frequency modulation strategy and demand response strategy, charge when the electricity price is low, and not charge when the electricity price is high, so as to achieve higher economic benefits.

[0065] In a possible implementation, the preset electricity price threshold is a valley electricity price.

[0066] In practical applications, one or more of these three strategies can be selected as needed. However, to ensure the stable operation of the power system and meet the electricity needs of users, the grid frequency regulation strategy is the first priority, the demand response strategy is the second priority, and the electricity price strategy is the third priority.

[0067] Figure 2 A schematic flow chart of another energy storage control method provided in an embodiment of the present application. Figure 4 A flow chart of another energy storage control method provided in an embodiment of the present application. It can be understood that: Figure 2 A flow chart of an energy storage control method for executing a grid frequency regulation strategy and a demand response strategy. Figure 3 A flow chart of the energy storage control method for executing the grid frequency regulation strategy and the peak-valley electricity price strategy. Figure 4A flow chart of an energy storage control method for executing grid frequency regulation strategy, demand response strategy and peak-valley electricity price strategy.

[0068] like Figure 2 As shown, when the current power grid is not in a frequency modulation state and the current reserved power of the energy storage device is less than the minimum reserved power, the energy storage device is controlled to charge, so that the energy storage device can be charged in time to a state where the power is not less than the minimum reserved power. When the current power grid is not in a frequency modulation state and the current reserved power of the energy storage device is not less than the minimum reserved power, if the current load change is greater than the load change threshold, the energy storage device is controlled to charge so that the load change becomes smaller and approaches the load change threshold, thereby approaching the maximum user benefit; if the current load change is not greater than the load change threshold, the energy storage device is controlled not to charge.

[0069] like Figure 3 As shown, when the current power grid is not in a frequency modulation state and the current reserved power of the energy storage device is not less than the minimum reserved power, if the current electricity price is not higher than the preset electricity price threshold, the energy storage device is controlled to charge; otherwise, the energy storage device is controlled not to charge, so that it can be charged when the electricity price is low, achieving higher economic benefits.

[0070] like Figure 4 As shown, the energy storage device is controlled to charge only when the power grid is not in a frequency modulation state and the current reserved power of the energy storage device is less than the minimum reserved power, or when the power grid is not in a frequency modulation state and the current reserved power of the energy storage device is not less than the minimum reserved power and the current load change is greater than the load change threshold and the current electricity price is not higher than the preset electricity price threshold, and charging is not performed in other cases.

[0071] In the embodiment of the present application, the minimum reserved power of the energy storage device is determined according to the historical data of the power grid frequency regulation, and the load change threshold corresponding to the maximum user benefit value is determined according to the incentive mechanism; when the current power grid is not in the frequency regulation state, and the current reserved power of the energy storage device is less than the minimum reserved power, the energy storage device is controlled to charge, so that the energy storage device can be charged in time to a state where the power is not less than the minimum reserved power, so that when the power grid frequency regulation reduces the power supply, the power grid can be effectively powered, the power grid frequency is maintained stable, and the stability and reliability of the power supply are effectively improved; when the current power grid is not in the frequency regulation state, and the current reserved power of the energy storage device is not less than the minimum reserved power, and the current load change is greater than the load change threshold, and the current electricity price is less than the preset electricity price threshold, the energy storage device is controlled to charge, so as to maintain sufficient reserved power of the energy storage device while improving the economic benefits of the user and realizing intelligent control of the charging and discharging of the energy storage device.

[0072] In a possible implementation, the minimum reserved power of the energy storage device is determined based on the historical data of power grid frequency regulation, including:

[0073] Based on the historical data of power grid frequency regulation, the multiple frequency regulation times and the single maximum frequency regulation power of the power grid are predicted;

[0074] Determine the minimum reserved power of the energy storage device based on multiple frequency modulation times and the maximum single frequency modulation power.

[0075] In the specific implementation, the frequency regulation of the power grid is predicted based on the historical data of power grid frequency regulation, including the multiple frequency regulation times and power of the power grid. The maximum single frequency regulation power can be determined based on the multiple frequency regulation times. The minimum reserved power of the energy storage device is determined based on the multiple frequency regulation times and the single maximum frequency regulation power. When the power grid is not in the frequency regulation state, if the current reserved power of the energy storage device is less than the minimum reserved power, the energy storage device is controlled to charge so that the energy storage device can be charged in time to a state where the power is not less than the minimum reserved power. When the power demand of the power grid frequency regulation reaches the single maximum frequency regulation power, the energy storage device can still provide sufficient power supply to the power grid and effectively maintain the stability of the power grid frequency.

[0076] In the embodiment of the present application, the frequency modulation of the power grid is predicted based on the historical data of the power grid frequency modulation, and the minimum reserved power of the energy storage device is determined based on the frequency modulation of the power grid. When the power grid is not in the frequency modulation state, it is decided to control the energy storage device to charge or not to charge based on whether the current reserved power of the energy storage device is less than the minimum reserved power, so that the energy storage device can be charged in time to a state where the power is not less than the minimum reserved power, so that the power grid can be fully powered when the power grid is modulated, and the reliability of the energy storage cabinet is effectively improved.

[0077] In a possible implementation, the minimum reserved power of the energy storage device is determined according to multiple frequency modulation times and a single maximum frequency modulation power, including:

[0078] According to multiple frequency modulation times, the minimum frequency modulation interval is calculated;

[0079] If the energy storage device can be charged to the single maximum frequency modulation power within the minimum frequency modulation interval, the minimum reserved power is determined to be the first power, and the first power is not less than the single maximum frequency modulation power.

[0080] In a specific implementation, if the energy storage device can be charged to the single maximum frequency modulation power within the minimum frequency modulation interval, it means that the energy storage device can be charged to the single maximum frequency modulation power within the time interval between any two grid frequency modulations. In this case, at each grid frequency modulation, the energy storage device only needs to store a first power of not less than the single maximum frequency modulation power to meet the requirement of stable power supply to the grid.

[0081] In the embodiment of the present application, when the energy storage device can be charged to the single maximum frequency modulation power within the minimum frequency modulation interval, the energy storage device has a power reserve of the single maximum frequency modulation power each time the grid frequency is modulated, thereby achieving higher benefits while meeting the grid frequency modulation requirements.

[0082] In a possible implementation, the method further includes:

[0083] If the energy storage device cannot be charged to the single maximum frequency modulation power within the minimum frequency modulation interval, and the next frequency modulation interval corresponding to the current time is greater than the minimum frequency modulation interval, then the current minimum reserved power is determined to be the first power;

[0084] If the energy storage device cannot be charged to the single maximum frequency modulation power within the minimum frequency modulation interval, and the next frequency modulation interval corresponding to the current time is not greater than the minimum frequency modulation interval, the current minimum reserved power is determined to be the second power, and the second power is not less than twice the single maximum frequency modulation power.

[0085] It is understandable that if the energy storage device cannot be charged to the single maximum frequency modulation power within the minimum frequency modulation interval, it means that there is an interval between two grid frequency modulations and the energy storage device cannot be charged to the single maximum frequency modulation power. Therefore, before the time interval arrives, the energy storage device needs to store a second power that is not less than twice the single maximum frequency modulation power, so that if the energy storage device cannot be fully charged during the time interval, it can still provide stable power for the next grid frequency modulation corresponding to the time interval.

[0086] In a specific implementation, if the energy storage device cannot be charged to the single maximum frequency modulation power within the minimum frequency modulation interval, then when the next frequency modulation interval corresponding to the current time is greater than the minimum frequency modulation interval, the current minimum reserved power is determined to be the first power; when the next frequency modulation interval corresponding to the current time is not greater than the minimum frequency modulation interval, the current minimum reserved power is determined to be the second power. For example, assuming that it is predicted that the power grid will be modulated at 13:00-14:00, 16:00-17:00, and 20:00-21:00 today, and the current time is 15:00, then the next frequency modulation interval corresponding to the current time is determined to be 3 hours, and the duration of the frequency modulation interval is 17:00-20:00.

[0087] It is understandable that the intervals between two consecutive frequency modulations are relatively short, resulting in a small probability that the energy storage device cannot be charged to the single maximum frequency modulation power within the intervals between two consecutive frequency modulations. Therefore, it is only necessary to make the second power not less than twice the single maximum frequency modulation power to meet the grid frequency modulation demand.

[0088] In an embodiment of the present application, when the energy storage device cannot be charged to the single maximum frequency modulation power within the minimum frequency modulation interval, the current minimum reserved power is dynamically adjusted so that the energy storage device has sufficient power reserve each time the grid frequency is modulated, thereby achieving higher benefits while meeting the grid frequency modulation requirements.

[0089] Exemplarily, the first power is the product of one plus the sum of preset redundancy and the single maximum frequency modulation power, and the second power is the product of two plus the sum of preset redundancy and the single maximum frequency modulation power.

[0090] That is to say, if the energy storage device can be charged to the single maximum frequency modulation capacity within the minimum frequency modulation interval, the minimum reserved capacity is ,in is the maximum frequency modulation power at a single time, For the preset grid frequency redundancy, e.g. If the energy storage device cannot be charged to the single maximum frequency modulation capacity within the minimum frequency modulation interval, the next frequency modulation interval corresponding to the current time is greater than the minimum frequency modulation interval. When, current ; The next frequency modulation interval corresponding to the current time is not greater than the minimum frequency modulation interval When, current .

[0091] In the embodiment of the present application, by setting power redundancy, the energy storage device can still have sufficient power to supply power to the power grid when the actual frequency modulation power of the power grid fluctuates greatly, thereby effectively improving the stability and reliability of the power supply of the energy storage cabinet.

[0092] In a possible implementation, the load change threshold corresponding to the maximum user benefit value is determined according to the incentive mechanism, including:

[0093] According to the incentive mechanism, the corresponding relationship between user benefit and load change is determined, and the load change value corresponding to the maximum user benefit value is used as the load change threshold.

[0094] The load change , To stimulate the load, it means that the energy storage device is in the second predetermined time under the incentive mechanism. The power load inside The load baseline refers to the energy storage device at the second predetermined time without an incentive mechanism. The electrical load inside.

[0095] For example, the load baseline can be calculated based on historical electricity load using statistical methods, or can be obtained through model prediction.

[0096] The formula for the grid balance condition is as follows:

[0097]

[0098] in, is the allowable load deviation threshold, is the demand load, is the power generation of the grid, is the load change. In practical applications, the required load The power load target set for the power grid company. When there is a gap between the demand load and the actual power generation of the power grid, the actual power load can be reduced by reducing the charging amount of the energy storage device. By making the demand load close to the sum of the power generation of the power grid and the load change, the supply and demand balance of the power grid can be achieved.

[0099] In an embodiment of the present application, the corresponding relationship between user benefit and load change is determined, and on the premise that the load change amount meets the grid balance condition, the load change value corresponding to the maximum user benefit value is used as the load change threshold, which can effectively maintain the balance of supply and demand of the grid while improving user benefits.

[0100] In a possible implementation, the corresponding relationship between user benefits and load changes is determined according to an incentive mechanism, including:

[0101] According to the incentive mechanism, determine the corresponding relationship between the compensation amount and the load change; and determine the corresponding relationship between the change cost and the load change;

[0102] The difference between the compensation amount and the change cost is taken as the user benefit, thus obtaining the corresponding relationship between user benefit and load change.

[0103] In actual implementation, power grid companies usually provide financial compensation to users who participate in demand response. However, users who adjust their electricity consumption behavior will also incur inconvenience costs and possible production losses. Therefore, the corresponding relationship between the compensation amount and the load change can be determined. And the corresponding relationship between the variable cost and the load change , thus obtaining the corresponding relationship between user benefits and load changes .

[0104] In a possible implementation, the compensation amount is positively correlated with the load change. The compensation function can be expressed as: ,in is the compensation coefficient.

[0105] In one possible implementation, the change cost is positively correlated with the square of the load change. The cost function can be expressed as: ,in is the user cost coefficient.

[0106] The user's total utility (revenue) function can be expressed as:

[0107] In a possible implementation, based on the historical data of power grid frequency regulation, multiple frequency regulation times and a single maximum frequency regulation power are predicted, including:

[0108] The historical data of power grid frequency regulation is input into the trained machine learning model and / or linear regression model to obtain the multiple frequency regulation times and the single maximum frequency regulation power output by the machine learning model and / or linear regression model.

[0109] In the specific implementation, the power grid multiple frequency modulation time and the single maximum frequency modulation power, load baseline, and electricity price changes can all be predicted. By inputting historical data into the prediction model, the power grid multiple frequency modulation time and the single maximum frequency modulation power, load baseline, and electricity price changes can be predicted. Among them, the prediction model can be a linear regression model, or a machine learning model such as a long short-term memory network (Long Short-Term Memory, referred to as LSTM), or a hybrid model consisting of a machine learning model and a linear regression model.

[0110] Among them, the linear regression model can be: , where y is the prediction target, such as the power grid frequency regulation time, frequency regulation power, load baseline or electricity price change; a0 is the intercept term; x1, x2, ..., xn are independent variables, such as historical electricity prices, historical electricity loads, historical weather data, historical power grid frequency regulation data, etc.; a1, a2, ..., an are regression coefficients, indicating the contribution of each independent variable to the prediction target; b is the error term, indicating the variability not captured by the model. When training the linear regression model, historical data can be obtained, including but not limited to historical electricity prices, historical electricity loads, historical weather data, historical power grid frequency regulation data, etc. Based on historical data, the least squares method is used for model training, and the prediction performance of the trained linear regression model is evaluated by methods such as cross-validation.

[0111] When training a machine learning model, the acquired historical data can be preprocessed, including but not limited to cleaning, conversion, and normalization. The preprocessed historical data is divided into a training set, a validation set, and a test set. The machine learning model is trained based on the training set. According to the performance of the machine learning model on the validation set, the hyperparameters or network structure are adjusted to improve the prediction accuracy of the model. Finally, the test set can be used to evaluate the performance of the trained machine learning model.

[0112] Furthermore, the machine learning model and the linear regression model are trained separately, and the machine learning model and the linear regression model with better prediction performance can be selected as sub-models of the prediction model at different times, thereby obtaining a hybrid model. For example, a sub-model can be corresponding to each month, such as using a machine learning model in January, February, and April, and a linear regression model in March, May, and June, thereby obtaining a hybrid model.

[0113] In the embodiment of the present application, the model can accurately predict the grid frequency modulation situation, so that the charging and discharging strategy can be effectively formulated according to the predicted grid frequency modulation situation, which is beneficial to improving the stability and reliability of power supply.

[0114] The embodiment of the present application also provides an energy storage control system. Figure 5 This is a schematic diagram of the structure of the energy storage control system provided in the embodiment of the present application. Figure 5 As shown, the system includes: a data center, an edge computing node and an energy storage device;

[0115] A data center, for determining a load change threshold corresponding to the maximum user benefit value according to an incentive mechanism; wherein the load change includes the difference between the incentive load and the load baseline, the incentive load includes the power load of the energy storage device within a predetermined time when there is an incentive mechanism, and the load baseline includes the power load of the energy storage device within a predetermined time when there is no incentive mechanism; and, according to whether the current power grid is in a frequency modulation state, the current reserved power of the energy storage device, the current load change and the current electricity price, sending a control instruction to the edge computing node;

[0116] The edge computing node is used to control the energy storage device to charge or not charge according to the control instructions.

[0117] In the specific implementation, the data center (such as the cloud platform) is used to make predictions based on historical data, and formulate charging and discharging plans based on the predicted data such as the grid frequency modulation time, frequency modulation power, load baseline, and electricity price changes; the edge computing node is used to receive the charging and discharging plan issued by the data center, and control the charging and discharging operations of the energy storage equipment in real time, and monitor the operating status of the energy storage system and grid frequency changes, and report them to the data center in a timely manner; the energy storage equipment is equipped with an intelligent control system, which receives and executes the control instructions of the edge computing node to perform charging and discharging operations, and provides a status monitoring interface to facilitate the edge computing node to obtain the operating status information of the energy storage equipment in real time.

[0118] The energy storage control system provided in the embodiment of the present application is used to execute the energy storage control method as described above. The specific implementation method is as described above and will not be repeated here.

[0119] Figure 6 Schematic diagram of the structure of an electronic device provided in an embodiment of the present application. The electronic device may be a data center or edge computing node as described above. Figure 6 As shown, the electronic device includes:

[0120] The electronic device includes a processor 291 and a memory 292; it may also include a communication interface 293 and a bus 294. The processor 291, the memory 292, and the communication interface 293 may communicate with each other through the bus 294. The communication interface 293 may be used for information transmission. The processor 291 may call the logic instructions in the memory 292 to execute the method of the above embodiment.

[0121] In addition, the logic instructions in the above-mentioned memory 292 can be implemented in the form of software functional units and can be stored in a computer-readable storage medium when sold or used as an independent product.

[0122] The memory 292 is a computer-readable storage medium that can be used to store software programs and computer executable programs, such as program instructions / modules corresponding to the methods in the embodiments of the present application. The processor 291 executes functional applications and data processing by running the software programs, instructions, and modules stored in the memory 292, that is, implementing the methods in the above method embodiments.

[0123] The memory 292 may include a program storage area and a data storage area, wherein the program storage area may store an operating system and an application required for at least one function; the data storage area may store data created according to the use of the terminal device, etc. In addition, the memory 292 may include a high-speed random access memory and may also include a non-volatile memory.

[0124] An embodiment of the present application provides a non-temporary computer-readable storage medium, in which computer-executable instructions are stored. When the computer-executable instructions are executed by a processor, they are used to implement the method described in the above embodiment.

[0125] An embodiment of the present application provides a computer program product, including a computer program. When the computer program is executed by a processor, the method provided in any embodiment of the present application is implemented.

[0126] Those skilled in the art will readily appreciate other embodiments of the present application after considering the specification and practicing the invention disclosed herein. The present application is intended to cover any modification, use or adaptation of the present application, which follows the general principles of the present application and includes common knowledge or customary techniques in the art that are not disclosed in the present application. The specification and examples are intended to be exemplary only, and the true scope and spirit of the present application are indicated by the following claims.

[0127] It should be understood that the present application is not limited to the precise structures that have been described above and shown in the drawings, and that various modifications and changes may be made without departing from the scope thereof. The scope of the present application is limited only by the appended claims.

Claims

1. A method for controlling energy storage, characterized in that: include: Determine the minimum reserved power for energy storage equipment based on historical data of grid frequency regulation; According to the incentive mechanism, determine the load change threshold corresponding to the maximum user benefit value; wherein the load change includes the difference between the incentive load and the load baseline, the incentive load includes the power load of the energy storage device within a predetermined time when there is an incentive mechanism, and the load baseline includes the power load of the energy storage device within a predetermined time when there is no incentive mechanism; If the current power grid is not in frequency regulation state, and the current reserved power of the energy storage device is less than the minimum reserved power, Alternatively, if the current power grid is not in a frequency modulation state, and the current reserved power of the energy storage device is not less than the minimum reserved power, and the current load change is greater than the load change threshold, and the current electricity price is less than the preset electricity price threshold, then the energy storage device is controlled to charge; Otherwise, the energy storage device is controlled not to be charged.

2. The method according to claim 1, characterized in that Determining the minimum reserved power of the energy storage device based on the historical data of power grid frequency regulation includes: According to the historical data of power grid frequency regulation, the multiple frequency regulation times and the single maximum frequency regulation power of the power grid are predicted; The minimum reserved power of the energy storage device is determined according to the multiple frequency modulation times and the single maximum frequency modulation power.

3. The method according to claim 2, characterized in that The determining, according to the multiple frequency modulation times and the single maximum frequency modulation power, of the minimum reserved power of the energy storage device includes: Calculating a minimum frequency modulation interval according to the multiple frequency modulation times; If the energy storage device can be charged to the single maximum frequency modulation power within the minimum frequency modulation interval, the minimum reserved power is determined to be the first power, and the first power is not less than the single maximum frequency modulation power.

4. The method according to claim 3, characterized in that The method further comprises: If the energy storage device cannot be charged to the single maximum frequency modulation capacity within the minimum frequency modulation interval, and the next frequency modulation time interval corresponding to the current time is greater than the minimum frequency modulation interval, then determining that the current minimum reserved capacity is the first capacity; If the energy storage device cannot be charged to the single maximum frequency modulation power within the minimum frequency modulation interval, and the next frequency modulation time interval corresponding to the current time is not greater than the minimum frequency modulation interval, the current minimum reserved power is determined to be the second power, and the second power is not less than twice the single maximum frequency modulation power.

5. The method according to claim 4, characterized in that The first amount of electricity is the product of one plus the sum of the preset redundancy and the single maximum frequency modulation amount, and the second amount of electricity is the product of two plus the sum of the preset redundancy and the single maximum frequency modulation amount.

6. The method according to claim 1, characterized in that Determining the load change threshold corresponding to the maximum user benefit value according to the incentive mechanism includes: According to the incentive mechanism, the corresponding relationship between user benefits and load changes is determined, and the load change value corresponding to the maximum user benefit value is used as the load change threshold; The load change satisfies a grid balance condition, and the grid balance condition includes: The absolute value of the demand load minus the grid power generation minus the load change is not greater than the preset load deviation threshold; the demand load includes the power load target of the energy storage device within the predetermined time, and the grid power generation includes the power generation of the grid within the second preset time.

7. The method according to claim 6, characterized in that Determining the corresponding relationship between user benefits and load changes according to the incentive mechanism includes: According to the incentive mechanism, determining the corresponding relationship between the compensation amount and the load change; and determining the corresponding relationship between the change cost and the load change; The difference between the compensation amount and the change cost is taken as the user benefit, thereby obtaining the corresponding relationship between the user benefit and the load change.

8. The method according to claim 7, characterized in that The compensation amount is proportional to the load change, and the change cost is proportional to the square of the load change.

9. The method according to any one of claims 2 to 5, characterized in that: The prediction of multiple frequency regulation times and a single maximum frequency regulation power according to the historical data of power grid frequency regulation includes: The power grid frequency modulation historical data is input into a trained machine learning model and / or a linear regression model to obtain the multiple frequency modulation times and the single maximum frequency modulation power output by the machine learning model and / or the linear regression model.

10. An energy storage control system, characterized in that: The energy storage control system is used to execute the energy storage control method according to any one of claims 1 to 9 above, and the energy storage control system includes: a data center, an edge computing node and an energy storage device; The data center is used to determine the load change threshold corresponding to the maximum user benefit value according to the incentive mechanism; wherein the load change includes the difference between the incentive load and the load baseline, the incentive load includes the power load of the energy storage device within a predetermined time when there is an incentive mechanism, and the load baseline includes the power load of the energy storage device within a predetermined time when there is no incentive mechanism; and, according to whether the current power grid is in a frequency modulation state, the current reserved power of the energy storage device, the current load change and the current electricity price, send a control instruction to the edge computing node; The edge computing node is used to control the energy storage device to charge or not charge according to the control instruction.

11. An electronic device, characterized in that: include: A processor, and a memory communicatively connected to the processor; The memory stores computer-executable instructions; The processor executes the computer-executable instructions stored in the memory to implement the method according to any one of claims 1 to 9.

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