Data processing method, device and equipment based on energy storage equipment and storage medium

Abstract

The embodiment of the invention provides a data processing method and device based on energy storage equipment, equipment and a storage medium. The method comprises the following steps: acquiring first information, power information and load information; the first information represents resources obtained by providing unit electric energy by the energy storage equipment; the power information represents the power of the energy storage equipment at the current moment; the load information represents the load of the power grid in a first preset time period; determining reference information according to the first information; determining first candidate power corresponding to a preset strategy based on the preset strategy according to the power information and the load information; the first candidate power represents the power of the energy storage equipment in a second preset time period based on a preset strategy; determining weight information of each preset strategy according to the reference information and the first candidate power corresponding to each preset strategy; and generating a target power supply strategy according to the weight information of each preset strategy and the first candidate power corresponding to each preset strategy. The method is used for improving the data processing accuracy of the energy storage equipment.

Description

Technical Field

[0001] This application relates to the field of power electronics technology, and in particular to a data processing method, apparatus, device and storage medium based on energy storage equipment. Background Technology

[0002] With the global energy structure transformation, energy storage devices, especially industrial and commercial energy storage devices, have become an important energy supply tool in the power grid.

[0003] In related technologies, when using energy storage devices to supply power, only a single power adjustment strategy is relied upon to adjust the power provided by the energy storage device. Therefore, the accuracy of power adjustment is not high, which may result in the energy storage device providing too much or too little electrical energy. Therefore, how to improve the accuracy of the power provided by energy storage devices has become an urgent technical problem to be solved. Summary of the Invention

[0004] This application provides a data processing method, apparatus, device, and storage medium based on energy storage devices, in order to improve the accuracy of data processing in energy storage devices.

[0005] In a first aspect, embodiments of this application provide a data processing method based on an energy storage device, including:

[0006] The system acquires first information, power information, and load information; the first information represents the resources obtained by the energy storage device for providing a unit of electrical energy; the power information represents the power of the energy storage device at the current moment; the load information represents the load of the power grid within a first preset time period; the first preset time period includes the current moment.

[0007] Based on the first information, reference information is determined; and based on the power information and the load information, a first candidate power corresponding to the preset strategy is determined; the reference information represents the power of the energy storage device within the expected second preset time period; the preset strategy represents the power adjustment strategy of the energy storage device; there are multiple preset strategies; the first candidate power represents the power of the energy storage device within the second preset time period based on the preset strategy; the first preset time period includes the second preset time period; the second preset time period is located after the current time.

[0008] Based on the reference information and the first candidate power corresponding to each preset strategy, the weight information of each preset strategy is determined; the weight information characterizes the degree of influence of the preset strategy on the power adjustment of the energy storage device within the second preset time period.

[0009] A target power supply strategy is generated based on the weight information of each preset strategy and the first candidate power corresponding to each preset strategy; wherein, the target power supply strategy represents the power adjustment strategy of the energy storage device within a second preset time period.

[0010] Secondly, embodiments of this application provide a data processing apparatus based on an energy storage device, comprising:

[0011] The acquisition module is used to acquire first information, power information, and load information; the first information represents the resources obtained by the energy storage device for providing a unit of electrical energy; the power information represents the power of the energy storage device at the current moment; the load information represents the load of the power grid within a first preset time period; the first preset time period includes the current moment;

[0012] A first determining module is configured to determine reference information based on the first information; and to determine a first candidate power corresponding to the preset strategy based on the power information and the load information and a preset strategy; the reference information represents the power of the energy storage device within a expected second preset time period; the preset strategy represents the power adjustment strategy of the energy storage device; there are multiple preset strategies; the first candidate power represents the power of the energy storage device within a second preset time period based on the preset strategy; the first preset time period includes the second preset time period; the second preset time period is located after the current time.

[0013] The second determining module is used to determine the weight information of each preset strategy based on the reference information and the first candidate power corresponding to each preset strategy; the weight information represents the degree of influence of the preset strategy on the power adjustment of the energy storage device within a second preset time period.

[0014] The generation module is used to generate a target power supply strategy based on the weight information of each preset strategy and the first candidate power corresponding to each preset strategy; wherein, the target power supply strategy represents the power adjustment strategy of the energy storage device within a second preset time period.

[0015] Thirdly, embodiments of this application provide a data processing device based on an energy storage device, including: a memory and a processor;

[0016] The memory stores computer-executed instructions;

[0017] The processor executes computer execution instructions stored in the memory, causing the processor to perform the first aspect and / or various possible implementations of the first aspect as described above.

[0018] Fourthly, embodiments of this application provide a computer-readable storage medium storing computer-executable instructions, which, when executed by a processor, are used to implement the first aspect and / or various possible implementations of the first aspect.

[0019] Fifthly, embodiments of this application provide a computer program product, including a computer program that, when executed by a processor, implements the first aspect and / or various possible implementations of the first aspect.

[0020] The data processing method, apparatus, device, and storage medium based on energy storage devices provided in this application acquire first information, power information, and load information. The acquired first information facilitates the conversion of electrical energy provided by the energy storage device into valuable resources during subsequent data processing, thereby better evaluating the power supply strategy of the energy storage device for a pre-set future period. The acquired load information facilitates subsequent analysis of the grid load fluctuations at the current moment, allowing for the matching of corresponding power adjustment strategies based on the current grid load fluctuations, and timely adjustment of the energy storage device's power supply strategy for a future period based on the acquired power information. Then, reference information is determined based on the first information. This reference information serves as the expected power of the energy storage device within a second preset time period, providing an initial baseline value for subsequent refined data adjustments. Furthermore, based on the power information and load information, and according to preset strategies, first candidate power corresponding to each preset strategy is determined. The resulting first candidate power corresponding to each preset strategy provides multiple adjustment schemes for subsequent refined data adjustments. After obtaining the reference information and the first candidate power corresponding to each preset strategy, the weight information of each preset strategy is determined based on the reference information and the first candidate power corresponding to each preset strategy. This transforms the first candidate power corresponding to each preset strategy into weight information representing the degree of influence of the preset strategy on the power adjustment of the energy storage device within a second preset time period, thus providing a data foundation for subsequent refined data adjustments. Finally, based on the weight information of each preset strategy and the first candidate power corresponding to each preset strategy, a target power supply strategy is generated. This ensures that when setting the power supply strategy of the energy storage device for a future period, multiple preset strategies are fully considered, i.e., multiple factors are comprehensively considered. This improves the accuracy of data processing for the energy storage device and solves the technical problem in related technologies where considering only a single strategy leads to inaccurate power settings for the energy storage device. Attached Figure Description

[0021] The accompanying drawings, which are incorporated in and form part of this specification, illustrate embodiments consistent with this application and, together with the description, serve to explain the principles of this application.

[0022] Figure 1 A flowchart illustrating the data processing method based on energy storage devices provided in this application embodiment. Figure 1 ;

[0023] Figure 2A flowchart illustrating the data processing method based on energy storage devices provided in this application embodiment. Figure 2 ;

[0024] Figure 3 A flowchart illustrating the data processing method based on energy storage devices provided in this application embodiment. Figure 3 ;

[0025] Figure 4 A schematic diagram of the process for generating a target power supply strategy provided in an embodiment of this application;

[0026] Figure 5 A schematic diagram of the structure of a data processing device based on an energy storage device provided in an embodiment of this application;

[0027] Figure 6 This is a schematic diagram of the structure of a data processing device based on an energy storage device provided in an embodiment of this application.

[0028] The accompanying drawings have illustrated specific embodiments of this application, which will be described in more detail below. These drawings and descriptions are not intended to limit the scope of the concept in any way, but rather to illustrate the concept of this application to those skilled in the art through reference to specific embodiments. Detailed Implementation

[0029] Exemplary embodiments will now be described in detail, examples of which are illustrated in the accompanying drawings. When the following description relates to the drawings, unless otherwise indicated, the same numbers in different drawings denote the same or similar elements. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with this application. Rather, they are merely examples of apparatuses and methods consistent with some aspects of this application as detailed in the appended claims.

[0030] With the deepening of global energy structure transformation and electricity market reform, energy storage devices, especially industrial and commercial energy storage devices, have become important tools for enterprises to optimize energy costs and improve energy flexibility. Currently, the operating environment of energy storage devices is becoming increasingly complex, requiring them to simultaneously cope with multiple dynamic factors such as load fluctuations, changes in equipment health status, and adjustments in market rules. For example, during peak electricity demand periods, rapid response to peak shaving commands is necessary while avoiding transformer overload; when photovoltaic output fluctuates, the charging and discharging strategies of energy storage devices need to be dynamically adjusted to balance grid power. Furthermore, battery life affects the power supply of energy storage devices; frequent high-rate charging and discharging, while providing more energy, significantly shortens battery life.

[0031] In related technologies, relying on a single strategy to adjust the power supply of energy storage devices lacks synergistic optimization between different strategies and fails to comprehensively consider multiple factors such as market rules, load, and equipment status. This can lead to the energy storage device providing too much or too little power. Furthermore, relying on a single strategy to adjust the power supply of energy storage devices does not take into account battery damage, resulting in shorter battery life and affecting the long-term power supply of the energy storage device.

[0032] The data processing method, apparatus, equipment, and storage medium based on energy storage devices provided in this application are intended to solve the aforementioned technical problems.

[0033] The technical solution of this application and how it solves the above-mentioned technical problems will be described in detail below with specific embodiments. These specific embodiments can be combined with each other, and the same or similar concepts or processes may not be described again in some embodiments. The embodiments of this application will be described below with reference to the accompanying drawings.

[0034] Figure 1 A flowchart illustrating the data processing method based on energy storage devices provided in this application embodiment. Figure 1 ,like Figure 1 As shown, the method includes:

[0035] S101. Obtain first information, power information, and load information; the first information represents the resources obtained by the energy storage device for providing a unit of electrical energy; the power information represents the power of the energy storage device at the current moment; the load information represents the load of the power grid within a first preset time period; the first preset time period includes the current moment.

[0036] This application can be applied to electronic devices to pre-set the power supply strategy of energy storage devices for a future period of time in order to better manage energy storage devices.

[0037] For example, a timer can be pre-set to issue control commands at fixed time intervals, instructing the energy storage device to update its power supply strategy. In response to receiving the control command, first information is acquired, representing the resources obtained by the energy storage device for providing a unit of electrical energy. For instance, the first information could be the price per unit of electrical energy. This first information is obtained from the power system through a pre-defined first interface. Using this first information, the electrical energy provided by the energy storage device can be converted into valuable resources, thereby better evaluating the energy storage device's power supply strategy for a pre-set future period.

[0038] Simultaneously, power and load information are acquired. Power information represents the power of the energy storage device at the current moment, such as the discharge or charging power of the device. Load information represents the grid load within a first preset time period, such as the grid load fluctuation curve within that period, which includes the current moment. In other words, the load information includes the grid load fluctuation curve over a historical period and also the grid load fluctuation curve over a future period. By analyzing the load information, the grid load fluctuation at the current moment can be analyzed, and corresponding power adjustment strategies can be matched based on this fluctuation. This allows for timely adjustments to the energy storage device's power supply strategy for the future period, based on the power information.

[0039] For example, power information can be obtained from the management system of an energy storage device through a pre-defined second interface. Similarly, load information can be obtained from the power system through a pre-defined third interface. The pre-defined first, second, and third interfaces can be different. The load information represents the grid load within a first pre-defined time period, which includes both historical and future periods. The grid load within the historical period can be the load recorded at historical moments, while the grid load within the future period can be the predicted load based on the historical load. For instance, the power system may include a pre-trained artificial intelligence model. This pre-trained AI model, after training, possesses inference capabilities and can predict the grid load within a future period based on the historical load. The pre-defined third interface can be used to invoke the pre-defined AI model to obtain the load information.

[0040] S102. Based on the first information, determine the reference information; and based on the power information and load information, determine the first candidate power corresponding to the preset strategy; the reference information represents the expected power of the energy storage device within the second preset time period; the preset strategy represents the power adjustment strategy of the energy storage device; there are multiple preset strategies; the first candidate power represents the power of the energy storage device within the second preset time period based on the preset strategy; the first preset time period includes the second preset time period; the second preset time period is located after the current time.

[0041] For example, after obtaining the first information, reference information is determined based on the first information. The reference information represents the power of the energy storage device within a anticipated second preset time period. The first preset time period includes the second preset time period, which is located after the current time. That is, the reference information can be the power of the energy storage device within a anticipated future time period.

[0042] For example, since the first information represents the resources obtained by the energy storage device for providing a unit of electrical energy, if the power of the energy storage device within a second preset time period is known, the electrical energy provided by the energy storage device within the second preset time period can be obtained. Therefore, the total resources obtained by the energy storage device within the second preset time period can be analyzed using the first information and the power of the energy storage device within the second preset time period. It can be expected that the total resources obtained by the energy storage device can be maximized. Therefore, based on the first information, and to maximize the total resources obtained by the energy storage device, reference information can be determined, i.e., the expected power of the energy storage device within the second preset time period can be obtained. The reference information can be used as an initial base value. Based on this, multiple power adjustment strategies are analyzed, and the reference information is adjusted to obtain a power that considers multiple power adjustment strategies. This power is then used as the power of the energy storage device within the second preset time period, which can solve the technical problem in related technologies where considering only a single strategy leads to inaccurate power settings for the energy storage device.

[0043] After obtaining power and load information, the first candidate power corresponding to the preset strategy can be determined based on the power information and the load information, according to the preset strategy. The preset strategy represents the power adjustment strategy of the energy storage device. There are multiple preset strategies, meaning the power of the energy storage device can be adjusted according to one or more of them. The first candidate power represents the power of the energy storage device within a second preset time period based on the preset strategy; that is, the power of the energy storage device within the second preset time period determined based on the preset strategy.

[0044] For each preset strategy, a first candidate power is obtained. This first candidate power is the power of the energy storage device within a second preset time period determined based on the preset strategy. For example, if the preset strategy is to charge the energy storage device during off-peak hours and discharge it during peak hours, the load fluctuation curve in the load information can be used to determine whether the current time is during an off-peak or peak period. If it is determined that the current time is during an off-peak period, the energy storage device needs to be charged. Therefore, the power of the energy storage device can be lowered based on the current power information to obtain the first candidate power for charging. If it is determined that the current time is during a peak period, the energy storage device needs to be discharged. Therefore, the power of the energy storage device can be increased based on the current power information to obtain the first candidate power for discharging. Each first candidate power is a power obtained based on a preset strategy, and these first candidate powers provide data support for subsequent analysis of multiple preset strategies.

[0045] S103. Based on the reference information and the first candidate power corresponding to each preset strategy, determine the weight information of each preset strategy; the weight information represents the degree of influence of the preset strategy on the power adjustment of the energy storage device within the second preset time period.

[0046] For example, reference information can be used as a benchmark to sequentially compare the difference between each first candidate power and the reference information. The smaller the difference, the closer the power of the energy storage device within the second preset time period, based on the preset strategy corresponding to the first candidate power, is to the expected value. This indicates that the first candidate power is closer to the ideal value, and therefore, the preset strategy corresponding to the first candidate power is a more suitable strategy for the current moment. Conversely, the preset strategy corresponding to the first candidate power is a less suitable strategy for the current moment.

[0047] Therefore, the weight information of each preset strategy can be determined based on the difference between the reference information and the first candidate power corresponding to each preset strategy. The weight information characterizes the degree of influence of the preset strategy on the power adjustment of the energy storage device within the second preset time period. For example, the greater the difference, the smaller the weight information of the preset strategy, and the less suitable the preset strategy is for the current moment; that is, the smaller the influence of the preset strategy on the power adjustment of the energy storage device within the second preset time period. Conversely, the smaller the difference, the larger the weight information of the preset strategy, and the more suitable the preset strategy is for the current moment; that is, the greater the influence of the preset strategy on the power adjustment of the energy storage device within the second preset time period.

[0048] By generating weight information for each preset strategy, guidance information is provided for generating the power adjustment strategy of the energy storage device in the second preset time period, so that the final strategy used is the one most suitable for the current moment.

[0049] S104. Generate a target power supply strategy based on the weight information of each preset strategy and the first candidate power corresponding to each preset strategy; wherein, the target power supply strategy represents the power adjustment strategy of the energy storage device within the second preset time period.

[0050] Assuming the power of the energy storage device within the final second preset time period is obtained, the first candidate power of each preset strategy can be compared with the power of the energy storage device within the final second preset time period. If the weight information of the preset strategy is greater, the difference between the first candidate power of the preset power and the power of the energy storage device within the final second preset time period should be smaller, thereby ensuring that the preset strategy has a greater impact on the power of the energy storage device within the final second preset time period.

[0051] Therefore, the power of the energy storage device within the final second preset time period can be set as an unknown parameter. The difference between the first candidate power of each preset strategy and the power of the energy storage device within the final second preset time period can be calculated. Using the weight information of the preset strategy as the weight of the difference value, all difference values ​​are weighted and summed to obtain a total difference value. Based on minimizing the total difference value, the power of the energy storage device within the final second preset time period is obtained. The energy storage device will supply power according to the power of the energy storage device within the final second preset time period, thus obtaining the target power supply strategy. Therefore, when setting the power supply strategy of the energy storage device for a future period, multiple preset strategies are fully considered, that is, multiple factors are comprehensively considered, thereby solving the technical problem in related technologies where considering only a single strategy leads to inaccurate power settings for the energy storage device.

[0052] The data processing method based on energy storage devices provided in this application acquires first information, power information, and load information. The acquired first information facilitates the conversion of electrical energy provided by the energy storage device into valuable resources during subsequent data processing, thereby better evaluating the power supply strategy of the energy storage device over a pre-set future period. The acquired load information facilitates subsequent analysis of the grid load fluctuations at the current moment, allowing for the matching of corresponding power adjustment strategies based on the current grid load fluctuations. This enables timely adjustment of the energy storage device's power supply strategy over a future period based on the acquired power information. Next, reference information is determined based on the first information. This reference information serves as the expected power of the energy storage device within a second preset time period, providing an initial baseline value for subsequent refined data adjustments. Furthermore, based on the power information and load information, and according to preset strategies, first candidate power corresponding to each preset strategy is determined. The resulting first candidate power corresponding to each preset strategy provides multiple adjustment schemes for subsequent refined data adjustments. After obtaining the reference information and the first candidate power corresponding to each preset strategy, the weight information of each preset strategy is determined based on the reference information and the first candidate power corresponding to each preset strategy. This transforms the first candidate power corresponding to each preset strategy into weight information representing the degree of influence of the preset strategy on the power adjustment of the energy storage device within a second preset time period, thus providing a data foundation for subsequent refined data adjustments. Finally, based on the weight information of each preset strategy and the first candidate power corresponding to each preset strategy, a target power supply strategy is generated. This ensures that when setting the power supply strategy of the energy storage device for a future period, multiple preset strategies are fully considered, i.e., multiple factors are comprehensively considered. This improves the accuracy of data processing for the energy storage device and solves the technical problem in related technologies where considering only a single strategy leads to inaccurate power settings for the energy storage device.

[0053] Figure 2A flowchart illustrating the data processing method based on energy storage devices provided in this application embodiment. Figure 2 ,like Figure 2 As shown, the above-mentioned determination of reference information based on the first information includes: generating at least two second candidate powers based on a preset power range; the second candidate power represents the power of the energy storage device generated within a second preset time period within the preset power range; for each second candidate power, determining the value information corresponding to the second candidate power based on the second candidate power and the first information; the value information represents the actual resources obtained by the energy storage device under the second candidate power within the second preset time period; and determining reference information from the at least two second candidate powers based on the value information corresponding to each second candidate power. The method includes:

[0054] S201, Obtain first information, power information, and load information.

[0055] S202. Based on a preset power range, generate at least two second candidate powers; the second candidate power represents the power of the energy storage device generated within a second preset time period within the preset power range.

[0056] For example, within a preset power range, a random algorithm can be invoked to randomly generate at least two second candidate power values. The random algorithm is used to generate the second candidate power values ​​within the preset power range. The preset power range can be determined based on the constraints that the power of the energy storage device needs to meet. For example, the constraints include that the power of the energy storage device is greater than or equal to the minimum allowable power value and less than or equal to the maximum allowable power value. Therefore, the range between the minimum allowable power value and the maximum allowable power value can be used as the preset power range. It should be noted that, to ensure that the power of the energy storage device does not exceed the physical limits of the energy storage device, the constraints may also include that the battery's state of charge (SOC) is within a preset SOC range, etc.

[0057] Each of the at least two second candidate powers generated can be used as a candidate value for the power of the energy storage device within the final generated preset second preset time period.

[0058] S203. For each second candidate power, determine the value information corresponding to the second candidate power based on the second candidate power and the first information; the value information represents the actual resources obtained by the energy storage device under the second candidate power within the second preset time period.

[0059] For example, for each second candidate power, the electrical energy provided by the energy storage device within the second preset time period under the second candidate power can be obtained by multiplying the second candidate power by the second preset time period. Since the first information characterizes the resources obtained by the energy storage device for providing a unit of electrical energy, the total resources obtained by the energy storage device for providing electrical energy within the second preset time period under the second candidate power can be obtained based on the second candidate power and the first information. This total resource can be used as the value information corresponding to the second candidate power. The value information characterizes the actual resources obtained by the energy storage device under the second candidate power within the second preset time period, that is, the final amount of resources obtained when the power of the energy storage device is the second candidate power within the second preset time period.

[0060] S204. Based on the value information corresponding to each second candidate power, determine reference information from at least two second candidate powers.

[0061] For example, the value information corresponding to each second candidate power can be sorted from smallest to largest, and the second candidate power with the largest value information can be used as reference information.

[0062] The advantage of this setting is that by using the second candidate information with the highest value as the reference information, it is ensured that the reference information, which serves as the initial base value, can maximize the value of the energy storage device within the preset second time period. In the subsequent fine-tuning process based on this, it can be ensured that the final target power supply strategy can fully consider multiple preset strategies while also maximizing the value of the energy storage device as much as possible.

[0063] In this embodiment of the application, the determination of the value information corresponding to the second candidate power based on the second candidate power and the first information includes:

[0064] Based on the second candidate power and the first information, revenue information is determined; the revenue information represents the initial resources obtained by the energy storage device under the second candidate power within the second preset time period; based on the second candidate information and preset battery information, cost information is determined; the preset battery information represents the battery loss parameters of the energy storage device; the cost information represents the resources consumed by the battery loss of the energy storage device within the second preset time period; based on the revenue information and cost information, the value information corresponding to the second candidate power is determined.

[0065] For example, the product of the second candidate power and the second preset time period can be used as the first electrical energy provided by the energy storage device within the second preset time period under the second candidate power. Since the first information represents the resources obtained by the energy storage device for providing a unit of electrical energy, the product of the first electrical energy and the first information can be used as the revenue information, wherein the revenue information represents the initial resources obtained by the energy storage device under the second candidate power within the second preset time period, that is, the initial resources obtained within the second preset time period when the power of the energy storage device is set to the second candidate power.

[0066] Meanwhile, since energy storage devices consume resources due to battery wear during operation, these resources can be taken into account. After obtaining the first electrical energy based on the second candidate information, the product of the first electrical energy and preset battery information can be used as cost information. Cost information represents the resources consumed by the battery due to power supply from the energy storage device within a second preset time period. The preset battery information can be parameters pre-set based on the battery's health status.

[0067] Then, the difference between the revenue information and the cost information is determined as the value information corresponding to the second candidate power.

[0068] In some specific implementations, other resources resulting from the power adjustment of energy storage devices, such as market resources arising from the impact of power adjustment on market electricity usage and incentive resources arising from the impact of power adjustment on electricity usage, can also be included in the revenue information. That is, the revenue information can also include market resources and incentive resources.

[0069] The advantage of this setup is that when analyzing the value of energy storage devices at the second candidate power level, the resources consumed by battery losses are also included in the analysis, resulting in more accurate value information.

[0070] S205. Based on the power information and load information, determine the first candidate power corresponding to the preset strategy.

[0071] In this embodiment, the preset strategy is a first strategy, which is used to increase the power of the energy storage device during peak load periods of the power grid and decrease the power of the energy storage device during off-peak load periods of the power grid. The above-mentioned determination of the first candidate power corresponding to the preset strategy based on power information and load information includes:

[0072] If the load information determines that the current time is during the peak load period of the power grid, then the first candidate power corresponding to the preset strategy is determined based on the power information; the first candidate power corresponding to the preset strategy is greater than the power information. If the load information determines that the current time is during the off-peak load period of the power grid, then the first candidate power corresponding to the preset strategy is determined based on the power information; the first candidate power corresponding to the preset strategy is less than the power information.

[0073] For example, the preset strategy is a first strategy, which includes a preset adjustment algorithm used to adjust the power of the energy storage device. For instance, the preset adjustment algorithm adjusts the power of the energy storage device based on the load change rate. The greater the load change rate, the greater the power adjustment value of the energy storage device.

[0074] Based on the load fluctuation curve in the load information, it can be determined whether the current moment falls within the peak load period of the power grid. If the current moment does fall within the peak load period, the load change rate at the current moment can be calculated based on the load fluctuation curve in the load information, which is designated as the first rate. By calling the preset adjustment algorithm in the first strategy, the power adjustment value corresponding to the first rate is obtained. At this time, the power adjustment value corresponding to the first rate is positive, meaning that the power of the energy storage device needs to be increased. The sum of the power information and the power adjustment value corresponding to the first rate can be used as the first candidate power corresponding to the preset strategy, so that the first candidate power is greater than the power information.

[0075] If the current time falls during a period of low load on the power grid, the rate of load change at the current moment can be calculated based on the load fluctuation curve in the load information, which is the second rate. By calling the preset adjustment algorithm in the first strategy, the power adjustment value corresponding to the second rate is obtained. At this time, the power adjustment value corresponding to the second rate is negative, that is, the power of the energy storage device needs to be reduced. The sum of the power information and the power adjustment value corresponding to the second rate can be used as the first candidate power corresponding to the preset strategy, so that the first candidate power is less than the power information.

[0076] It should be noted that the preset strategies are derived from a preset strategy library, which includes multiple power adjustment strategies. The preset strategy can also be any other power adjustment strategy in the library. The preset strategy library supports real-time updates, and the preset strategies can be updated synchronously with the updated library. Each preset strategy corresponds to its own preset adjustment algorithm, and different preset strategies may correspond to different preset adjustment algorithms.

[0077] For example, the preset strategy could also be a second strategy. This second strategy is used to maintain grid stability when the grid's power is too high, and the load cannot consume the excess power, causing excess power to flow back into the upstream grid. This is achieved by preventing the energy storage device from discharging. The second strategy includes a preset adjustment algorithm. In this algorithm, when it is determined that the grid's power is too high and the load cannot consume the excess power, causing excess power to flow back into the upstream grid, the power of the energy storage device is reduced to prevent it from discharging. Therefore, by analyzing the load fluctuation curve in the load information, it can be calculated whether the current situation of excessive grid power, insufficient load consumption, and excess power flowing back into the upstream grid has occurred. If this situation occurs, the preset adjustment algorithm of the second strategy is invoked to reduce the power of the energy storage device.

[0078] The advantage of this setting is that, for different preset strategies, the power information can be finely adjusted according to the respective adjustment algorithms of the preset strategies to obtain the first candidate information corresponding to the preset strategy.

[0079] S206. Based on the reference information and the first candidate power corresponding to each preset strategy, determine the weight information of each preset strategy.

[0080] S207. Generate a target power supply strategy based on the weight information of each preset strategy and the first candidate power corresponding to each preset strategy.

[0081] Figure 3 A flowchart illustrating the data processing method based on energy storage devices provided in this application embodiment. Figure 3 ,like Figure 3 As shown, the weight information of each preset strategy is determined based on the reference information and the first candidate power corresponding to each preset strategy, including:

[0082] For each preset strategy, the difference between the first candidate power and the reference information is determined; based on the difference corresponding to each preset strategy, the weight information of each preset strategy is determined. The above method includes:

[0083] S301, Obtain first information, power information, and load information.

[0084] S302. Based on the first information, determine the reference information; and based on the power information and load information, determine the first candidate power corresponding to the preset strategy.

[0085] S303. For each preset strategy, determine the difference between the first candidate power and the reference information.

[0086] For example, for each preset strategy corresponding to a first candidate power, the difference between the first candidate power and the reference information can be calculated. The difference is an absolute value, and the magnitude of the difference reflects the degree of deviation between the first candidate power and the reference information. For instance, the larger the difference, the greater the deviation between the first candidate power and the reference information; the smaller the difference, the smaller the deviation between the first candidate power and the reference information.

[0087] S304. Determine the weight information of each preset strategy based on the difference between each preset strategy.

[0088] For example, the differences corresponding to all preset strategies can be sorted in ascending order, and weight information can be set for each preset strategy in turn based on preset rules. In the preset rules, the preset strategy that appears earlier in the list has a larger weight.

[0089] By calculating the difference between the first candidate power and the reference information for each preset strategy, the magnitude of the difference reflects the degree of deviation between the first candidate power and the reference information. Based on the difference corresponding to each preset strategy, the weight information of each preset strategy is determined. A larger weight information can be assigned to the first candidate power with the smaller difference, so that the first candidate power with the smaller difference provides more information when generating the target power supply strategy in the subsequent process, thereby ensuring the accuracy of the subsequently generated target power supply strategy.

[0090] S305. Generate a target power supply strategy based on the weight information of each preset strategy and the first candidate power corresponding to each preset strategy.

[0091] Figure 4 This is a schematic diagram of the process for generating a target power supply strategy provided in an embodiment of this application, such as... Figure 4 As shown, based on the weight information of each preset strategy and the first candidate power corresponding to each preset strategy, a target power supply strategy is generated, including:

[0092] S401. Based on a preset power range, generate at least two second candidate powers; the second candidate power represents the power of the energy storage device generated within a second preset time period within the preset power range.

[0093] The execution process of S401 is the same as that of S202 described above, and will not be repeated here.

[0094] S402. For each second candidate power, determine the deviation information based on the second candidate power, the first candidate power corresponding to each preset strategy, and the weight information corresponding to each preset strategy; the deviation information characterizes the degree of deviation between the second candidate power and all first candidate powers.

[0095] For example, for each second candidate power, it can be compared with the first candidate power corresponding to each preset strategy. The comparison result can be a weighted comparison result, such as the final comparison result obtained by multiplying the weight information corresponding to each preset strategy with the comparison result between the second candidate power and the preset strategy. Then, the final comparison results corresponding to all preset strategies are fused to obtain the deviation information. Here, the deviation information characterizes the degree of deviation between the second candidate power and all first candidate powers; that is, the deviation information measures the sum of the degree of deviation between the second candidate power and each first candidate power.

[0096] Specifically, in this embodiment, determining the deviation information based on the second candidate power, the first candidate power corresponding to each preset strategy, and the weight information corresponding to each preset strategy includes:

[0097] For each preset strategy, sub-information is determined based on the second candidate power, the first candidate power corresponding to the preset strategy, and the weight information corresponding to the preset strategy; the sub-information characterizes the degree of deviation between the second candidate power and the first candidate power corresponding to the preset strategy; deviation information is determined based on the sub-information corresponding to each preset strategy.

[0098] For example, for each preset strategy, sub-information is determined based on the second candidate power, the first candidate power corresponding to the preset strategy, and the weight information corresponding to the preset strategy. For instance, sub-information can be calculated using the following formula (1):

[0099] (1);

[0100] In the formula, This indicates the degree of deviation between the second candidate power and the first candidate power corresponding to the i-th preset strategy, i.e., sub-information; This represents the weight information corresponding to the i-th preset strategy; Indicates the power of the second candidate j; This represents the first candidate power corresponding to the i-th preset strategy.

[0101] Based on the sub-information corresponding to each preset strategy, the deviation information is determined. For example, the deviation information can be calculated according to the following formula (2):

[0102] (2);

[0103] In the formula, N represents the total number of preset strategies.

[0104] For each preset strategy, sub-information is determined based on the second candidate power, the first candidate power corresponding to the preset strategy, and the weight information corresponding to the preset strategy. This determined sub-information allows for a more precise quantification of the impact of the second candidate power for each preset strategy. Therefore, based on the sub-information corresponding to all preset strategies, more accurate bias information is obtained.

[0105] S403. Based on the deviation information corresponding to each second candidate power, determine the target power from multiple second candidate powers; the target power represents the power of the energy storage device within a second preset time period based on all preset strategies.

[0106] For example, the deviation information corresponding to all second candidate power can be sorted in ascending order, and the second candidate power with the smallest deviation information can be taken as the target power. The target power represents the power of the energy storage device within a second preset time period based on all preset strategies. That is, the target power is the final power of the energy storage device within the second preset time period, which integrates all preset strategies.

[0107] For example, the target power can be determined according to the following formula (3):

[0108] (3);

[0109] In the formula, min represents the minimization function.

[0110] S404. Generate the target power supply strategy based on the target power.

[0111] For example, the target power is taken as the final power of the energy storage device in the second preset time period. Based on this, a power command is generated and sent to the energy storage device. The power command instructs the control of the charging and discharging state of the converter of the energy storage device.

[0112] In this embodiment, at least two second candidate powers are generated based on a preset power range. For each second candidate power, deviation information is determined according to the second candidate power, the first candidate power corresponding to each preset strategy, and the weight information corresponding to each preset strategy. The deviation information can be used to quantify whether each second candidate power, as the power of the energy storage device within a second preset time period, fully considers all preset strategies. Then, based on the deviation information corresponding to each second candidate power, a target power is determined from the multiple second candidate powers, ensuring that the determined target power is the most accurate for analyzing all preset strategies. This improves the accuracy of the target power.

[0113] Figure 5 A schematic diagram of the structure of the data processing device based on energy storage equipment provided in the embodiments of this application is shown below. Figure 5As shown, the data processing device 50 based on energy storage equipment provided in this embodiment includes:

[0114] The acquisition module 501 is used to acquire first information, power information, and load information; the first information represents the resources obtained by the energy storage device for providing a unit of electrical energy; the power information represents the power of the energy storage device at the current moment; the load information represents the load of the power grid within a first preset time period; the first preset time period includes the current moment;

[0115] The first determining module 502 is used to determine reference information based on the first information; and to determine the first candidate power corresponding to the preset strategy based on the power information and load information and the preset strategy; the reference information represents the power of the energy storage device within the expected second preset time period; the preset strategy represents the power adjustment strategy of the energy storage device; there are multiple preset strategies; the first candidate power represents the power of the energy storage device within the second preset time period based on the preset strategy; the first preset time period includes the second preset time period; the second preset time period is located after the current time.

[0116] The second determining module 503 is used to determine the weight information of each preset strategy based on the reference information and the first candidate power corresponding to each preset strategy; the weight information represents the degree of influence of the preset strategy on the power adjustment of the energy storage device within the second preset time period.

[0117] The generation module 504 is used to generate a target power supply strategy based on the weight information of each preset strategy and the first candidate power corresponding to each preset strategy; wherein, the target power supply strategy represents the power adjustment strategy of the energy storage device within a second preset time period.

[0118] In one possible implementation, the first determining module 502 is further configured to:

[0119] Based on a preset power range, at least two second candidate powers are generated; the second candidate power represents the power of the energy storage device within a second preset time period generated within the preset power range.

[0120] For each second candidate power, the value information corresponding to the second candidate power is determined based on the second candidate power and the first information; the value information represents the actual resources obtained by the energy storage device under the second candidate power within the second preset time period;

[0121] Reference information is determined from at least two second candidate powers based on the value information corresponding to each second candidate power.

[0122] In one possible implementation, the first determining module 502 is further configured to:

[0123] Based on the second candidate power and the first information, the revenue information is determined; the revenue information represents the initial resources obtained by the energy storage device under the second candidate power within the second preset time period;

[0124] Cost information is determined based on the second candidate information and the preset battery information; the preset battery information represents the battery loss parameters of the energy storage device; the cost information represents the resources consumed by the battery loss of the energy storage device within the second preset time period.

[0125] Based on revenue and cost information, determine the value information corresponding to the second candidate power.

[0126] In one possible implementation, the preset strategy is a first strategy; the first strategy is used to increase the power of the energy storage device during peak load periods of the power grid and to decrease the power of the energy storage device during off-peak load periods of the power grid; the first determining module 502 is further used to:

[0127] If the load information determines that the current time is during the peak load period of the power grid, then the first candidate power corresponding to the preset strategy is determined based on the power information; the first candidate power corresponding to the preset strategy is greater than the power information.

[0128] In one possible implementation, the first determining module 502 is further configured to:

[0129] If the load information indicates that the current time is during a period of low load in the power grid, then the first candidate power corresponding to the preset strategy is determined based on the power information; the first candidate power corresponding to the preset strategy is less than the power information.

[0130] In one possible implementation, the second determining module 503 is further configured to:

[0131] For each preset strategy, determine the difference between the first candidate power and the reference information;

[0132] The weight information of each preset strategy is determined based on the difference between each preset strategy.

[0133] In one possible implementation, the generation module 504 is also used for:

[0134] Based on a preset power range, at least two second candidate powers are generated; the second candidate power represents the power of the energy storage device within a second preset time period generated within the preset power range.

[0135] For each second candidate power, deviation information is determined based on the second candidate power, the first candidate power corresponding to each preset strategy, and the weight information corresponding to each preset strategy; the deviation information characterizes the degree of deviation between the second candidate power and all first candidate powers.

[0136] Based on the deviation information corresponding to each second candidate power, the target power is determined from multiple second candidate powers; the target power represents the power of the energy storage device within a second preset time period based on all preset strategies;

[0137] Generate a target power supply strategy based on the target power.

[0138] In one possible implementation, the generation module 504 is also used for:

[0139] For each preset strategy, sub-information is determined based on the second candidate power, the first candidate power corresponding to the preset strategy, and the weight information corresponding to the preset strategy; the sub-information represents the degree of deviation between the second candidate power and the first candidate power corresponding to the preset strategy.

[0140] Based on the sub-information corresponding to each preset strategy, the deviation information is determined.

[0141] The data processing device based on energy storage equipment provided in this embodiment can execute the method provided in the above method embodiment. Its implementation principle and technical effect are similar, and will not be described in detail here.

[0142] Figure 6 This is a schematic diagram of the structure of a data processing device based on an energy storage device provided in an embodiment of this application. Figure 6 As shown, the data processing device 60 based on an energy storage device provided in this embodiment includes at least one processor 601 and a memory 602. Optionally, the data processing device 60 based on an energy storage device further includes a communication component 603. The processor 601, memory 602, and communication component 603 are connected via a bus.

[0143] In a specific implementation, at least one processor 601 executes computer execution instructions stored in memory 602, causing at least one processor 601 to perform the above-described method.

[0144] The specific implementation process of processor 601 can be found in the above method embodiments, and its implementation principle and technical effect are similar. It will not be repeated here.

[0145] In the above embodiments, it should be understood that the processor can be a Central Processing Unit (CPU), or other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), etc. The general-purpose processor can be a microprocessor or any conventional processor. The steps of the method disclosed in this invention can be directly implemented by a hardware processor, or implemented by a combination of hardware and software modules within the processor.

[0146] The memory may include random access memory (RAM) and may also include non-volatile memory (NVM), such as at least one disk storage device.

[0147] The bus can be an Industry Standard Architecture (ISA) bus, a Peripheral Component Interconnect (PCI) bus, or an Extended Industry Standard Architecture (EISA) bus, etc. Buses can be categorized as address buses, data buses, control buses, etc. For ease of illustration, the buses shown in the accompanying drawings are not limited to a single bus or a single type of bus.

[0148] This application also provides a computer program product, including a computer program that, when executed by a processor, implements the above-described method.

[0149] This application also provides a computer-readable storage medium storing computer-executable instructions, which, when executed by a processor, implement the above-described method.

[0150] The aforementioned readable storage medium can be implemented by any type of volatile or non-volatile storage device or a combination thereof, such as static random access memory (SRAM), electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable read-only memory (PROM), read-only memory (ROM), magnetic storage, flash memory, magnetic disk, or optical disk. The readable storage medium can be any available medium accessible to a general-purpose or special-purpose computer.

[0151] An exemplary readable storage medium is coupled to a processor, enabling the processor to read information from and write information to the readable storage medium. Of course, the readable storage medium can also be a component of the processor. The processor and the readable storage medium can reside in an Application Specific Integrated Circuit (ASIC). Alternatively, the processor and the readable storage medium can exist as discrete components in the device.

[0152] The division of units is merely a logical functional division; in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be indirect coupling or communication connection through some interfaces, devices, or units, and may be electrical, mechanical, or other forms.

[0153] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0154] In addition, the functional units in the various embodiments of the present invention can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit.

[0155] If a function is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this invention, or the part that contributes to the prior art, or a part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods of the various embodiments of this invention. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0156] Those skilled in the art will understand that all or part of the steps of the above-described method embodiments can be implemented by hardware related to program instructions. The aforementioned program can be stored in a computer-readable storage medium. When executed, the program performs the steps of the above-described method embodiments; and the aforementioned storage medium includes various media capable of storing program code, such as ROM, RAM, magnetic disks, or optical disks.

[0157] Finally, it should be noted that other embodiments of the invention will readily occur to those skilled in the art upon consideration of the specification and practice of the invention disclosed herein. This invention is intended to cover any variations, uses, or adaptations of the invention that follow the general principles of the invention and include common knowledge or customary techniques in the art not disclosed herein, and is not limited to the precise structures described above and shown in the accompanying drawings, and various modifications and changes can be made without departing from its scope. The scope of the invention is limited only by the appended claims.

Claims

1. A data processing method based on energy storage devices, characterized in that, include: Obtain initial information, power information, and load information; The first information represents the resources obtained by the energy storage device for providing a unit of electrical energy; The power information represents the power of the energy storage device at the current moment; the load information represents the load of the power grid within a first preset time period; the first preset time period includes the current moment; Based on the first information, determine the reference information; And based on the power information and the load information, a first candidate power corresponding to the preset strategy is determined based on the preset strategy; The reference information represents the power of the energy storage device within the expected second preset time period; The preset strategy characterizes the power adjustment strategy of the energy storage device; There are multiple preset strategies; the first candidate power represents the power of the energy storage device within a second preset time period based on the preset strategy; the first preset time period includes the second preset time period; the second preset time period is located after the current moment; Based on the reference information and the first candidate power corresponding to each preset strategy, the weight information of each preset strategy is determined; the weight information characterizes the degree of influence of the preset strategy on the power adjustment of the energy storage device within the second preset time period. A target power supply strategy is generated based on the weight information of each preset strategy and the first candidate power corresponding to each preset strategy; wherein, the target power supply strategy represents the power adjustment strategy of the energy storage device within a second preset time period.

2. The method according to claim 1, characterized in that, Based on the first information, reference information is determined, including: Based on a preset power range, at least two second candidate powers are generated; the second candidate power represents the power of the energy storage device generated within a second preset time period within the preset power range; For each second candidate power, value information corresponding to the second candidate power is determined based on the second candidate power and the first information; the value information represents the actual resources obtained by the energy storage device under the second candidate power within a second preset time period; The reference information is determined from the at least two second candidate powers based on the value information corresponding to each second candidate power.

3. The method according to claim 2, characterized in that, Based on the second candidate power and the first information, determine the value information corresponding to the second candidate power, including: Based on the second candidate power and the first information, revenue information is determined; the revenue information represents the initial resources obtained by the energy storage device under the second candidate power within a second preset time period; Cost information is determined based on the second candidate information and the preset battery information; the preset battery information represents the battery loss parameters of the energy storage device; the cost information represents the resources consumed by the battery loss of the energy storage device within a second preset time period. Based on the revenue information and the cost information, the value information corresponding to the second candidate power is determined.

4. The method according to claim 1, characterized in that, The preset strategy is a first strategy; the first strategy is used to increase the power of the energy storage device during peak load periods of the power grid and to decrease the power of the energy storage device during off-peak load periods of the power grid. Based on the power information and the load information, and according to a preset strategy, a first candidate power corresponding to the preset strategy is determined, including: If the load information indicates that the current time is during the peak load period of the power grid, then the first candidate power corresponding to the preset strategy is determined based on the power information. The first candidate power corresponding to the preset strategy is greater than the power information.

5. The method according to claim 4, characterized in that, Based on the power information and the load information, and according to a preset strategy, determining the first candidate power corresponding to the preset strategy further includes: If the load information determines that the current time is during a low-load period of the power grid, then the first candidate power corresponding to the preset strategy is determined based on the power information; the first candidate power corresponding to the preset strategy is less than the power information.

6. The method according to claim 1, characterized in that, Based on the reference information and the first candidate power corresponding to each preset strategy, the weight information of each preset strategy is determined, including: For each preset strategy, determine the difference between the first candidate power and the reference information; The weight information of each preset strategy is determined based on the difference between each preset strategy.

7. The method according to any one of claims 1-6, characterized in that, Based on the weight information of each preset strategy and the first candidate power corresponding to each preset strategy, a target power supply strategy is generated, including: Based on a preset power range, at least two second candidate powers are generated; the second candidate power represents the power of the energy storage device generated within a second preset time period within the preset power range; For each second candidate power, deviation information is determined based on the second candidate power, the first candidate power corresponding to each preset strategy, and the weight information corresponding to each preset strategy; the deviation information characterizes the degree of deviation between the second candidate power and all first candidate powers. Based on the deviation information corresponding to each second candidate power, a target power is determined from the plurality of second candidate powers; the target power represents the power of the energy storage device within a second preset time period based on all preset strategies; The target power supply strategy is generated based on the target power.

8. The method according to claim 7, characterized in that, Based on the second candidate power, the first candidate power corresponding to each preset strategy, and the weight information corresponding to each preset strategy, the deviation information is determined, including: For each preset strategy, sub-information is determined based on the second candidate power, the first candidate power corresponding to the preset strategy, and the weight information corresponding to the preset strategy; the sub-information characterizes the degree of deviation between the second candidate power and the first candidate power corresponding to the preset strategy. The deviation information is determined based on the sub-information corresponding to each preset strategy.

9. A data processing device based on an energy storage device, characterized in that, include: The acquisition module is used to acquire the first information, power information, and load information; The first information represents the resources obtained by the energy storage device for providing a unit of electrical energy; The power information represents the power of the energy storage device at the current moment; The load information represents the load of the power grid within a first preset time period; the first preset time period includes the current moment; The first determining module is used to determine reference information based on the first information; And based on the power information and the load information, a first candidate power corresponding to the preset strategy is determined based on the preset strategy; The reference information represents the power of the energy storage device within the expected second preset time period; The preset strategy characterizes the power adjustment strategy of the energy storage device; There are multiple preset strategies; the first candidate power represents the power of the energy storage device within a second preset time period based on the preset strategy; the first preset time period includes the second preset time period; the second preset time period is located after the current moment; The second determining module is used to determine the weight information of each preset strategy based on the reference information and the first candidate power corresponding to each preset strategy; the weight information represents the degree of influence of the preset strategy on the power adjustment of the energy storage device within a second preset time period. The generation module is used to generate a target power supply strategy based on the weight information of each preset strategy and the first candidate power corresponding to each preset strategy; wherein, the target power supply strategy represents the power adjustment strategy of the energy storage device within a second preset time period.

10. A data processing device based on an energy storage device, characterized in that, include: Memory, processor; The memory stores computer-executed instructions; The processor executes computer execution instructions stored in the memory, causing the processor to perform the method as described in any one of claims 1-8.

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