Power consumption allocation control method, device and equipment of power grid energy storage system, storage medium and program product

Abstract

The embodiment of the invention provides an electricity consumption allocation control method and device for a power grid energy storage system, equipment, a storage medium and a program product. The method comprises the following steps: acquiring current power grid load demand information of each energy storage unit in the power grid energy storage system; wherein the current power grid load demand information comprises fluctuation information and peak load information; determining charging and discharging strategy information of the energy storage unit according to the current power grid load demand information of the energy storage unit; according to the volatility information and the peak load information of the energy storage unit, determining the allocation priority of the energy storage unit; and controlling the power grid energy storage system to carry out power consumption allocation processing according to the charging and discharging strategy information and the allocation priority of each energy storage unit in the power grid energy storage system. According to the method, accurate analysis of the power grid load and efficient allocation processing of the energy storage equipment are realized, and the utilization efficiency of the energy storage system and the operation stability of the power grid can be remarkably improved.

Description

Technical Field

[0001] This application relates to the field of power grid energy storage technology, and in particular to a power consumption allocation and control method, device, equipment, storage medium and program product for a power grid energy storage system. Background Technology

[0002] With the large-scale integration of renewable energy sources such as wind and solar power into the traditional power grid, the scale of the distribution network continues to expand. In order to alleviate the dynamic balance between power demand and power supply capacity, grid energy storage systems can balance the grid load by charging during low-load periods and discharging during high-load periods, thereby improving the operational quality and stability of the power grid.

[0003] In existing technologies, power allocation strategies based on grid energy storage systems statically optimize historical load data within a fixed time window and use fixed rules for charging / discharging to complete power consumption allocation control.

[0004] However, the above method uses fixed rules for charging / discharging, which fails to fully consider the dynamic characteristics of each energy storage device in the grid energy storage system and the real-time changes in grid load, resulting in low utilization efficiency of the grid energy storage system. Summary of the Invention

[0005] This application provides a method, apparatus, equipment, storage medium, and program product for power grid energy storage system, which can significantly improve the utilization efficiency of power grid energy storage system and the operational stability of power grid.

[0006] In a first aspect, embodiments of this application provide a method for power consumption allocation and control of a power grid energy storage system, including:

[0007] Obtain the current grid load demand information for each energy storage unit in the grid energy storage system; wherein, the current grid load demand information includes fluctuation information and peak load information;

[0008] Based on the current grid load demand information of the energy storage unit, the charging and discharging strategy information of the energy storage unit is determined; wherein, the charging and discharging strategy information characterizes the charging and discharging operation strategy.

[0009] The allocation priority of the energy storage unit is determined based on the fluctuation information and peak load information of the energy storage unit.

[0010] Based on the charging and discharging strategy information and allocation priority of each energy storage unit in the grid energy storage system, the grid energy storage system is controlled to perform power consumption allocation processing.

[0011] In one possible implementation, determining the charging and discharging strategy information of the energy storage unit based on the current grid load demand information of the energy storage unit includes:

[0012] Based on the current grid load demand information of the energy storage unit, the optimal charging and discharging power of the energy storage unit is determined; wherein, the optimal charging and discharging power is the optimal charging and discharging power allocated to the energy storage unit.

[0013] Based on the energy storage function type of the energy storage unit, the current grid load demand information, and the optimal charging and discharging power, the charging and discharging strategy information of the energy storage unit is determined.

[0014] In one possible implementation, determining the optimal charging and discharging power of the energy storage unit based on the current grid load demand information of the energy storage unit includes:

[0015] Based on the current grid load demand information and historical electricity consumption data of the energy storage unit, a predicted grid load demand curve for the energy storage unit is determined; wherein, the predicted grid load demand curve includes at least one curve segment; the curve segment has a load label;

[0016] Based on the predicted grid load demand curve of the energy storage unit, the current energy storage status, and the current charging and discharging efficiency, the priority charging and discharging power of the energy storage unit is determined.

[0017] The priority charging and discharging power of each energy storage unit is normalized to obtain the optimal charging and discharging power of the energy storage unit.

[0018] In one possible implementation, before determining the charging and discharging strategy information of the energy storage unit based on the energy storage function type, current grid load demand information, and optimal charging and discharging power, the following steps are included:

[0019] Based on the current grid load demand information and historical electricity consumption data of the energy storage unit, the predicted grid load demand curve of the energy storage unit is determined.

[0020] Based on the current charge and discharge efficiency, current energy storage status, and predicted load demand curve of the energy storage unit, determine the charge and discharge efficiency information of the energy storage unit.

[0021] The energy storage function type of the energy storage unit is determined based on the charging and discharging efficiency information and charging and discharging priority of the energy storage unit.

[0022] In one possible implementation, determining the allocation priority of the energy storage unit based on its volatility information and peak load information includes:

[0023] The load allocation coefficient of the energy storage unit is determined based on the fluctuation information and peak load information of the energy storage unit.

[0024] The response capability score of the energy storage unit is determined based on its current charge / discharge efficiency and current energy storage state.

[0025] The allocation priority of the energy storage unit is determined based on its load allocation coefficient and response capability score.

[0026] In one possible implementation, determining the allocation priority of the energy storage unit based on its load allocation coefficient and response capability score includes:

[0027] Based on the current grid load demand information and historical electricity consumption data of the energy storage unit, the predicted grid load demand curve of the energy storage unit is determined.

[0028] The load matching degree of the energy storage unit is determined based on the predicted grid load demand curve and real-time power output information of the energy storage unit.

[0029] Based on the current charge / discharge efficiency, current energy storage state, and current response speed of the energy storage unit, the operating information of the energy storage unit is determined; wherein, the operating information characterizes the operational adaptability of the energy storage unit.

[0030] The allocation priority of the energy storage unit is determined based on its load matching degree, operating information, and priority allocation factor.

[0031] In one possible implementation, the method further includes:

[0032] The operating mode of the energy storage unit is adjusted based on the operating status data of the energy storage unit and the current grid load demand information.

[0033] In one possible implementation, adjusting the operating mode of the energy storage unit based on its operating status data and current grid load demand information includes:

[0034] Adjust the operating status data of the energy storage unit based on the current grid load demand information of the energy storage unit;

[0035] If it is determined that the adjusted operating status data of the energy storage unit exceeds the preset range, the operating mode of the energy storage unit is adjusted to a low-power charging and discharging mode, and the charging and discharging strategy information of other energy storage units in the grid energy storage system other than the energy storage unit is re-determined.

[0036] Secondly, embodiments of this application provide a power consumption dispatching and control device for a power grid energy storage system, comprising:

[0037] The acquisition module is used to acquire the current grid load demand information of each energy storage unit in the grid energy storage system; wherein, the current grid load demand information includes fluctuation information and peak load information;

[0038] The first determining module is used to determine the charging and discharging strategy information of the energy storage unit based on the current grid load demand information of the energy storage unit; wherein the charging and discharging strategy information characterizes the charging and discharging operation strategy.

[0039] The second determining module is used to determine the allocation priority of the energy storage unit based on the fluctuation information and peak load information of the energy storage unit.

[0040] The control module is used to control the power consumption allocation of the grid energy storage system according to the charging and discharging strategy information and allocation priority of each energy storage unit in the grid energy storage system.

[0041] In one possible implementation, the first determining module is specifically configured to: determine the optimal charging and discharging power of the energy storage unit based on the current grid load demand information of the energy storage unit; wherein the optimal charging and discharging power is the optimal charging and discharging power allocated to the energy storage unit; and determine the charging and discharging strategy information of the energy storage unit based on the energy storage function type of the energy storage unit, the current grid load demand information, and the optimal charging and discharging power.

[0042] In one possible implementation, the first determining module is specifically configured to: determine the predicted grid load demand curve of the energy storage unit based on the current grid load demand information and historical electricity consumption data of the energy storage unit; wherein the predicted grid load demand curve includes at least one curve segment; the curve segment has a load label; determine the priority charging and discharging power of the energy storage unit based on the predicted grid load demand curve of the energy storage unit, the current energy storage state, and the current charging and discharging efficiency; and normalize the priority charging and discharging power of each energy storage unit to obtain the optimal charging and discharging power of the energy storage unit.

[0043] In one possible implementation, before the first determining module is specifically configured to determine the charging and discharging strategy information of the energy storage unit based on the energy storage function type, current grid load demand information, and optimal charging and discharging power, the first determining module is further specifically configured to: determine the predicted grid load demand curve of the energy storage unit based on the current grid load demand information and historical electricity consumption data of the energy storage unit; determine the charging and discharging efficiency information of the energy storage unit based on the current charging and discharging efficiency, current energy storage status, and predicted load demand curve of the energy storage unit; and determine the energy storage function type of the energy storage unit based on the charging and discharging efficiency information and charging and discharging priority of the energy storage unit.

[0044] In one possible implementation, the second determining module is specifically configured to: determine the load allocation coefficient of the energy storage unit based on the fluctuation information and peak load information of the energy storage unit; determine the response capability score of the energy storage unit based on the current charge / discharge efficiency and current energy storage state of the energy storage unit; and determine the allocation priority of the energy storage unit based on the load allocation coefficient and response capability score of the energy storage unit.

[0045] In one possible implementation, the second determining module is further configured to: determine the predicted grid load demand curve of the energy storage unit based on the current grid load demand information and historical electricity consumption data of the energy storage unit; determine the load matching degree of the energy storage unit based on the predicted grid load demand curve and real-time power output information of the energy storage unit; determine the operating information of the energy storage unit based on the current charging and discharging efficiency, current energy storage status, and current response speed of the energy storage unit; wherein the operating information characterizes the operating adaptability of the energy storage unit; and determine the allocation priority of the energy storage unit based on the load matching degree, operating information, and priority allocation factor of the energy storage unit.

[0046] In one possible implementation, the device is further configured to: adjust the operating mode of the energy storage unit based on the operating status data of the energy storage unit and the current grid load demand information.

[0047] In one possible implementation, the device is further configured to: adjust the operating status data of the energy storage unit according to the current grid load demand information of the energy storage unit; if it is determined that the adjusted operating status data of the energy storage unit exceeds a preset range, adjust the operating mode of the energy storage unit to a low-power charging and discharging mode, and re-determine the charging and discharging strategy information of other energy storage units in the grid energy storage system besides the energy storage unit.

[0048] Thirdly, embodiments of this application provide an electronic device, including: a memory and a processor;

[0049] The memory stores computer-executed instructions;

[0050] 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.

[0051] 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.

[0052] 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.

[0053] The power consumption allocation control method, device, equipment, storage medium, and program product for the power grid energy storage system provided in this application process the current grid load demand information of each energy storage unit in the power grid energy storage system to determine the charging and discharging operation strategy of each energy storage unit. By processing the fluctuation information and peak load information of each energy storage unit in the power grid energy storage system, the power consumption allocation priority of each energy storage unit is determined. Based on the power consumption allocation priority and charging and discharging operation strategy of each energy storage unit, the power consumption allocation of each energy storage unit in the power grid energy storage system is controlled. Therefore, dynamic balance of grid load and optimal power consumption allocation can be achieved, significantly improving the utilization efficiency of the energy storage system and the operational stability of the power grid. Attached Figure Description

[0054] 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.

[0055] Figure 1 This application provides an illustration of an application scenario.

[0056] Figure 2 A flowchart illustrating a power consumption allocation and control method for a power grid energy storage system provided in this application embodiment;

[0057] Figure 3 A flowchart illustrating another power consumption allocation and control method for a power grid energy storage system provided in this application embodiment;

[0058] Figure 4 A flowchart illustrating another power consumption allocation and control method for a power grid energy storage system provided in this application embodiment;

[0059] Figure 5 A schematic diagram of the structure of a power distribution control device for a power grid energy storage system provided in this application embodiment;

[0060] Figure 6 This is a schematic diagram of the structure of an electronic device provided in an embodiment of this application.

[0061] The accompanying drawings illustrate 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 particular embodiments. Detailed Implementation

[0062] 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.

[0063] It should be noted that this application can be used in the field of grid energy storage technology, or in any field other than grid energy storage technology. The application field of this application is not limited.

[0064] Figure 1 This application provides an illustration of an application scenario, such as... Figure 1 As shown, the specific application scenario of this application is as follows: In order to alleviate the dynamic balance problem between the power demand and the power supply capacity of the power grid, the power grid energy storage system can balance the power grid load by charging during low load periods and discharging during high load periods, thereby improving the operation quality and stability of the power grid.

[0065] Based on the above scenarios, it can be seen that using fixed rules to control the charging / discharging of each energy storage unit in the grid energy storage system results in a low utilization efficiency of the grid energy storage system.

[0066] The power consumption allocation control method for the grid energy storage system provided in this application processes the current grid load demand information of each energy storage unit in the grid energy storage system to determine the charging and discharging operation strategy of each energy storage unit. It also processes the fluctuation information and peak load information of each energy storage unit in the grid energy storage system to determine the power consumption allocation priority of each energy storage unit. Based on the power consumption allocation priority and charging and discharging operation strategy of each energy storage unit, the method controls the power consumption allocation of each energy storage unit in the grid energy storage system, thereby solving the technical problem of insufficient utilization of energy storage efficiency.

[0067] The technical solution of this application and how the technical solution of this application solves the above-mentioned technical problems are 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 now be described with reference to the accompanying drawings.

[0068] Figure 2 A flowchart illustrating a power consumption allocation and control method for a power grid energy storage system provided in this application embodiment is shown below. Figure 2 As shown, the method includes:

[0069] 201. Obtain the current grid load demand information for each energy storage unit in the grid energy storage system; wherein, the current grid load demand information includes fluctuation information and peak load information.

[0070] For example, the execution subject of this embodiment may be an electronic device, hereinafter referred to as the device. For a grid energy storage system that requires power consumption dispatch control, the grid energy storage system includes one or more energy storage units. The device can monitor the load status of each energy storage unit in real time, that is, the device can obtain the current grid load demand information of each energy storage unit to characterize the current grid load demand of each energy storage unit, such as the total power supply required by the grid at the current moment and the required reserve capacity of the grid, to cope with sudden load increases or generator failures; the current grid load demand information also includes volatility information and peak load information; wherein, the volatility information of each energy storage unit characterizes the current grid load change of each energy storage unit, including daytime and seasonal fluctuations; the peak load information of each energy storage unit characterizes the maximum load demand of each energy storage unit in the current time period.

[0071] 202. Based on the current grid load demand information of the energy storage unit, determine the charging and discharging strategy information of the energy storage unit; wherein, the charging and discharging strategy information characterizes the charging and discharging operation strategy.

[0072] For example, the device processes the current grid load demand information of each energy storage unit based on preset rules, such as preset information processing technology, determines the power consumption allocation strategy of each energy storage unit, and then dynamically adjusts the charging and discharging operation strategy of each energy storage unit to obtain the charging and discharging strategy information of each energy storage unit.

[0073] For example, based on the one-to-one correspondence between each preset condition and each preset charging and discharging operation strategy, if the device determines that the load value in the current grid load demand information of each energy storage unit meets the first preset condition, then the charging and discharging operation strategy of that energy storage unit is adjusted to the first preset charging and discharging operation strategy corresponding to the first preset condition; if it determines that the load value in the current grid load demand information of each energy storage unit meets the second preset condition, then the charging and discharging operation strategy of that energy storage unit is adjusted to the second preset charging and discharging operation strategy corresponding to the second preset condition.

[0074] 203. Determine the allocation priority of energy storage units based on the fluctuation information and peak load information of the energy storage units.

[0075] For example, the device processes the volatility information and peak load information of each energy storage unit based on the volatility information and peak load information of each energy storage unit. For instance, it performs weighted summation processing on the volatility information and peak load information of each energy storage unit according to the preset weights corresponding to the volatility information and the peak load information, and determines the allocation priority of each energy storage unit.

[0076] 204. Based on the charging and discharging strategy information and allocation priority of each energy storage unit in the grid energy storage system, control the grid energy storage system to perform power consumption allocation processing.

[0077] For example, the device analyzes the allocation priority of each energy storage unit in the grid energy storage system, determines the energy storage unit with the highest allocation priority, and controls the energy storage unit with the highest priority to perform power allocation processing according to the charging and discharging strategy information of the energy storage unit with the highest priority, so as to achieve the power load balance of the grid energy storage system.

[0078] This embodiment provides a power consumption allocation control method for a grid energy storage system. By processing the current grid load demand information of each energy storage unit in the grid energy storage system, a charging and discharging operation strategy for each energy storage unit is determined. By processing the fluctuation information and peak load information of each energy storage unit in the grid energy storage system, a power consumption allocation priority for each energy storage unit is determined. Based on the power consumption allocation priority and charging and discharging operation strategy of each energy storage unit, the power consumption allocation of each energy storage unit in the grid energy storage system is controlled. Therefore, dynamic balance of grid load and optimal power consumption allocation can be achieved, significantly improving the utilization efficiency of the energy storage system and the operational stability of the grid.

[0079] Figure 3 A flowchart illustrating another power consumption allocation and control method for a power grid energy storage system provided in this application embodiment is shown below. Figure 3 As shown, the method includes:

[0080] 301. Obtain the current grid load demand information for each energy storage unit in the grid energy storage system; wherein, the current grid load demand information includes fluctuation information and peak load information.

[0081] For example, this step can be referred to as step 201, which will not be repeated here.

[0082] 302. Based on the current grid load demand information of the energy storage unit, determine the optimal charging and discharging power of the energy storage unit; wherein, the optimal charging and discharging power is the optimal charging and discharging power allocated to the energy storage unit.

[0083] For example, the device uses preset rules, such as preset information processing technology, to process the current grid load demand information of each energy storage unit, determine the optimal charging and discharging power of each energy storage unit, and then determine the optimal charging and discharging power allocated to the energy storage unit.

[0084] For example, based on the one-to-one correspondence between each preset condition and each preset charging / discharging power, if the device determines that the load value in the current grid load demand information of each energy storage unit meets the first preset condition, then the first preset charging / discharging power corresponding to the first preset condition is determined as the optimal charging / discharging power of the energy storage unit; if it determines that the load value in the current grid load demand information of each energy storage unit meets the second preset condition, then the second preset charging / discharging power corresponding to the second preset condition is determined as the optimal charging / discharging power of the energy storage unit.

[0085] In one example, step 302 includes the following steps:

[0086] The first step is to determine the predicted grid load demand curve of the energy storage unit based on the current grid load demand information and historical electricity consumption data. The predicted grid load demand curve includes at least one curve segment, and the curve segment has a load label.

[0087] The second step is to determine the priority charging and discharging power of the energy storage unit based on the predicted grid load demand curve, the current energy storage status, and the current charging and discharging efficiency.

[0088] The third step is to normalize the priority charging and discharging power of each energy storage unit to obtain the optimal charging and discharging power of the energy storage unit.

[0089] For example, Figure 4 A flowchart illustrating another power consumption allocation and control method for a power grid energy storage system provided in this application embodiment is shown below. Figure 4As shown, the device can acquire historical electricity consumption data for each energy storage unit and call a preset load prediction model, such as a time-series neural network-based load prediction model. The historical electricity consumption data and current grid load demand information of each energy storage unit are input into the load prediction model for processing. This allows the device to predict the grid load demand curve for a set future time period. Each grid load demand curve is segmented, and each segment is labeled as a peak load period, a low load period, or a balanced load period, resulting in a load label for each segment. The device acquires the current charging and discharging efficiency of each energy storage unit and processes the predicted grid load demand curve, current energy storage status, and current charging and discharging efficiency for each unit. For example, a preset deep learning model can be used for model processing to obtain the priority charging and discharging power for each energy storage unit. The device uses a preset normalization algorithm to normalize the priority charging and discharging power of all energy storage units, obtaining the optimal charging and discharging power for each energy storage unit.

[0090] For example, a deep learning model based on Long Short-Term Memory (LSTM) networks can be used to predict future power grid load demand curves. The core formula of the LSTM-based deep learning model is: , where y t+1 Represents the grid load at forecast time t+1; represents the input characteristics at time t, including historical load, weather, temperature, etc.; h t The hidden state at time t is represented by the following formula: σ is the activation function, typically the sigmoid function; W h W x b, b h These represent the weight matrix and bias parameters of the model, respectively. By training this LSTM deep learning model, a load prediction model is obtained, and using current grid load demand information and historical electricity consumption data, the load demand curve for a future set time period is predicted. The device obtains the current energy storage capacity C of each energy storage unit. i Maximum charge / discharge power P max,i Minimum charge / discharge power P min,i and the current energy storage state of charge (SOC) i (State of the energy storage unit, such as the current percentage of total capacity), based on the current state of charge (SOC) of the energy storage unit. i Charge and discharge efficiency η i and the current load demand of the power grid L t The priority charging and discharging power of each energy storage unit is calculated using the following formula:

[0091] ,

[0092] Among them, P i Allocate charging and discharging power to the i-th energy storage unit; L t This represents the current load demand of the power grid. The total power allocated to other energy storage units; N is the total number of energy storage units; η i The charging and discharging efficiency of the energy storage units is assessed. The equipment normalizes the power distribution of all energy storage units to ensure that the total output power of all energy storage units matches the grid load demand, while simultaneously meeting the power limit conditions of each energy storage unit: P min,i ≤P i ≤P max,i If the allocation result exceeds the power limit of the energy storage unit, the allocated power is adjusted to keep it within a safe range, and the remaining load power is redistributed to obtain the optimal charging and discharging power for each energy storage unit.

[0093] For example, to obtain the current state of an energy storage unit: Unit 1: C1=50, P max,1 =30, P min,1 =5, SOC1=0.6, η1=0.95; Unit 2: C2=40, P max,2 =20, P min,2 =5, SOC2=0.8, η2=0.9; Unit 3: C3=60, P max,3 =40, P min,3 =10, SOC3=0.4, η3=0.85; Calculate the priority charge / discharge power for each energy storage unit: Assume the initial power allocation is:

[0094] ;

[0095] ;

[0096] ;

[0097] Furthermore, by obtaining the energy storage units in the grid energy storage system and adjusting them according to the constraints: Unit 1: P1 exceeds P max,1 =30, adjusted to P1=30kW; Unit 2: P2=20kW (because it exceeds the maximum power limit); Unit 3: P3=28.33kW (meets the limit); further normalization is performed to ensure that the total power meets L t =100kW, i.e., P1=30kW, P2=20kW, P3=28.33kW; calculate the priority U of the energy storage unit. iUnit 1: M1 = 1 - (|30 - 100 / 3|) / 100 = 0.7, R1 = (0.95⋅50) / 30 ≈ 1.58; U1 = α⋅0.7 + β⋅1.58; Calculate Unit 2 and Unit 3 in sequence; Output results: Optimal charging and discharging power allocation: Unit 1: 30kW; Unit 2: 20kW; Unit 3: 28.33kW, meeting grid demand. t =100kW, to be used to determine the allocation priority and power allocation of each energy storage unit.

[0098] By using information such as the charging and discharging efficiency of each energy storage unit and the current load demand, and combining it with a load prediction model, dynamic balance of grid load and optimal allocation of energy storage units can be achieved. This can effectively reduce the peak grid load of the grid energy storage system, improve the utilization efficiency of the grid energy storage system, reduce grid operating costs, and ensure the stability of system operation.

[0099] 303. Determine the charging and discharging strategy information of the energy storage unit based on the energy storage function type, current grid load demand information, and optimal charging and discharging power.

[0100] For example, the device classifies each energy storage unit based on a preset classification method to obtain the energy storage function type of each energy storage unit. For example, all energy storage units are divided into three categories: high-efficiency charging unit, balancing unit, and high-efficiency discharging unit. Based on a preset analysis method, such as calling a preset deep learning model, the device performs model processing on the energy storage function type, current grid load demand information, and optimal charging and discharging power of each energy storage unit to obtain the charging and discharging strategy information of each energy storage unit.

[0101] Furthermore, by collecting the grid load demand of the energy storage units in real time, the charging and discharging power of the energy storage units can be dynamically allocated. Combined with the energy storage function type of the energy storage units, the charging and discharging operation strategy can be dynamically adjusted to ensure that each energy storage unit is always in a suitable operating state, thereby improving the operating efficiency of the grid energy storage system.

[0102] In one example, before step 303, the following is also included:

[0103] The first step is to determine the predicted grid load demand curve for the energy storage unit based on the current grid load demand information and historical electricity consumption data.

[0104] The second step is to determine the charging and discharging efficiency information of the energy storage unit based on its current charging and discharging efficiency, current energy storage status, and predicted load demand curve.

[0105] The third step is to determine the energy storage function type of the energy storage unit based on its charging and discharging efficiency information and charging and discharging priority.

[0106] For example, the device uses a load prediction model to process the historical electricity consumption data and current grid load demand of each energy storage unit, predicting the grid load demand curve for a future set time period. Based on the charging and discharging efficiency of each energy storage unit, its current energy storage status, and the grid load demand curve, the device calculates the charging and discharging efficiency of each energy storage unit, thus obtaining the charging and discharging efficiency information of each unit. Based on preset rules, the device processes the charging and discharging efficiency information and charging and discharging priority of each energy storage unit to determine its energy storage function type. For example, combining... Figure 4 Energy storage units with charging and discharging efficiency higher than a preset threshold and higher charging priority are classified as high-efficiency charging units; energy storage units with charging and discharging efficiency higher than a preset threshold and higher discharging priority are classified as high-efficiency discharging units; and the remaining energy storage units are classified as balancing units, which are used to dynamically supplement the fluctuations in grid load demand.

[0107] For example, energy storage units can be classified based on their charge and discharge efficiency:

[0108] ;

[0109] Where: E i Indicates the efficiency of energy storage unit i; C i This represents the current energy storage capacity of energy storage unit i; Δt represents the fluctuation period of the grid load. The classification rule is: when E i >E th1 At that time, the energy storage unit is divided into a high-efficiency discharge unit; when E th2 <E i ≤E th1 When E is in a state of equilibrium, the energy storage unit is divided into a balance unit; when E i ≤E th2 At that time, the energy storage unit is divided into a high-efficiency charging unit; among which, E th1 and E th2 The classification threshold is dynamically adjusted based on the power grid load demand.

[0110] Furthermore, by collecting the status of energy storage units (such as energy storage capacity and charging / discharging efficiency) and grid load demand in real time, load prediction models (such as deep learning models) are used to predict future load demand, providing a reference for the allocation of energy storage units; energy storage units are divided into high-efficiency charging units, balancing units and high-efficiency discharging units, and by dynamically adjusting charging and discharging strategies, it is ensured that energy storage units are always in a suitable operating state.

[0111] 304. Determine the load allocation coefficient of the energy storage unit based on the fluctuation information and peak load information of the energy storage unit.

[0112] For example, the device processes the volatility information, peak load information and historical load data of each energy storage unit through a preset prediction model to predict the load fluctuation amplitude and peak load duration of each energy storage unit in a future set time period. Through a preset calculation method, the device calculates and processes the load fluctuation amplitude and peak load duration of each energy storage unit in the future set time period to obtain the load allocation coefficient of each energy storage unit.

[0113] 305. Determine the response capability score of the energy storage unit based on its current charge / discharge efficiency and current energy storage status.

[0114] For example, the device obtains the current charge and discharge efficiency and current energy storage status of each energy storage unit, and calculates and processes the current charge and discharge efficiency and current energy storage status of each energy storage unit through a preset calculation method to obtain the response capability score of each energy storage unit, so as to characterize the response capability of each energy storage unit in terms of power consumption allocation.

[0115] 306. Determine the allocation priority of energy storage units based on their load allocation coefficient and response capability score.

[0116] For example, the load allocation coefficient and response capability score of each energy storage unit are calculated and processed by a preset calculation method to obtain the allocation priority of each energy storage unit.

[0117] In one example, step 306 includes the following steps:

[0118] The first step is to determine the predicted grid load demand curve for the energy storage unit based on the current grid load demand information and historical electricity consumption data.

[0119] The second step is to determine the load matching degree of the energy storage unit based on the predicted grid load demand curve and real-time power output information of the energy storage unit.

[0120] The third step is to determine the operating information of the energy storage unit based on its current charge and discharge efficiency, current energy storage status, and current response speed; the operating information characterizes the operational adaptability of the energy storage unit.

[0121] The fourth step is to determine the allocation priority of the energy storage units based on their load matching degree, operating information, and priority allocation factors.

[0122] For example, the device uses a predictive model to process the current grid load demand information and historical electricity consumption data of each energy storage unit to obtain the predicted grid load demand curve of the energy storage unit; it obtains the real-time power output information of each energy storage unit, and calculates the predicted grid load demand curve and real-time power output information of each energy storage unit based on a preset calculation formula. For example, it calculates the deviation between the real-time power output and the predicted load demand of each energy storage unit, and further calculates the load matching degree of each energy storage unit; it obtains the charging and discharging efficiency, current energy storage status and response speed of each energy storage unit, and calculates the operating information of each energy storage unit to characterize the operating adaptability of each energy storage unit; it determines the priority allocation factor of each energy storage unit, and calculates the load matching degree, operating information and priority allocation factor of each energy storage unit based on a preset calculation formula to obtain the allocation priority of each energy storage unit.

[0123] For example, the formula for calculating the allocation priority of energy storage units includes: allocation priority U i The calculation formula is: U i =α⋅M i +β⋅R i +γ⋅Q i ; where: U i The allocation priority for energy storage unit i; M i The load matching degree of an energy storage unit is expressed by the following formula:

[0124] ;

[0125] R i The formula representing the response capability of an energy storage unit is:

[0126] ;

[0127] Q i The operational adaptability of the energy storage unit is represented by the analysis and processing of its historical operating status; α, β and γ are priority weighting factors, which can be dynamically adjusted according to demand.

[0128] 307. Based on the charging and discharging strategy information and allocation priority of each energy storage unit in the grid energy storage system, control the grid energy storage system to perform power consumption allocation processing.

[0129] For example, combined Figure 4 The equipment analyzes the allocation priority of each energy storage unit in the grid energy storage system, determines the energy storage unit with the highest allocation priority, and controls the energy storage unit with the highest priority to perform power allocation processing based on the charging and discharging strategy information of the energy storage unit with the highest priority, so as to achieve the power load balance of the grid energy storage system.

[0130] 308. Adjust the working mode of the energy storage unit based on the operating status data of the energy storage unit and the current grid load demand information.

[0131] For example, combined Figure 4 The equipment monitors the charging and discharging operations of each energy storage unit in real time, obtaining real-time operating status data for each unit, including real-time charging and discharging power, current energy storage status, and operating status parameters. It also obtains current grid load demand information for each unit, such as real-time grid load data. Based on the real-time operating status data and current grid load demand information, the equipment dynamically adjusts the operating mode of each energy storage unit to achieve dynamic balance of grid load and optimal allocation of electricity consumption. Furthermore, it can monitor the operating status of the energy storage units in real time, avoiding abnormal situations such as overload and overcharging, thereby further improving the safety and reliability of the system.

[0132] In one example, step 308 includes the following steps:

[0133] The first step is to adjust the operating status data of the energy storage unit based on the current grid load demand information.

[0134] The second step is to determine that if the adjusted operating status data of the energy storage unit exceeds the preset range, the working mode of the energy storage unit will be adjusted to the protection mode, and the charging and discharging strategy information of other energy storage units in the grid energy storage system will be redefined.

[0135] For example, combined Figure 4 The device dynamically adjusts the charging and discharging power in the operating status data of each energy storage unit based on the current grid load demand information, to obtain adjusted operating status data, including the real-time charging and discharging power, current energy storage status, and operating status parameters of the energy storage unit. If it is determined that the adjusted operating status data of the energy storage unit exceeds the preset range, the operating mode of the energy storage unit is adjusted to a low-power charging and discharging mode, i.e., a protection mode, by limiting or reducing the output power of the energy storage unit's charging and discharging operations to avoid causing excessive current or voltage pressure on the energy storage unit. Furthermore, for other energy storage units in the grid energy storage system besides the energy storage unit, the device re-processes the power consumption of these other energy storage units to determine their charging and discharging strategy information in order to perform load balancing. This enables accurate analysis of grid load and efficient allocation of energy storage devices, which can significantly improve the utilization efficiency of the grid energy storage system and the operational stability of the grid.

[0136] In this embodiment, based on the above embodiments, on the one hand, the charging and discharging power of the energy storage unit is dynamically allocated by collecting the status of the energy storage unit (such as energy storage capacity and charging and discharging efficiency) and the grid load demand in real time; on the other hand, the load prediction model (such as a deep learning model) is used to predict future load demand, providing a reference for the allocation of energy storage units; the energy storage unit is divided into high-efficiency charging unit, balancing unit and high-efficiency discharging unit, and the charging and discharging strategy is dynamically adjusted to ensure that the energy storage unit is always in a suitable operating state; thereby, the peak load of the grid can be effectively reduced, the utilization efficiency of the energy storage system can be improved, the grid operating cost can be reduced, and the stability of the system operation can be guaranteed.

[0137] Figure 5 A schematic diagram of the structure of a power distribution control device for a power grid energy storage system provided in this application embodiment is shown below. Figure 5 As shown, the device includes:

[0138] The acquisition module 401 is used to acquire the current grid load demand information of each energy storage unit in the grid energy storage system; wherein, the current grid load demand information includes fluctuation information and peak load information;

[0139] The first determining module 402 is used to determine the charging and discharging strategy information of the energy storage unit based on the current grid load demand information of the energy storage unit; wherein, the charging and discharging strategy information characterizes the charging and discharging operation strategy.

[0140] The second determining module 403 is used to determine the allocation priority of the energy storage unit based on the fluctuation information and peak load information of the energy storage unit.

[0141] The control module 404 is used to control the power consumption allocation of the grid energy storage system according to the charging and discharging strategy information and allocation priority of each energy storage unit in the grid energy storage system.

[0142] In one possible implementation, the first determining module 402 is specifically used to: determine the optimal charging and discharging power of the energy storage unit based on the current grid load demand information of the energy storage unit; wherein, the optimal charging and discharging power is the optimal charging and discharging power allocated to the energy storage unit; and determine the charging and discharging strategy information of the energy storage unit based on the energy storage function type of the energy storage unit, the current grid load demand information, and the optimal charging and discharging power.

[0143] In one possible implementation, the first determining module 402 is specifically configured to: determine the predicted grid load demand curve of the energy storage unit based on the current grid load demand information and historical electricity consumption data of the energy storage unit; wherein the predicted grid load demand curve includes at least one curve segment; the curve segment has a load label; determine the priority charging and discharging power of the energy storage unit based on the predicted grid load demand curve of the energy storage unit, the current energy storage state and the current charging and discharging efficiency; and normalize the priority charging and discharging power of each energy storage unit to obtain the optimal charging and discharging power of the energy storage unit.

[0144] In one possible implementation, before the first determining module 402 is specifically used to determine the charging and discharging strategy information of the energy storage unit based on the energy storage function type of the energy storage unit, the current grid load demand information, and the optimal charging and discharging power, the first determining module 402 is further specifically used to: determine the predicted grid load demand curve of the energy storage unit based on the current grid load demand information and historical electricity consumption data of the energy storage unit; determine the charging and discharging efficiency information of the energy storage unit based on the current charging and discharging efficiency, the current energy storage state, and the predicted load demand curve of the energy storage unit; and determine the energy storage function type of the energy storage unit based on the charging and discharging efficiency information and the charging and discharging priority of the energy storage unit.

[0145] In one possible implementation, the second determining module 403 is specifically used to: determine the load allocation coefficient of the energy storage unit based on the fluctuation information and peak load information of the energy storage unit; determine the response capability score of the energy storage unit based on the current charge and discharge efficiency and current energy storage state of the energy storage unit; and determine the allocation priority of the energy storage unit based on the load allocation coefficient and response capability score of the energy storage unit.

[0146] In one possible implementation, the second determining module 403 is further specifically configured to: determine the predicted grid load demand curve of the energy storage unit based on the current grid load demand information and historical electricity consumption data of the energy storage unit; determine the load matching degree of the energy storage unit based on the predicted grid load demand curve and real-time power output information of the energy storage unit; determine the operating information of the energy storage unit based on the current charging and discharging efficiency, current energy storage status, and current response speed of the energy storage unit; wherein the operating information characterizes the operating adaptability of the energy storage unit; and determine the allocation priority of the energy storage unit based on the load matching degree, operating information, and priority allocation factor of the energy storage unit.

[0147] In one possible implementation, the device is further configured to: adjust the operating mode of the energy storage unit based on the operating status data of the energy storage unit and the current grid load demand information.

[0148] In one possible implementation, the device is further configured to: adjust the operating status data of the energy storage unit according to the current grid load demand information of the energy storage unit; if it is determined that the adjusted operating status data of the energy storage unit exceeds the preset range, adjust the working mode of the energy storage unit to a low-power charging and discharging mode, and re-determine the charging and discharging strategy information of other energy storage units in the grid energy storage system besides the energy storage unit.

[0149] The apparatus in this embodiment can execute the technical solutions in the above method. Its specific implementation process and technical principles are the same, and will not be repeated here.

[0150] Figure 6 This is a schematic diagram of the structure of an electronic device provided in an embodiment of this application, such as... Figure 6 As shown, the electronic device includes: a memory 501 and a processor 502; the memory 501 is a memory used to store instructions executable by the processor 502.

[0151] The processor 502 is configured to perform the method provided in the above embodiments.

[0152] The electronic device also includes a receiver 503 and a transmitter 504. The receiver 503 is used to receive instructions and data sent by other devices, and the transmitter 504 is used to send instructions and data to external devices.

[0153] The specific implementation process of the processor can be found in the above method embodiments, and its implementation principle and technical effect are similar, so it will not be repeated here.

[0154] 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.

[0155] This application also provides a computer-readable storage medium storing computer-executable instructions, which, when executed on a computer, cause the computer to perform the technical solutions described above.

[0156] 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, electrically erasable programmable read-only memory, erasable programmable read-only memory, programmable read-only memory, read-only memory, 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.

[0157] 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. 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 a device.

[0158] This application also provides a computer program product, which includes a computer program stored in a computer-readable storage medium. At least one processor can read the computer program from the computer-readable storage medium, and when the at least one processor executes the computer program, it can implement the technical solutions in the above embodiments.

[0159] 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.

[0160] 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.

[0161] 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 method for power consumption allocation and control in a power grid energy storage system, characterized in that, include: Obtain the current grid load demand information for each energy storage unit in the grid energy storage system; wherein, the current grid load demand information includes fluctuation information and peak load information; Based on the current grid load demand information of the energy storage unit, the charging and discharging strategy information of the energy storage unit is determined; wherein, the charging and discharging strategy information characterizes the charging and discharging operation strategy. The allocation priority of the energy storage unit is determined based on the fluctuation information and peak load information of the energy storage unit. Based on the charging and discharging strategy information and allocation priority of each energy storage unit in the grid energy storage system, the grid energy storage system is controlled to perform power consumption allocation processing.

2. The method according to claim 1, characterized in that, The step of determining the charging and discharging strategy information of the energy storage unit based on the current grid load demand information of the energy storage unit includes: Based on the current grid load demand information of the energy storage unit, the optimal charging and discharging power of the energy storage unit is determined; wherein, the optimal charging and discharging power is the optimal charging and discharging power allocated to the energy storage unit. Based on the energy storage function type of the energy storage unit, the current grid load demand information, and the optimal charging and discharging power, the charging and discharging strategy information of the energy storage unit is determined.

3. The method according to claim 2, characterized in that, Determining the optimal charging and discharging power of the energy storage unit based on the current grid load demand information of the energy storage unit includes: Based on the current grid load demand information and historical electricity consumption data of the energy storage unit, a predicted grid load demand curve for the energy storage unit is determined; wherein, the predicted grid load demand curve includes at least one curve segment; the curve segment has a load label; Based on the predicted grid load demand curve of the energy storage unit, the current energy storage status, and the current charging and discharging efficiency, the priority charging and discharging power of the energy storage unit is determined. The priority charging and discharging power of each energy storage unit is normalized to obtain the optimal charging and discharging power of the energy storage unit.

4. The method according to claim 2, characterized in that, Before determining the charging and discharging strategy information of the energy storage unit based on its energy storage function type, current grid load demand information, and optimal charging and discharging power, the process includes: Based on the current grid load demand information and historical electricity consumption data of the energy storage unit, the predicted grid load demand curve of the energy storage unit is determined. Based on the current charge and discharge efficiency, current energy storage status, and predicted load demand curve of the energy storage unit, determine the charge and discharge efficiency information of the energy storage unit. The energy storage function type of the energy storage unit is determined based on the charging and discharging efficiency information and charging and discharging priority of the energy storage unit.

5. The method according to claim 1, characterized in that, The step of determining the allocation priority of the energy storage unit based on its volatility information and peak load information includes: The load allocation coefficient of the energy storage unit is determined based on the fluctuation information and peak load information of the energy storage unit. The response capability score of the energy storage unit is determined based on its current charge / discharge efficiency and current energy storage state. The allocation priority of the energy storage unit is determined based on its load allocation coefficient and response capability score.

6. The method according to claim 5, characterized in that, The step of determining the allocation priority of the energy storage unit based on its load allocation coefficient and response capability score includes: Based on the current grid load demand information and historical electricity consumption data of the energy storage unit, the predicted grid load demand curve of the energy storage unit is determined. The load matching degree of the energy storage unit is determined based on the predicted grid load demand curve and real-time power output information of the energy storage unit. Based on the current charge / discharge efficiency, current energy storage state, and current response speed of the energy storage unit, the operating information of the energy storage unit is determined; wherein, the operating information characterizes the operational adaptability of the energy storage unit. The allocation priority of the energy storage unit is determined based on its load matching degree, operating information, and priority allocation factor.

7. The method according to any one of claims 1-6, characterized in that, The method further includes: The operating mode of the energy storage unit is adjusted based on the operating status data of the energy storage unit and the current grid load demand information.

8. The method according to claim 7, characterized in that, The step of adjusting the operating mode of the energy storage unit based on its operating status data and current grid load demand information includes: Adjust the operating status data of the energy storage unit based on the current grid load demand information of the energy storage unit; If it is determined that the adjusted operating status data of the energy storage unit exceeds the preset range, the operating mode of the energy storage unit is adjusted to a low-power charging and discharging mode, and the charging and discharging strategy information of other energy storage units in the grid energy storage system other than the energy storage unit is re-determined.

9. A power consumption distribution and control device for a power grid energy storage system, characterized in that, include: The acquisition module is used to acquire the current grid load demand information of each energy storage unit in the grid energy storage system; wherein, the current grid load demand information includes fluctuation information and peak load information; The first determining module is used to determine the charging and discharging strategy information of the energy storage unit based on the current grid load demand information of the energy storage unit; wherein the charging and discharging strategy information characterizes the charging and discharging operation strategy. The second determining module is used to determine the allocation priority of the energy storage unit based on the fluctuation information and peak load information of the energy storage unit. The control module is used to control the power consumption allocation of the grid energy storage system according to the charging and discharging strategy information and allocation priority of each energy storage unit in the grid energy storage system.

10. An electronic 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.

11. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores computer-executable instructions, which, when executed by a processor, are used to implement the method as described in any one of claims 1-8.

12. A computer program product, characterized in that, Includes a computer program that, when executed by a processor, implements the method described in any one of claims 1-8.

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