Operation parameter determination method and device of energy storage power generation equipment, equipment, medium and product

Abstract

The invention relates to an operation parameter determination method and device of energy storage power generation equipment, computer equipment, a computer readable storage medium and a computer program product. The method comprises the steps of obtaining target power load data of a target area corresponding to energy storage power generation equipment, determining a target calculation strategy of operation parameters of the energy storage power generation equipment corresponding to the target power load data in a preset strategy library, and calculating the operation parameters of the energy storage power generation equipment according to the target calculation strategy and the target power load data. And target operation parameters of the energy storage power generation equipment are determined. By adopting the method, the power supply stability of the energy storage power generation equipment can be improved.

Description

Methods, devices, equipment, media, and products for determining operating parameters of energy storage power generation equipment Technical Field

[0001] This application relates to the field of power technology, and in particular to a method, apparatus, computer equipment, computer-readable storage medium, and computer program product for determining the operating parameters of an energy storage power generation device. Background Technology

[0002] With the continuous development of power technology and the continuous improvement of users' living standards, various devices are becoming increasingly dependent on electricity, which makes users' demand for stable power supply greater and greater. At present, energy storage generator vehicles are mainly used as backup power supply equipment to ensure power supply in the event of a power islanding situation when the main grid is disconnected.

[0003] In existing technologies, energy storage power generation vehicles are usually controlled by external commands. However, external communication takes time and it is difficult to respond to power demand in a timely manner, which affects the stability of power supply. Summary of the Invention

[0004] Therefore, it is necessary to provide a method, apparatus, computer equipment, computer-readable storage medium, and computer program product for determining the operating parameters of energy storage power generation equipment that can improve the stability of power supply, in response to the above-mentioned technical problems.

[0005] In a first aspect, this application provides a method for determining the operating parameters of an energy storage power generation device, applied to the energy storage power generation device, comprising: acquiring target power load data of a target area corresponding to the energy storage power generation device; determining a target calculation strategy for the operating parameters of the energy storage power generation device corresponding to the target power load data in a preset strategy library, wherein the strategy library includes the mapping relationship between each power load data and each calculation strategy; and determining the target operating parameters of the energy storage power generation device based on the target calculation strategy and the target power load data.

[0006] In one embodiment, the strategy library construction process includes: acquiring multiple historical operating parameters of the energy storage power generation device in a power island state, and historical power load data of the target area corresponding to each historical operating parameter; determining multiple candidate calculation strategies based on each historical operating parameter and each historical power load data; and constructing a strategy library based on each candidate calculation strategy and each historical power load data.

[0007] In one embodiment, the target operating parameters of the energy storage power generation device are determined based on the target calculation strategy and the target power load data. This includes: performing clustering processing on each historical operating parameter and the historical power load data corresponding to each historical operating parameter to obtain multiple clustering results, with different clustering results corresponding to different ranges of power load data; for each clustering result, calculating operating parameter calculation coefficients based on a preset power calculation function, the historical operating parameters included in the clustering result, and the historical power load data included in the clustering result, whereby the operating parameter calculation coefficients are the calculation coefficients of the power calculation function; and generating candidate calculation strategies based on the operating parameter calculation coefficients, the power calculation function, and the historical power load data included in the clustering result.

[0008] In one embodiment, different calculation strategies correspond to different power load data ranges. In a preset strategy library, the target calculation strategy for the operating parameters of the energy storage power generation device corresponding to the target power load data is determined, including: determining the target power load range to which the target power load data belongs; in the strategy library, determining the target calculation strategy corresponding to the power load data based on the target power load range; wherein, the target calculation strategy includes: target operating parameter calculation coefficients and target operating parameter calculation functions.

[0009] In one embodiment, the target operating parameters of the energy storage power generation device are determined based on the target calculation strategy and the target power load data, including: obtaining the target operating parameter calculation coefficients and the target operating parameter calculation function contained in the target calculation strategy; substituting the target power load data and the target operating parameter calculation coefficients into the target operating parameter calculation function to calculate the target operating parameters, which include active power and reactive power.

[0010] In one embodiment, the energy storage power generation device includes an energy storage power generation vehicle, and the method further includes: sending target operating parameters to the control device of the energy storage power generation vehicle, the target operating parameters being used to control the battery included in the energy storage power generation vehicle to supply power to electrical equipment in the target area.

[0011] Secondly, this application also provides an operating parameter determination device for an energy storage power generation device, comprising: a power load data acquisition module for acquiring target power load data of a target area corresponding to the energy storage power generation device; a calculation strategy determination module for determining a target calculation strategy for the operating parameters of the energy storage power generation device corresponding to the target power load data in a preset strategy library, wherein the strategy library includes a mapping relationship between each power load data and each calculation strategy; and an operating parameter determination module for determining the target operating parameters of the energy storage power generation device based on the target calculation strategy and the target power load data.

[0012] Thirdly, this application also provides a computer device, including a memory and a processor, wherein the memory stores a computer program, and the processor executes the computer program to implement the steps of the method described in the first aspect.

[0013] Fourthly, this application also provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the steps of the method described in the first aspect.

[0014] Fifthly, this application also provides a computer program product, including a computer program that, when executed by a processor, implements the steps of the method described in the first aspect above.

[0015] The aforementioned method, apparatus, computer equipment, computer-readable storage medium, and computer program product for determining the operating parameters of energy storage power generation equipment are applied to energy storage power generation equipment. When the energy storage power generation equipment is in a power island state, the target power load data of the target area corresponding to the energy storage power generation equipment is first obtained. In a preset strategy library, the target calculation strategy for the operating parameters of the energy storage power generation equipment corresponding to the target power load data is determined. The strategy library includes the mapping relationship between each power load data and each calculation strategy. Based on the target calculation strategy and the target power load data, the target operating parameters of the energy storage power generation equipment are determined. By configuring the strategy library in the energy storage power generation equipment, the energy storage power generation equipment can independently perform the calculation operation of the operating strategy, avoiding the communication delay caused by external calculation, enabling the energy storage power generation equipment to quickly and stably supply power, and improving the power supply stability of the target area. Attached Figure Description

[0016] To more clearly illustrate the technical solutions in the embodiments of this application or related technologies, the drawings used in the description of the embodiments of this application or related technologies will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other related drawings can be obtained based on these drawings without creative effort.

[0017] Figure 1 is an application environment diagram of the method for determining the operating parameters of an energy storage power generation device in one embodiment;

[0018] Figure 2 is a flowchart illustrating a method for determining the operating parameters of an energy storage power generation device in one embodiment;

[0019] Figure 3 is a flowchart illustrating the steps involved in building a strategy library in one embodiment;

[0020] Figure 4 is a flowchart illustrating the steps for determining candidate computation strategies in one embodiment;

[0021] Figure 5 is a flowchart of step 202 in one embodiment;

[0022] Figure 6 is a flowchart of step 203 in one embodiment;

[0023] Figure 7 is a flowchart illustrating the power supply control steps in one embodiment;

[0024] Figure 8 is a flowchart illustrating the method for determining the operating parameters of an energy storage power generation device in another embodiment;

[0025] Figure 9 is a structural block diagram of an energy storage power generation device for determining operating parameters in one embodiment;

[0026] Figure 10 is an internal structure diagram of a computer device in one embodiment. Detailed Implementation

[0027] To make the objectives, technical solutions, and advantages of this application clearer, the following detailed description is provided in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the scope of this application.

[0028] It should be noted that the terms "first," "second," etc., used in this application can be used to describe various elements, but these elements are not limited by these terms. These terms are only used to distinguish the first element from the second element. The terms "comprising" and "having," and any variations thereof, used in this application, are intended to cover non-exclusive inclusion. The term "multiple" used in this application refers to two or more. The term "and / or" used in this application refers to one of the embodiments, or any combination of multiple embodiments.

[0029] The method for determining the operating parameters of an energy storage power generation device provided in this application embodiment can be applied to the application environment shown in Figure 1. This application environment includes at least an energy storage power generation device 101 and at least one electrical device 102.

[0030] The energy storage power generation device 101 is used to acquire target power load data of the target area in a power islanded state. It determines the target calculation strategy for the operating parameters corresponding to the target power load data in a preset strategy library, and determines the target operating parameters of the energy storage power generation device 101 based on the target calculation strategy and the target power load data. The energy storage power generation device 101 can also control the battery to supply power to the electrical equipment 102 in the target area according to the target operating parameters. The energy storage power generation device 101 can be an energy storage power generation vehicle, which is a mobile power device integrating a battery pack, inverter, energy management system, cooling system, power distribution unit, and vehicle chassis. The battery pack is connected to the inverter via the DC side, and the inverter converts DC power to AC power before outputting it to the load or grid via the power distribution unit.

[0031] Electrical equipment 102 is used to consume electricity, and target power load data is generated based on the power demand of at least one electrical device 102. Electrical equipment 102 refers to electrical equipment in the target area, and electrical equipment 102 can be connected to energy storage power generation equipment 101 through the power grid.

[0032] In real-world scenarios, energy storage power generation devices may enter islanded operation mode after being connected to the grid due to grid faults or adjustments in operating modes. Therefore, energy storage power generation devices need to promptly switch inverter operating modes upon detecting islanding conditions to provide a stable power supply to local loads. Current islanding mode switching control methods suffer from high installation costs and communication error risks with remote methods, passive methods often fail to detect islanding under matched power conditions, active methods with disturbance injection may distort current waveforms and degrade power quality, active methods based on reactive power control require precise understanding of load characteristics for parameter selection, and AI-based methods are highly data-dependent in their detection performance, requiring significant time and computing power for training.

[0033] In addition, calculations can also be performed according to the formula. In practical applications, the load type in the power system is usually R (resistance) L (inductance) C (capacitor) load. In islanded mode, the output power of the energy storage generator inverter is usually as shown in formula (1):

[0034] Formula (1);

[0035] Among them, P inv Q is the active power output of the inverter. inv For the inverter to output reactive power, V q For the q-axis voltage at the grid connection point of the energy storage generator vehicle, I q I is the q-axis current of the inverter. d V is the d-axis current of the inverter. PCC is the grid connection voltage of the energy storage generator vehicle, f is the grid connection frequency, and R, L, and C are the load resistance, inductance, and capacitance, respectively.

[0036] Furthermore, the resonant frequency f of the three-phase parallel RLC load r And quality factor Q f As shown in formula (2):

[0037] Formula (2);

[0038] According to formula (2), the formula for calculating the grid connection point frequency is as follows:

[0039] Formula (3);

[0040] Formula (3) can also be rewritten as formula (4):

[0041] Formula (4);

[0042] Among them, f * To detect the frequency setpoint of the isolated island, k * To be with f * The corresponding dq axis current ratio.

[0043] Operating parameters can be obtained step by step by using electricity demand data and the above formulas. However, this method requires a lot of data collection and cannot determine the operating parameters of energy storage power generation equipment in a timely manner, which affects the timeliness of power supply and thus affects the power supply stability of the target area.

[0044] To address this, this application, when the energy storage power generation device is in a power island state, determines the target calculation strategy for operating parameters based on the target power load data of the target area, and determines the target operating parameters based on the target calculation strategy. This enables the energy storage power generation device to autonomously determine and adjust its operating parameters in a power island state, thereby improving the operating efficiency of the energy storage power generation device in a power island state and thus improving the power supply stability of the target area.

[0045] In an exemplary embodiment, as shown in FIG2, a method for determining the operating parameters of an energy storage power generation device is provided. Taking the application of this method to the energy storage power generation device in FIG1 as an example, the method includes the following steps 201 to 203.

[0046] Step 201: Obtain the target power load data of the target area corresponding to the energy storage power generation equipment.

[0047] In real-world scenarios, energy storage power generation devices can switch to power islanding mode to output power when a main grid outage is detected or the output power is less than a threshold. Power islanding mode means that only the energy storage power generation device is outputting power within the target area. During execution, the energy storage power generation device can simultaneously monitor the main grid's output power and the target area's power load data. If the main grid's output power is less than a preset threshold, the energy storage power generation device is determined to be in target power islanding mode. Alternatively, the energy storage power generation device can also monitor the grid connection point's power data; when the system frequency exceeds the upper limit (f*... max ), below the lower limit (f*) min ) or voltage below the lower limit (V min In the case of ), switch to islanded operation mode, that is: execute steps 201 to 202.

[0048] During implementation, when the energy storage power generation device detects that it is in a power islanding state, it acquires the target power load data of the target area to which the energy storage power generation device is connected. The target power load data can be the power demand data of the target area, including at least one of the following: power demand data, voltage demand data, frequency demand data, and current demand data.

[0049] It should be noted that when an energy storage power generation device outputs electrical energy, the active power and reactive power of the inverter can be determined. The active power refers to the electrical power output by the energy storage power generation device, while the reactive power refers to the power required to adjust the output power generation to match the target power load data. In other words, the active power is output externally, and the reactive power is consumed by the energy storage power generation device.

[0050] Step 202: In the preset strategy library, determine the target calculation strategy for the operating parameters of the energy storage power generation equipment corresponding to the target power load data.

[0051] In this application, the strategy library includes the mapping relationship between each power load data and each calculation strategy. The mapping relationship is used to determine the operating parameters of the energy storage power generation device. In actual scenarios, the energy storage power generation device needs to provide power with different parameters for different power load data. The output of the energy storage power generation device is controlled by the operating parameters. The energy storage power generation device can be pre-configured with the strategy library so as to quickly determine the target calculation strategy that matches the target power load data through the configuration library.

[0052] During implementation, the energy storage power generation equipment queries a pre-set strategy library based on the target power load data to obtain a target calculation strategy that matches the target power load data, which is then used to calculate the operating parameters of the energy storage power generation equipment.

[0053] In this application, the calculation strategy refers to the calculation function obtained by fitting the above formula. The calculation strategy includes the calculation function and the corresponding fitting coefficient. The operating parameters of the energy storage power generation device can be determined based on the target power load data, the calculation function and the fitting coefficient. In addition, the calculation strategy can also be used to characterize the calculation method of the operating parameters. The calculation strategy may include an operating parameter calculation model. The target power load data can be input into the operating parameter calculation model to obtain the operating parameters of the energy storage power generation device.

[0054] Step 203: Determine the target operating parameters of the energy storage power generation equipment based on the target calculation strategy and target power load data.

[0055] During implementation, the energy storage power generation equipment performs calculations based on the target power load data according to the target calculation strategy to obtain the target operating parameters of the energy storage power generation equipment. During execution, the energy storage power generation equipment can input the target power load data into the calculation function included in the target calculation strategy to obtain the target operating parameters. Alternatively, the energy storage power generation equipment can input the target power load data into the calculation model corresponding to the target calculation strategy to obtain the target operating parameters output by the calculation model.

[0056] In this application, the target operating parameters refer to the parameters that control the energy storage power generation equipment to output electrical energy. The operating parameters may include at least one of the following: inverter output active power, inverter output reactive power, grid connection point q-axis voltage, inverter q-axis current, inverter d-axis current, and grid connection point frequency.

[0057] In the above-mentioned method for determining the operating parameters of energy storage power generation equipment, when the energy storage power generation equipment is in a power island state, the target power load data of the target area corresponding to the energy storage power generation equipment is first obtained. In the preset strategy library, the target calculation strategy for the operating parameters of the energy storage power generation equipment corresponding to the target power load data is determined. The strategy library includes the mapping relationship between each power load data and each calculation strategy. Based on the target calculation strategy and the target power load data, the target operating parameters of the energy storage power generation equipment are determined. By configuring the strategy library in the energy storage power generation equipment, the energy storage power generation equipment can independently perform the calculation operation of the operating strategy, avoiding the communication delay caused by external calculation, enabling the energy storage power generation equipment to quickly and stably supply power, and improving the power supply stability of the target area.

[0058] Based on the above exemplary embodiment, the following describes a method for determining the operating parameters of an energy storage power generation device in one or more exemplary embodiments. Taking the application of this method to the energy storage power generation device in Figure 1 as an example, the method specifically includes the following contents.

[0059] During the strategy library construction process, data pairs consisting of historical operating parameters of energy storage power generation equipment and historical power load data of the target area can be obtained through external computing devices. Multiple candidate calculation strategies are determined based on multiple data pairs, and a strategy library is constructed based on each candidate calculation strategy. In one optional embodiment provided in this application, as shown in Figure 3, the strategy library construction process includes steps 301 to 303:

[0060] Step 301: Obtain multiple historical operating parameters of the energy storage power generation device in power island state, as well as the historical power load data of the target area corresponding to each historical operating parameter.

[0061] During implementation, external computing devices query multiple historical operating parameters of the energy storage power generation equipment in power island state within a historical time period, as well as the historical power load data of the target area corresponding to each historical operating parameter.

[0062] Step 302: Determine multiple candidate calculation strategies based on historical operating parameters and historical power load data.

[0063] During implementation, the external computing device performs fitting calculations based on each historical operating parameter and the corresponding historical power load data to obtain multiple candidate calculation functions, and generates candidate calculation strategies based on the candidate calculation functions.

[0064] In the process of generating computational strategies, a running parameter algorithm can be constructed based on the candidate computational functions, and a candidate computational strategy can be generated based on the running parameter algorithm. Alternatively, the candidate computational functions can be encapsulated into a running parameter computation model, and a candidate computational strategy can be generated based on the running parameter computation model.

[0065] Step 303: Construct a strategy library based on each candidate calculation strategy and each historical power load data.

[0066] During implementation, the historical power load data corresponding to each candidate calculation strategy is determined, and a mapping relationship between each candidate calculation strategy and the power load data is constructed. A strategy library is then built based on the mapping relationship and the candidate calculation strategies.

[0067] One optional implementation method provided in this application maps and calculates the historical operating parameters of the energy storage power generation device and the corresponding historical power load data to construct multiple candidate calculation strategies. A strategy library is then constructed based on the candidate calculation strategies and the historical power load data. The accuracy of the candidate calculation strategies in the strategy library is ensured by using historical data, thereby improving the accuracy of the operating parameters.

[0068] In practical scenarios, a fitting function (calculation function) can be constructed for the power load data and operating parameters. Based on this calculation function and fitting coefficient, a calculation strategy can be determined, and the operating parameters can be determined according to the power load data through fitting. For this purpose, the historical operating parameters and power load data of historical time periods can be fitted to establish a corresponding relationship. The reactive power data can be determined first, as shown in formula (5).

[0069] Formula (5);

[0070] Among them, Q load Q represents the reactive power of the load. L For the sake of emotional inefficiency, Q C For capacitive reactive power; for motor load conditions, Q LPartial power is proportional to active power, see formula (6):

[0071] Formula (6);

[0072] Among them, V N α is the rated voltage, α is the proportionality coefficient between active power and inductive reactive power, and β0 is the reactive power that is not proportional to the active power.

[0073] Furthermore, with the power grid structure unchanged, the capacitive reactive power can be considered a constant value, as shown in formula (7):

[0074] Formula (7);

[0075] Combining formulas (5) and (7), we obtain formula (8):

[0076] Formula (8);

[0077] Here, α and β are the fitting coefficients (calculated coefficients for running parameters).

[0078] In the process of generating the computational strategy, historical data can be clustered, and a suitable fitting coefficient can be determined for each clustering result. Candidate computational strategies are then determined based on the fitting coefficient and the computational function. In one optional implementation provided by this application, as shown in Figure 4, the process of determining the candidate computational strategy includes steps 401 to 403:

[0079] Step 401: Cluster the historical operating parameters and the corresponding historical power load data to obtain multiple clustering results.

[0080] During implementation, an aggregation algorithm was used to cluster the historical operating parameters and the corresponding historical power load data, resulting in multiple clustering results. The range of power load data corresponding to different clustering results was different.

[0081] During execution, historical data can be clustered using a Gaussian mixture model, and the Gaussian mixture coefficients for each group of load data can be calculated using the expectation-maximization algorithm. , average vector μ m Variance-covariance matrix Σ m .

[0082] For example, a responsibility function can be used to determine a specific historical power load data x. n Whether to include it in group m, see formula (9):

[0083] Formula (9);

[0084] Among them, z nm Let p be the responsibility variable, p represent the probability density function, and M be the total number of groups;

[0085] The density function for each cluster data group is shown in formula (10):

[0086] Formula (10);

[0087] Where, μ m Let Σ be the average vector of the load data for the m-th group. m Given the load variance-covariance matrix of the m-th group, we can obtain formulas (11) to (13):

[0088] Formula (11);

[0089] Formula (12);

[0090] Formula (13);

[0091] Where: N p Given the total number of load data, and substituting equations (11)-(13) back into equations (9) and (10), we obtain equation (14), where the clustering probability density function reaches its maximum value:

[0092] Formula (14);

[0093] Furthermore, after grouping, the least squares method is used, with active power and reactive power as independent and dependent variables respectively, and the goal is to minimize the mean square error (14), to obtain the calculation function shown in formula (15):

[0094] Formula (15);

[0095] Where: N m P represents the total number of data points in the m-th group. n,m Q n,m These are the active and reactive power values ​​of the nth group in the mth group, respectively;

[0096] The coefficient of determination R² is used to evaluate the estimation accuracy of the least squares algorithm. The value of R² ranges from -1 to 1. A higher value indicates higher estimation accuracy. See formula (16).

[0097] Formula (16);

[0098] in: For Q n,m The estimated value, This represents the average reactive power of the m-th group.

[0099] Step 402: For each clustering result, calculate the operating parameter calculation coefficient based on the preset power calculation function, the historical operating parameters included in the clustering result, and the historical power load data included in the clustering result.

[0100] During implementation, for each clustering result, the external computing device inputs the historical operating parameters and historical power load data included in the clustering result into a preset power calculation function to calculate the operating parameter calculation coefficients. These operating parameter calculation coefficients are the coefficients calculated by the power calculation function, and can also be fitting coefficients.

[0101] During the execution process, the external computing device inputs the historical operating parameters and historical power load data included in the clustering results into the preset power calculation function, such as the power calculation function shown in formula (15), and performs fitting processing to obtain the fitting coefficients α and β corresponding to the clustering results.

[0102] It should be noted that the power calculation function can be a group of functions, and the fitting function α and β can be determined based on the fitting function in the power calculation function.

[0103] Step 403: Based on the operating parameter calculation coefficients, power calculation function, and historical power load data included in the clustering results, candidate calculation strategies are generated.

[0104] During implementation, the external computing device determines the power load range corresponding to the clustering result based on historical power load data included in the clustering result. It then constructs a complete power calculation function based on operating parameter calculation coefficients and a power calculation function, establishing a correspondence between the power calculation function and the power load range to obtain candidate calculation strategies. Specifically, the function can be determined based on the operating parameters in the power calculation function to generate candidate calculation strategies.

[0105] One optional implementation method provided in this application establishes the relationship between different power load data and power calculation functions through clustering and fitting, and then constructs candidate calculation strategies. By using historical data to determine the calculation strategies in advance, the energy storage power generation equipment can directly determine the operating parameters based on the calculation strategies in the power island state, which ensures the accuracy of the operating parameters and improves the stability of power supply.

[0106] In determining the target calculation strategy, a target calculation strategy matching the target power load data can be determined from a preset strategy library. The target power load data is then calculated according to the target calculation strategy to obtain the target operating parameters. Different calculation strategies correspond to different power load data ranges. In one optional implementation provided by this application, as shown in Figure 5, step 202 includes steps 501 to 502:

[0107] Step 501: Determine the target power load range to which the target power load data belongs.

[0108] During implementation, the energy storage power generation equipment can query the target power load range corresponding to the target power load data in the data table; the data table can be preset in the energy storage power generation equipment, and the data table can record different power load ranges and the corresponding identifiers of different power load ranges; the energy storage power generation equipment can determine the identifier corresponding to the target power load data.

[0109] Step 502: In the strategy library, determine the target calculation strategy corresponding to the power load data based on the target power load range.

[0110] During implementation, the energy storage power generation equipment determines the target calculation strategy corresponding to the power load data in the strategy library based on the identifier corresponding to the target power load range; then, it calculates the target operating parameters according to the target calculation strategy. The target calculation strategy includes: target operating parameter calculation coefficients and target operating parameter calculation functions. The target operating parameter calculation coefficients can be target fitting coefficients, and the target operating parameter calculation functions can be target calculation functions.

[0111] One optional implementation method provided in this application uses a strategy library for strategy querying, which avoids real-time strategy determination, improves the efficiency of calculating the operating parameters of the energy storage power generation equipment, and thus improves the reliability and timeliness of the power supply from the energy storage power generation equipment.

[0112] In the calculation of the target operating parameters, the fitting coefficients can be substituted into the calculation function to obtain the target operating parameters; in an optional embodiment provided by this application, as shown in Figure 6, step 203 includes steps 601 to 602:

[0113] Step 601: Obtain the target operating parameter calculation coefficients and target operating parameter calculation functions included in the target calculation strategy.

[0114] During implementation, the target calculation strategy for energy storage power generation equipment includes the target operating parameter calculation coefficients and the target operating parameter calculation functions.

[0115] For example, the target operating parameter calculation function can be found in the above formula (1); the target operating parameter calculation function may include active power calculation function and reactive power calculation function.

[0116] Step 602: Substitute the power load data and the target operating parameter calculation coefficients into the target operating parameter calculation function to calculate the target operating parameters.

[0117] During implementation, the energy storage power generation equipment substitutes the power load data and the target operating parameter calculation coefficients into the target operating parameter calculation function to obtain the target operating parameters. These target operating parameters include active power and reactive power.

[0118] During execution, the energy storage power generation equipment can input the target operating parameter calculation coefficients into the active power calculation function and reactive power calculation function to obtain the load resonant frequency and quality factor. Based on the load resonant frequency and quality factor, it can calculate the inverter d-axis current ratio and inverter q-axis current ratio, and determine the active power and reactive power based on the inverter d-axis current ratio and inverter q-axis current ratio.

[0119] For example, by substituting the target operating parameter calculation coefficients into formula (2), the load resonant frequency and quality factor are obtained. Based on the load resonant frequency and quality factor, the inverter d-axis current ratio is calculated (see formula (17), and the inverter q-axis current ratio is calculated (see formula (18)).

[0120] Formula (17);

[0121] Formula (18);

[0122] The reference value of the inverter's q-axis current is determined based on the current ratio, as shown in formula (19):

[0123] Formula (19);

[0124] Formula (20);

[0125] Furthermore, the above current values ​​can be substituted into formula (1) to determine the active power and reactive power.

[0126] One optional implementation method provided in this application quickly and accurately determines the output of the energy storage power generation device by pre-setting a calculation formula, thereby enabling the energy storage power generation device to autonomously and quickly determine its operating parameters and then rapidly provide regional power supply.

[0127] In practical scenarios, energy storage power generation equipment includes energy storage power generation vehicles, which can control the batteries of the energy storage power generation vehicles to supply power to electrical equipment in the target area according to operating parameters; in one optional embodiment provided in this application, as shown in FIG7, the method further includes step 701:

[0128] Step 701: Send the target operating parameters to the control equipment of the energy storage generator vehicle.

[0129] The target operating parameters are used to control the batteries in the energy storage generator vehicle to supply power to electrical equipment in the target area.

[0130] During implementation, the energy storage generator vehicle sends the target operating parameters to the control equipment. Based on the operating parameters, the control equipment first adjusts the system parameters. After the adjustment is completed, it controls the inverter to supply power to the outside with the adjusted voltage, current and frequency. The control equipment controls the battery to supply DC power to the outside according to the preset current and voltage, which is converted by the inverter.

[0131] In one embodiment, referring to Figure 8, a flowchart of a method for determining the operating parameters of an energy storage power generation device according to an embodiment of this application is shown. This method can be applied to the energy storage power generation device shown in Figure 1. As shown in Figure 8, the method for determining the operating parameters of the energy storage power generation device may include the following steps:

[0132] Step 801: Obtain the target power load data of the target area corresponding to the energy storage power generation equipment.

[0133] Step 802: Determine the target power load range to which the target power load data belongs.

[0134] Step 803: In the strategy library, determine the target calculation strategy corresponding to the power load data based on the target power load range.

[0135] Step 804: Obtain the fitting coefficients and calculation functions included in the target calculation strategy.

[0136] Step 805: Substitute the target power load data and fitting coefficients into the calculation function to obtain the target operating parameters.

[0137] The target operating parameters include active power and reactive power.

[0138] Step 806: The active power and reactive power are sent to the control equipment of the energy storage generator vehicle.

[0139] The active power and reactive power are used to control the batteries included in the energy storage generator vehicle to supply power to electrical equipment in the target area.

[0140] It should be noted that any one or more of steps 801 to 806 can be combined to form a new implementation method according to the needs of implementation and deployment. Furthermore, any one or more technical features in the technical solution composed of steps 801 to 806 can also be combined to form a new implementation method according to the actual deployment needs, or technical features in one or more optional implementations provided by one or more of the above embodiments can be combined to form a new implementation method. These will not be elaborated on here.

[0141] It should be understood that although the steps in the flowcharts of the embodiments described above are shown sequentially according to the arrows, these steps are not necessarily executed in the order indicated by the arrows. Unless explicitly stated herein, there is no strict order restriction on the execution of these steps, and they can be executed in other orders. Moreover, at least some steps in the flowcharts of the embodiments described above may include multiple steps or multiple stages. These steps or stages are not necessarily completed at the same time, but can be executed at different times. The execution order of these steps or stages is not necessarily sequential, but can be performed alternately or in turn with other steps or at least some of the steps or stages in other steps. It is understood that the steps in different embodiments can be freely combined as needed, and all non-contradictory solutions formed by such combinations are within the scope of protection of this application.

[0142] Based on the same inventive concept, this application also provides an apparatus for determining the operating parameters of an energy storage power generation device to implement the above-described method for determining the operating parameters of an energy storage power generation device. The solution provided by this apparatus is similar to the solution described in the above-described method. Therefore, the specific limitations in one or more embodiments of the apparatus for determining the operating parameters of an energy storage power generation device provided below can be found in the limitations of the method for determining the operating parameters of an energy storage power generation device described above, and will not be repeated here.

[0143] In an exemplary embodiment, as shown in FIG9, an operating parameter determination device for an energy storage power generation device is provided, comprising: a power load data acquisition module 901, a calculation strategy determination module 902, and an operating parameter determination module 903, wherein: the power load data acquisition module 901 is used to acquire target power load data of a target area corresponding to the energy storage power generation device; the calculation strategy determination module 902 is used to determine the target calculation strategy for the operating parameters of the energy storage power generation device corresponding to the target power load data in a preset strategy library, the strategy library including the mapping relationship between each power load data and each calculation strategy; and the operating parameter determination module 903 is used to determine the target operating parameters of the energy storage power generation device according to the target calculation strategy and the target power load data.

[0144] In one embodiment, the device further includes a historical data acquisition module, a candidate calculation strategy determination module, and a strategy library construction module, wherein: the historical data acquisition module is used to acquire multiple historical operating parameters of the energy storage power generation device in power islanding state, as well as historical power load data of the target area corresponding to each historical operating parameter; the candidate calculation strategy determination module is used to determine multiple candidate calculation strategies based on each historical operating parameter and each historical power load data; and the strategy library construction module is used to construct a strategy library based on each candidate calculation strategy and each historical power load data.

[0145] In one embodiment, the candidate calculation strategy determination module includes a clustering unit, a data calculation unit, and a calculation strategy determination unit. The clustering unit performs clustering processing on each historical operating parameter and the corresponding historical power load data to obtain multiple clustering results, with different clustering results corresponding to different ranges of power load data. The data calculation unit calculates operating parameter calculation coefficients for each clustering result based on a preset power calculation function, the historical operating parameters included in the clustering result, and the historical power load data included in the clustering result. The operating parameter calculation coefficients are the calculation coefficients of the power calculation function. The calculation strategy determination unit generates candidate calculation strategies based on the operating parameter calculation coefficients, the power calculation function, and the historical power load data included in the clustering result.

[0146] In one embodiment, the calculation strategy determination module 902 includes a range determination unit and a calculation strategy determination unit, wherein: the range determination unit is used to determine the target power load range to which the target power load data belongs; the calculation strategy determination unit is used to determine the target calculation strategy corresponding to the power load data in the strategy library according to the target power load range; wherein the target calculation strategy includes: target operating parameter calculation coefficients and target operating parameter calculation functions.

[0147] In one embodiment, the operating parameter determination module 903 includes a function acquisition unit and a calculation unit, wherein: the function acquisition unit is used to acquire the target operating parameter calculation coefficients and the target operating parameter calculation function included in the target calculation strategy; the calculation unit is used to substitute the power load data and the target operating parameter calculation coefficients into the target operating parameter calculation function to calculate the target operating parameters, which include active power and reactive power.

[0148] In one embodiment, the apparatus further includes a control unit, wherein the control unit is used to send target operating parameters to the control equipment of the energy storage power generation vehicle, the target operating parameters being used to control the battery included in the energy storage power generation vehicle to supply power to electrical equipment in the target area.

[0149] The various modules in the aforementioned energy storage power generation equipment operating parameter determination device can be implemented entirely or partially through software, hardware, or a combination thereof. These modules can be embedded in the processor of a computer device in hardware form or independent of it, or stored in the memory of a computer device in software form, so that the processor can call and execute the operations corresponding to each module.

[0150] In an exemplary embodiment, a computer device is provided, which may be a server, and its internal structure diagram is shown in Figure 10. The computer device includes a processor, memory, input / output interfaces (I / O), and a communication interface. The processor, memory, and I / O interfaces are connected via a system bus, and the communication interface is connected to the system bus via the I / O interfaces. The processor of the computer device provides computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and internal memory. The non-volatile storage medium stores an operating system, computer programs, and a database. The internal memory provides an environment for the operation of the operating system and computer programs in the non-volatile storage medium. The database of the computer device stores operating parameter determination data. The I / O interfaces of the computer device are used for exchanging information between the processor and external devices. The communication interface of the computer device is used for communication with external terminals via a network connection. When the computer program is executed by the processor, it implements a method for determining the operating parameters of an energy storage power generation device.

[0151] Those skilled in the art will understand that the structure shown in Figure 10 is merely a block diagram of a portion of the structure related to the present application and does not constitute a limitation on the computer device to which the present application is applied. Specific computer devices may include more or fewer components than those shown in the figure, or may combine certain components, or may have different component arrangements.

[0152] In one exemplary embodiment, a computer device is provided, including a memory and a processor. The memory stores a computer program, and the processor executes the computer program to perform the following steps: acquiring target power load data of a target area corresponding to an energy storage power generation device; determining a target calculation strategy for the operating parameters of the energy storage power generation device corresponding to the target power load data in a preset strategy library, wherein the strategy library includes a mapping relationship between each power load data and each calculation strategy; and determining the target operating parameters of the energy storage power generation device based on the target calculation strategy and the target power load data.

[0153] In one embodiment, when the processor executes the computer program, it further performs the following steps: acquiring multiple historical operating parameters of the energy storage power generation device in a power island state, and historical power load data of the target area corresponding to each historical operating parameter; determining multiple candidate calculation strategies based on each historical operating parameter and each historical power load data; and constructing a strategy library based on each candidate calculation strategy and each historical power load data.

[0154] In one embodiment, when the processor executes the computer program, it further performs the following steps: clustering each historical operating parameter and the historical power load data corresponding to each historical operating parameter to obtain multiple clustering results, with different ranges of power load data corresponding to different clustering results; for each clustering result, calculating operating parameter calculation coefficients based on a preset power calculation function, the historical operating parameters included in the clustering result, and the historical power load data included in the clustering result, the operating parameter calculation coefficients being the calculation coefficients of the power calculation function; and generating candidate calculation strategies based on the operating parameter calculation coefficients, the power calculation function, and the historical power load data included in the clustering result.

[0155] In one embodiment, when the processor executes the computer program, it further performs the following steps: determining the target power load range to which the target power load data belongs; in the strategy library, determining the target calculation strategy corresponding to the power load data based on the target power load range; wherein, the target calculation strategy includes: target operating parameter calculation coefficients and target operating parameter calculation functions.

[0156] In one embodiment, when the processor executes the computer program, it further performs the following steps: obtaining the target operating parameter calculation coefficients and target operating parameter calculation functions contained in the target calculation strategy; substituting the power load data and the target operating parameter calculation coefficients into the target operating parameter calculation function to calculate the target operating parameters, which include active power and reactive power.

[0157] In one embodiment, when the processor executes the computer program, it also performs the following steps: sending target operating parameters to the control device of the energy storage power generation vehicle, the target operating parameters being used to control the batteries included in the energy storage power generation vehicle to supply power to electrical equipment in the target area.

[0158] In one embodiment, a computer-readable storage medium is provided, on which a computer program is stored. When the computer program is executed by a processor, it performs the following steps: acquiring target power load data of a target area corresponding to an energy storage power generation device; determining, in a preset strategy library, a target calculation strategy for the operating parameters of the energy storage power generation device corresponding to the target power load data, wherein the strategy library includes the mapping relationship between each power load data and each calculation strategy; and determining the target operating parameters of the energy storage power generation device based on the target calculation strategy and the target power load data.

[0159] In one embodiment, when the processor executes the computer program, it further performs the following steps: acquiring multiple historical operating parameters of the energy storage power generation device in a power island state, and historical power load data of the target area corresponding to each historical operating parameter; determining multiple candidate calculation strategies based on each historical operating parameter and each historical power load data; and constructing a strategy library based on each candidate calculation strategy and each historical power load data.

[0160] In one embodiment, when the processor executes the computer program, it further performs the following steps: clustering each historical operating parameter and the historical power load data corresponding to each historical operating parameter to obtain multiple clustering results, with different ranges of power load data corresponding to different clustering results; for each clustering result, calculating operating parameter calculation coefficients based on a preset power calculation function, the historical operating parameters included in the clustering result, and the historical power load data included in the clustering result, the operating parameter calculation coefficients being the calculation coefficients of the power calculation function; and generating candidate calculation strategies based on the operating parameter calculation coefficients, the power calculation function, and the historical power load data included in the clustering result.

[0161] In one embodiment, when the processor executes the computer program, it further performs the following steps: determining the target power load range to which the target power load data belongs; in the strategy library, determining the target calculation strategy corresponding to the power load data based on the target power load range; wherein, the target calculation strategy includes: target operating parameter calculation coefficients and target operating parameter calculation functions.

[0162] In one embodiment, when the processor executes the computer program, it further performs the following steps: obtaining the target operating parameter calculation coefficients and target operating parameter calculation functions contained in the target calculation strategy; substituting the power load data and the target operating parameter calculation coefficients into the target operating parameter calculation function to calculate the target operating parameters, which include active power and reactive power.

[0163] In one embodiment, when the processor executes the computer program, it also performs the following steps: sending target operating parameters to the control device of the energy storage power generation vehicle, the target operating parameters being used to control the batteries included in the energy storage power generation vehicle to supply power to electrical equipment in the target area.

[0164] In one embodiment, a computer program product is provided, including a computer program that, when executed by a processor, performs the following steps: acquiring target power load data of a target area corresponding to an energy storage power generation device; determining, in a preset strategy library, a target calculation strategy for the operating parameters of the energy storage power generation device corresponding to the target power load data, wherein the strategy library includes a mapping relationship between each power load data and each calculation strategy; and determining the target operating parameters of the energy storage power generation device based on the target calculation strategy and the target power load data.

[0165] In one embodiment, when the processor executes the computer program, it further performs the following steps: acquiring multiple historical operating parameters of the energy storage power generation device in a power island state, and historical power load data of the target area corresponding to each historical operating parameter; determining multiple candidate calculation strategies based on each historical operating parameter and each historical power load data; and constructing a strategy library based on each candidate calculation strategy and each historical power load data.

[0166] In one embodiment, when the processor executes the computer program, it further performs the following steps: clustering each historical operating parameter and the historical power load data corresponding to each historical operating parameter to obtain multiple clustering results, with different ranges of power load data corresponding to different clustering results; for each clustering result, calculating operating parameter calculation coefficients based on a preset power calculation function, the historical operating parameters included in the clustering result, and the historical power load data included in the clustering result, the operating parameter calculation coefficients being the calculation coefficients of the power calculation function; and generating candidate calculation strategies based on the operating parameter calculation coefficients, the power calculation function, and the historical power load data included in the clustering result.

[0167] In one embodiment, when the processor executes the computer program, it further performs the following steps: determining the target power load range to which the target power load data belongs; in the strategy library, determining the target calculation strategy corresponding to the power load data based on the target power load range; wherein, the target calculation strategy includes: target operating parameter calculation coefficients and target operating parameter calculation functions.

[0168] In one embodiment, when the processor executes the computer program, it further performs the following steps: obtaining the target operating parameter calculation coefficients and target operating parameter calculation functions contained in the target calculation strategy; substituting the power load data and the target operating parameter calculation coefficients into the target operating parameter calculation function to calculate the target operating parameters, which include active power and reactive power.

[0169] In one embodiment, when the processor executes the computer program, it also performs the following steps: sending target operating parameters to the control device of the energy storage power generation vehicle, the target operating parameters being used to control the batteries included in the energy storage power generation vehicle to supply power to electrical equipment in the target area.

[0170] It should be noted that the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data used for analysis, data stored, data displayed, etc.) involved in this application are all information and data authorized by the user or fully authorized by all parties, and the collection, use and processing of the relevant data must comply with relevant regulations.

[0171] Those skilled in the art will understand that all or part of the processes in the methods of the above embodiments can be implemented by a computer program instructing related hardware. The computer program can be stored in a non-volatile computer-readable storage medium, and when executed, it can include the processes of the embodiments of the above methods. Any references to memory, databases, or other media used in the embodiments provided in this application can include at least one of non-volatile memory and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetic random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory can include random access memory (RAM) or external cache memory, etc. By way of illustration and not limitation, RAM can take many forms, such as Static Random Access Memory (SRAM) or Dynamic Random Access Memory (DRAM). The databases involved in the embodiments provided in this application may include at least one type of relational database and non-relational database. Non-relational databases may include, but are not limited to, blockchain-based distributed databases. The processors involved in the embodiments provided in this application may be general-purpose processors, central processing units, graphics processing units, digital signal processors, programmable logic devices, quantum computing-based data processing logic devices, artificial intelligence (AI) processors, etc., and are not limited to these.

[0172] The technical features of the above embodiments can be combined in any way. For the sake of brevity, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this application.

[0173] The embodiments described above are merely illustrative of several implementation methods of this application, and while the descriptions are specific and detailed, they should not be construed as limiting the scope of this patent application. It should be noted that those skilled in the art can make various modifications and improvements without departing from the concept of this application, and these all fall within the protection scope of this application. Therefore, the protection scope of this application should be determined by the appended claims.

Claims

1. A method for determining the operating parameters of an energy storage power generation device, characterized in that, The method, applied to energy storage power generation equipment, includes: acquiring target power load data of a target area corresponding to the energy storage power generation equipment; determining, in a preset strategy library, a target calculation strategy for the operating parameters of the energy storage power generation equipment corresponding to the target power load data, wherein the strategy library includes a mapping relationship between each power load data and each calculation strategy; and determining the target operating parameters of the energy storage power generation equipment based on the target calculation strategy and the target power load data.

2. The method according to claim 1, characterized in that, The process of constructing the strategy library includes: acquiring multiple historical operating parameters of the energy storage power generation device in a power island state, and historical power load data of the target area corresponding to each historical operating parameter; determining multiple candidate calculation strategies based on each historical operating parameter and each historical power load data; and constructing the strategy library based on each candidate calculation strategy and each historical power load data.

3. The method according to claim 2, characterized in that, The step of determining the target operating parameters of the energy storage power generation equipment based on the target calculation strategy and the target power load data includes: performing clustering processing on each of the historical operating parameters and the historical power load data corresponding to each of the historical operating parameters to obtain multiple clustering results, with different clustering results corresponding to different ranges of power load data; for each clustering result, calculating operating parameter calculation coefficients based on a preset power calculation function, the historical operating parameters included in the clustering result, and the historical power load data included in the clustering result, wherein the operating parameter calculation coefficients are the calculation coefficients of the power calculation function; and generating the candidate calculation strategy based on the operating parameter calculation coefficients, the power calculation function, and the historical power load data included in the clustering result.

4. The method according to claim 1, characterized in that, Different calculation strategies correspond to different power load data ranges. The step of determining the target calculation strategy for the operating parameters of the energy storage power generation device corresponding to the target power load data in the preset strategy library includes: determining the target power load range to which the target power load data belongs; and determining the target calculation strategy corresponding to the target power load data in the strategy library based on the target power load range. The target calculation strategy includes: target operating parameter calculation coefficients and target operating parameter calculation functions.

5. The method according to any one of claims 1 to 4, characterized in that, The step of determining the target operating parameters of the energy storage power generation device based on the target calculation strategy and the target power load data includes: obtaining the target operating parameter calculation coefficients and the target operating parameter calculation function contained in the target calculation strategy; substituting the target power load data and the target operating parameter calculation coefficients into the target operating parameter calculation function to calculate the target operating parameters, wherein the target operating parameters include active power and reactive power.

6. The method according to claim 1, characterized in that, The energy storage power generation device includes an energy storage power generation vehicle, and the method further includes: sending the target operating parameters to the control device of the energy storage power generation vehicle, wherein the target operating parameters are used to control the battery included in the energy storage power generation vehicle to supply power to electrical equipment in the target area.

7. A device for determining the operating parameters of an energy storage power generation device, characterized in that, The device includes: a power load data acquisition module for acquiring target power load data of a target area corresponding to the energy storage power generation device; a calculation strategy determination module for determining, in a preset strategy library, a target calculation strategy for the operating parameters of the energy storage power generation device corresponding to the target power load data, wherein the strategy library includes a mapping relationship between each power load data and each calculation strategy; and an operating parameter determination module for determining the target operating parameters of the energy storage power generation device based on the target calculation strategy and the target power load data.

8. A computer device comprising a memory and a processor, wherein the memory stores a computer program, characterized in that, When the processor executes the computer program, it implements the steps of the method according to any one of claims 1 to 6.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by a processor, it implements the steps of the method according to any one of claims 1 to 6.

10. A computer program product, comprising a computer program, characterized in that, When the computer program is executed by a processor, it implements the steps of the method according to any one of claims 1 to 6.

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