Optical storage park micro-grid regulation method and device, electronic equipment and storage medium

Abstract

This application provides a microgrid control method and device, electronic equipment, and storage medium for a photovoltaic-storage park, belonging to the field of energy management technology. The method is applied to a photovoltaic-storage park microgrid system, which includes an energy storage system and a microgrid controller. The energy storage system is communicatively connected to the microgrid controller and is connected in parallel with the power grid. The method is executed by the microgrid controller and includes: acquiring the power load of the photovoltaic-storage park and the incoming power of the power grid; if the power load exceeds a preset power grid incoming power threshold, and the current period is a peak-price period, determining a first control threshold; and controlling the energy storage system to discharge to the power load when the power grid incoming power exceeds the first control threshold. The photovoltaic-storage park microgrid control method provided in this application can improve the precision of photovoltaic-storage park microgrid control.

Description

Technical Field

[0001] This application belongs to the field of energy management technology, and more specifically, it relates to a microgrid control method and device, electronic equipment, and storage medium for a photovoltaic-storage park. Background Technology

[0002] With the development of distributed photovoltaic (PV) and energy storage technologies, microgrids in PV-storage parks combine PV power generation with energy storage systems. This allows them to absorb surplus PV power, smooth out power output fluctuations, and utilize peak-valley electricity price differences to "smooth out peaks and fill valleys," thereby improving the utilization rate of clean energy and reducing the cost of purchasing grid electricity during peak hours. Therefore, PV-storage park microgrids have become an important way to improve the park's energy self-sufficiency rate and reduce electricity costs.

[0003] Currently, the control strategies of microgrids in photovoltaic-storage parks mostly adopt fixed threshold triggering of energy storage charging and discharging, resulting in extensive energy storage charging and discharging management and failing to achieve efficient energy utilization. Summary of the Invention

[0004] The purpose of this application is to provide a method and device for the control of a microgrid in a photovoltaic and energy storage park, as well as electronic equipment and storage medium, so as to improve the precision of the control of the microgrid in the photovoltaic and energy storage park.

[0005] A first aspect of this application provides a method for controlling a microgrid in a photovoltaic and energy storage park, comprising:

[0006] The method is applied to a solar-storage park microgrid system, which includes an energy storage system and a microgrid controller. The energy storage system is communicatively connected to the microgrid controller and is connected in parallel with the power grid. The method is executed by the microgrid controller and includes:

[0007] Obtain the power load and grid incoming power of the photovoltaic and energy storage park;

[0008] If the power of the electricity load is greater than the preset power threshold of the grid incoming line, and the current time period is a period of flat electricity price, a first control threshold is determined, and when the power of the grid incoming line is greater than the first control threshold, the energy storage system is controlled to discharge to the electricity load.

[0009] The method for determining the first control threshold includes:

[0010] The first discharge power is determined based on the rated discharge power of the energy storage system and a preset proportional coefficient.

[0011] The difference between the power grid incoming power threshold and the predicted average load power for the current period is calculated, and this difference is used as the second discharge power; wherein, the predicted average load power for the current period is obtained based on historical data of the power load.

[0012] The minimum power between the first discharge power and the second discharge power is taken as the third discharge power;

[0013] The difference between the preset power input threshold and the third discharge power is used as the first control threshold.

[0014] A second aspect of this application provides a microgrid control device for a photovoltaic-storage park, disposed in a microgrid controller. The microgrid controller is disposed in the photovoltaic-storage park microgrid system, which further includes an energy storage system. The energy storage system is communicatively connected to the microgrid controller and is connected in parallel with the power grid. The device includes:

[0015] The data acquisition module is used to acquire the power load and incoming power of the photovoltaic-storage park.

[0016] The charging and discharging control module is used to determine a first control threshold when the power of the electrical load is greater than a preset power threshold of the grid and the current time period is a period of flat electricity price, and to control the energy storage system to discharge to the electrical load when the power of the grid is greater than the first control threshold.

[0017] The method for determining the first control threshold includes:

[0018] The first discharge power is determined based on the rated discharge power of the energy storage system and a preset proportional coefficient.

[0019] The difference between the power grid incoming power threshold and the predicted average load power for the current period is calculated, and this difference is used as the second discharge power; wherein, the predicted average load power for the current period is obtained based on historical data of the electricity load power;

[0020] The minimum power between the first discharge power and the second discharge power is taken as the third discharge power;

[0021] The difference between the preset power input threshold and the third discharge power is used as the first control threshold.

[0022] A third aspect of this application provides an electronic device, including a memory, a processor, and a computer program stored in the memory and running on the processor, wherein the processor executes the computer program to implement the steps of the above-described photovoltaic-storage park microgrid control method.

[0023] In a fourth aspect of this application, a computer-readable storage medium is provided, the computer-readable storage medium storing a computer program, which, when executed by a processor, implements the steps of the above-described photovoltaic-storage park microgrid control method.

[0024] The beneficial effects of the microgrid control method and device, electronic equipment, and storage medium for photovoltaic and energy storage parks provided in this application embodiment are as follows:

[0025] In this embodiment, when the mains power cannot meet the power demand of the photovoltaic-storage park's equipment and the current time period is a peak electricity price period, the first discharge power is calculated with extending the cycle life of the energy storage system as the first constraint. Simultaneously, the second discharge power is calculated with stabilizing the grid's incoming power as the second constraint. Based on this, the minimum of the first and second discharge powers is taken as the third discharge power, which characterizes the maximum effective discharge capacity of the energy storage system. The difference between a preset grid incoming power threshold and the third discharge power is used as the first control threshold. When the grid incoming power exceeds the first control threshold, the microgrid controller controls the energy storage system to discharge to the load. Compared to traditional fixed-threshold control strategies, the method in this embodiment can improve the precision of microgrid control in the photovoltaic-storage park, achieving the control objectives of stabilizing grid incoming power and extending the lifespan of the energy storage system. Attached Figure Description

[0026] To more clearly illustrate the technical solutions in the embodiments of this application, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0027] Figure 1 A schematic block diagram of a photovoltaic and energy storage park microgrid system provided in an embodiment of this application;

[0028] Figure 2 A schematic flowchart illustrating a microgrid control method for a photovoltaic-storage park provided in an embodiment of this application;

[0029] Figure 3 A structural block diagram of a microgrid control device for a photovoltaic and energy storage park provided in an embodiment of this application;

[0030] Figure 4 This is a schematic block diagram of an electronic device provided in an embodiment of this application. Detailed Implementation

[0031] In the following description, specific details such as particular system architectures and techniques are set forth for illustrative purposes and not for limitation, in order to provide a thorough understanding of the embodiments of this application. However, those skilled in the art will understand that this application may also be implemented in other embodiments without these specific details. In other instances, detailed descriptions of well-known systems, apparatuses, circuits, and methods have been omitted so as not to obscure the description of this application with unnecessary detail.

[0032] It is understood that in the embodiments of this application, data such as user information are involved. When the embodiments of this application are applied to specific products or technologies, user permission or consent is required, and the collection, use and processing of related data must comply with relevant laws, regulations and standards.

[0033] It should be noted that the terms "first," "second," etc., used in the specification, claims, and drawings of this application are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such use of data can be interchanged where appropriate so that the embodiments of this application described herein can be implemented in sequences other than those illustrated or described herein.

[0034] To make the objectives, technical solutions, and advantages of this application clearer, the following description will be provided in conjunction with the accompanying drawings and specific embodiments.

[0035] Please refer to Figure 1 , Figure 1 This is a schematic diagram of a photovoltaic-storage park microgrid system according to an embodiment of this application. The main equipment of the photovoltaic-storage park microgrid system includes an Integrated Energy Management System (iEMS), a network switch, an anti-reverse current monitoring terminal, a microgrid controller, and switches at various levels. The iEMS communicates with the microgrid controller and the energy storage system via Ethernet. The microgrid controller communicates with the anti-reverse current monitoring terminal, the photovoltaic inverter, the low-voltage main incoming switch of the distribution transformer, the adjustable load incoming switch, and the energy storage system incoming switch via RS485 to achieve data acquisition and control.

[0036] Please refer to Figure 2 , Figure 2 This is a flowchart illustrating a microgrid control method for a photovoltaic-storage park according to an embodiment of this application. The microgrid control method for a photovoltaic-storage park provided in this embodiment can be executed by a microgrid controller, and the method may include:

[0037] S101: Obtain the power load and incoming power of the photovoltaic-storage park.

[0038] In this embodiment, the power load is the real-time total power consumption of all electrical equipment (including production equipment, office loads, and auxiliary facilities) within the photovoltaic-storage park, which can be collected by a meter installed at the park's total load input terminal. The grid input power is the real-time power supplied by the public power grid (mains power) to the photovoltaic-storage park, which can be collected by a smart meter installed at the grid connection node between the power grid and the park's microgrid. The collection frequencies of the power load power and the grid input power can be kept consistent to ensure the timing synchronization of the two types of parameters.

[0039] S102: If the power of the electricity load is greater than the preset power threshold of the grid incoming line, and the current period is a period of flat electricity price, determine the first control threshold, and when the power of the grid incoming line is greater than the first control threshold, control the energy storage system to discharge to the electricity load.

[0040] The method for determining the first control threshold includes:

[0041] The first discharge power is determined based on the rated discharge power of the energy storage system and a preset proportional coefficient.

[0042] The difference between the incoming power threshold of the power grid and the predicted average load power for the current period is calculated, and this difference is used as the second discharge power; wherein, the predicted average load power for the current period is obtained based on historical data of electricity load power;

[0043] The minimum power between the first discharge power and the second discharge power is taken as the third discharge power;

[0044] The difference between the preset power threshold of the incoming power grid and the third discharge power is used as the first control threshold.

[0045] In this embodiment, the preset power threshold of the incoming power grid refers to the maximum safe power carrying capacity allowed by the incoming power grid line, which can be calculated from the cable current carrying capacity and voltage level. The specific calculation formula is as follows: ,in, The threshold power of the incoming power grid. For voltage level, The overcurrent protection current threshold, The power factor angle.

[0046] If the power load exceeds the preset grid incoming power threshold, it indicates that the grid power cannot meet the power demand of the equipment. Therefore, the energy storage system needs to be triggered to discharge, dynamically increasing the power supply capacity of the park to ensure normal power consumption for the equipment. Specifically, the discharge trigger threshold for the energy storage system is determined for three scenarios: off-peak electricity price periods, low-price periods, and peak electricity price periods.

[0047] (1) The current time period is during the off-peak electricity price period:

[0048] When the power load exceeds the preset grid input power threshold, and the current period is during off-peak electricity pricing, the consideration is firstly that when the energy storage system's battery discharges at a low rate (0.2C~0.5C), the internal electrochemical reaction is gradual, and the rate of lithium ion insertion / extraction from the electrode material is slow, preventing irreversible damage such as rapid wear of the electrode structure or electrolyte decomposition. The cycle life can reach 3000~6000 cycles (or even higher). Therefore, this embodiment takes extending the cycle life of the energy storage system as the first constraint, limiting the discharge power of the energy storage system during off-peak electricity pricing to 30%~50% of the rated discharge power, which is equivalent to controlling the discharge rate within the low-loss range of 0.3C~0.5C. Accordingly, the first discharge power can be obtained as:

[0049] ;

[0050] in, Indicates the first discharge power. This indicates the rated discharge power of the energy storage system. This indicates a preset scaling factor (e.g., 0.3~0.5).

[0051] Meanwhile, considering that during off-peak periods, the main function of the energy storage system is to compensate for fluctuations exceeding the normal load, stabilizing the grid's incoming power near the normal load, the average power consumption of historical loads for the same period can be used as the predicted average load power for the current period, and this predicted average load power can be taken as the normal load for the current period. Based on this, with stabilizing the grid's incoming power as the second constraint, the second discharge power can be calculated based on the grid's incoming power threshold and the predicted average load power for the current period.

[0052] ;

[0053] in, Indicates the second discharge power. Indicates the power threshold of the power grid incoming line. This represents the predicted average load power for the current time period.

[0054] Based on the first and second discharge powers, if the first discharge power is less than or equal to the second discharge power, in order to force the energy storage system to operate in the low-loss range, the first discharge power can be used as the upper limit of discharge (i.e., the third discharge power). This is done at the cost of sacrificing some fluctuation compensation capability to ensure the long-term safe operation of the energy storage system. At the same time, since the first discharge power can still cover most short-term load fluctuations, it will not affect the overall stability of the grid power.

[0055] When the first discharge power exceeds the second discharge power, if the energy storage system discharges at the first discharge power, it will exceed the actual compensation required by the power grid, resulting in ineffective consumption of energy storage capacity and potentially leading to a lack of available power during peak electricity periods. In this case, the second discharge power can be used as the upper limit of discharge (i.e., the third discharge power) to ensure that the energy storage system can maintain the power input to the power grid at a stable level while also reserving capacity for power compensation during peak periods.

[0056] Based on the comparison of the magnitudes of the first and second discharge powers, this embodiment uses the minimum of the first and second discharge powers as the third discharge power, expressed by the following formula:

[0057] ;in, Indicates the third discharge power. Indicates the first discharge power. This indicates the second discharge power.

[0058] Furthermore, by subtracting the third discharge power from the grid incoming power threshold, the first control threshold can be obtained. The first control threshold is used as the discharge trigger threshold of the energy storage system. That is, when the grid incoming power is greater than the first control threshold, the microgrid controller controls the energy storage system to discharge to the electrical load.

[0059] As can be seen from the above, in this embodiment, when the mains power cannot meet the power demand of the photovoltaic-storage park's equipment and the current time period is a peak electricity price period, the first discharge power is calculated with extending the cycle life of the energy storage system as the first constraint; simultaneously, the second discharge power is calculated with stabilizing the grid incoming power as the second constraint; based on this, the minimum value between the first and second discharge powers is taken as the third discharge power, which can characterize the maximum effective discharge capacity of the energy storage system. The difference between the preset grid incoming power threshold and the third discharge power is taken as the first control threshold. When the grid incoming power is greater than the first control threshold, the microgrid controller controls the energy storage system to discharge to the load. Compared with the traditional fixed threshold control strategy, the method of this embodiment can improve the precision of microgrid control in the photovoltaic-storage park and achieve the control objectives of stabilizing grid incoming power and extending the life of the energy storage system.

[0060] (2) The current period is a low electricity price period:

[0061] If the power of the electricity load is greater than the preset power threshold of the grid incoming line, and the current period is a low electricity price period, a second control threshold is determined, and when the power of the grid incoming line is greater than the second control threshold, the energy storage system is controlled to discharge to the electricity load.

[0062] The determination method for the second control threshold includes:

[0063] Obtain the minimum discharge power of the energy storage system;

[0064] The correction amount is determined based on the historical power load fluctuation value corresponding to the current time period;

[0065] The fourth discharge power is determined based on the minimum discharge power and correction amount of the energy storage system;

[0066] The second control threshold is determined based on the grid incoming power threshold and the fourth discharge power.

[0067] In this embodiment, if the current time period is during a low electricity price period, the grid power should be used as much as possible, and the power from the energy storage system should be used as little as possible to take advantage of the low-priced electricity during the off-peak period and reduce electricity costs. Considering that the energy storage system has a minimum discharge power, which is determined by the battery type of the energy storage unit and the minimum operating power of the power conversion system (PCS, the interface device between the energy storage system and the grid), such as the minimum discharge power of a lithium battery energy storage system, which is usually 5% to 10% of the rated power, if the discharge power of the energy storage system is lower than the minimum discharge power, the power conversion system will trigger a protection shutdown due to low operating efficiency. Repeated start-stop cycles will accelerate the wear and tear on the battery and the power conversion system.

[0068] Meanwhile, to avoid frequent start-ups and false triggers of the energy storage system caused by load fluctuations, historical power load data for the same period can be obtained. Through statistical analysis, the fluctuation value of the power load for the corresponding historical period can be obtained as the historical power load fluctuation value for the current period. Based on the historical power load fluctuation value for the current period, the minimum discharge power of the energy storage system can be corrected to obtain the fourth discharge power. The fourth discharge power can characterize the minimum effective discharge power threshold that is adapted to the load fluctuation characteristics of the current period.

[0069] The historical corresponding time period refers to a historical time period that is consistent with the current time period in terms of date type (weekday / weekend / holiday), specific time period (e.g., 9:00-9:30, 16:00-16:30), and seasonal attribute. The fluctuation value of electricity load power can be characterized by the standard deviation of electricity load power at multiple consecutive time points within the corresponding time period. For example, if the current time period is Monday 9:00-9:15, the calculation process for the fluctuation value of electricity load power in the historical corresponding time period can be as follows: first calculate the standard deviation of electricity load power for each Monday 9:00-9:30 in the past month, and then calculate the average of the above multiple standard deviations to obtain the fluctuation value of electricity load power in the historical corresponding time period.

[0070] The larger the historical power load fluctuation value corresponding to the current time period, the greater the load fluctuation in the current time period, and the greater the fourth discharge power. Specifically, the fourth discharge power can be calculated using the following formula:

[0071] ;

[0072] in, Indicates the fourth discharge power. This indicates the minimum discharge power of the energy storage system. This indicates the preset correction factor (e.g., 1.2~1.5). This represents the historical power load fluctuation value corresponding to the current time period. It can characterize the natural fluctuation range of load under normal conditions, based on the statistical law of normal distribution, and the actual fluctuation value of load. The probability is 90%, and the actual load fluctuation value is... The probability is 95%, with a small amount of adjustment redundancy reserved, and the final determination is... This approach can both prevent the energy storage system from frequently charging and discharging and increasing losses due to setting the second control threshold too low, and prevent the second control threshold from being set too high, which would prevent timely compensation for grid fluctuations and ensure grid power stability.

[0073] Based on the fourth discharge power, the second control threshold can be obtained by subtracting the grid incoming power threshold from the fourth discharge power. The second control threshold is used as the discharge trigger threshold of the energy storage system. That is, when the grid incoming power is greater than the second control threshold, the microgrid controller controls the energy storage system to discharge to the electrical load.

[0074] As can be seen from the above, this embodiment determines the fourth discharge power based on the minimum discharge power of the energy storage system and the fluctuation value of the historical electricity load power during the same period. The fourth discharge power can characterize the minimum effective discharge power threshold that is adapted to the load fluctuation characteristics of the current period. The second control threshold is determined based on the fourth discharge power, which can filter short-term load fluctuations, avoid frequent start-ups and shutdowns of the energy storage system, and thus extend the life of the energy storage system.

[0075] (3) The current time period is during peak electricity price periods:

[0076] During peak electricity price periods, grid power should be used as little as possible, and energy storage systems should be used as much as possible. Therefore, microgrid controllers can control the energy storage system to discharge at full power (maximum discharge power) to minimize the power input to the grid.

[0077] It should be noted that when controlling the discharge of the energy storage system, the microgrid controller must consider the current state of charge (SOC) of the energy storage system, and will only discharge if the current SOC of the energy storage system is greater than the lower limit SOC. minWhen the lithium battery is at 20%~30%, the energy storage system discharge control is executed.

[0078] In one embodiment of this application, the method for determining the average load power forecast value for the current time period includes:

[0079] Obtain power load sequences for multiple historical dates; each historical date's power load sequence includes power load at multiple consecutive time points within that historical date.

[0080] According to the preset time length, the power consumption sequence of each historical date is divided into multiple time windows, and the power consumption sequence within each time window is a subsequence;

[0081] Calculate the average power of the electrical load for each subsequence to obtain the average load power of the subsequence;

[0082] For each time window, the average of the average load power of the subsequences of multiple historical dates within that time window is taken as the historical average load power within that time window;

[0083] Determine the time window to which the current period belongs as the target time window, and use the historical average load power within the target time window as the predicted average load power value for the current period.

[0084] In this embodiment, the predicted average load power for the current period can be determined based on the historical load power of the same period. Specifically, multiple historical dates' load power sequences can be obtained, each historical date's load power sequence including the load power at multiple consecutive time points within each historical date; each historical date is divided into equal-length time windows according to a preset time length (e.g., 30 minutes), load subsequences within each time window are extracted, and the average load power of each subsequence is calculated to obtain the average load power of the subsequence; the average of the average load power of the subsequences within the same time window of multiple historical dates is taken as the historical average load power within that time window; finally, the target time window corresponding to the current period is matched, and its historical average load power is taken as the predicted average load power for the current period.

[0085] Furthermore, considering the differences in electricity load characteristics between weekdays, weekends, and holidays, historical average load power can be statistically analyzed according to date type, thereby improving the prediction accuracy of the average load power forecast for the current period.

[0086] Specifically, the electricity load power series from multiple historical dates can be first divided into weekday datasets, weekend datasets, and holiday datasets based on date type. For each type of dataset, the above-mentioned time window division, subsequence average load power calculation, and historical average load power calculation operations for each time window are performed. Taking the weekday dataset as an example, the subsequence average load power of all weekdays within the same time window can be extracted, and their average value can be taken as the historical average load power of the corresponding weekday for that time window. Using the same method, the historical average load power for each time window of weekends and holidays can be obtained separately.

[0087] Based on this, when matching the target time window for the current period, first determine the date type of the current period (e.g., classify Monday as a weekday, Saturday as a weekend, and the Spring Festival holiday as a public holiday), and then call the historical average load power of the target time window under the corresponding date type dataset, and use it as the predicted value of the average load power for the current period.

[0088] As can be seen from the above, this embodiment can characterize the time-period differences in electricity load characteristics by dividing the time window. For each time window, the average of the average load power of multiple historical dates within that time window is taken as the historical average load power within that time window. This can eliminate the random fluctuation interference of electricity load power on a single historical date, and the resulting predicted average load power for the current time period is closer to the actual load situation for the current time period. The predicted average load power for the current time period can accurately characterize the normal level of the current time period, providing an accurate data basis for setting the first control threshold.

[0089] In one embodiment of this application, the method for determining the preset scaling factor includes:

[0090] Calculate the power load fluctuation value for the current period;

[0091] If the power fluctuation value of the current period's electricity load is greater than the preset fluctuation threshold, the preset proportional coefficient will be set as the first coefficient.

[0092] If the power fluctuation value of the current period is less than or equal to the preset fluctuation threshold, the preset proportional coefficient is set as the second coefficient.

[0093] The first coefficient is greater than the second coefficient.

[0094] In this embodiment, considering that when the power load fluctuates significantly during the current period, the power load will frequently approach the grid's incoming power threshold. Relying solely on low-power discharge cannot effectively mitigate these fluctuations and could easily trigger an grid overload warning. Therefore, this embodiment adjusts the discharge power of the energy storage system based on the degree of power load fluctuation during the current period, which can effectively suppress load fluctuations and avoid overload risks.

[0095] Specifically, the relative standard deviation of the power load at multiple consecutive time points within the current period (e.g., within 15 minutes prior to the current moment) can be calculated as the power load fluctuation value for the current period. Simultaneously, a fluctuation threshold (e.g., 10%) can be preset. If the power load fluctuation value for the current period is greater than the preset threshold, it indicates a large fluctuation in the power load. In this case, the preset proportional coefficient can be set to a larger first coefficient (e.g., 0.5) to increase the maximum discharge power of the energy storage system and quickly offset load spikes. If the power load fluctuation value for the current period is less than or equal to the preset threshold, it indicates a stable power load. In this case, the preset proportional coefficient can be set to a smaller second coefficient (e.g., 0.3) to control the energy storage system to operate in a lower discharge rate range (around 0.3C), further reducing equivalent battery internal resistance loss and extending cycle life.

[0096] The relative standard deviation is a commonly used concept in statistics, and its calculation formula is as follows:

[0097] ;

[0098] in, This represents the relative standard deviation, which is the fluctuation value of electricity load power in the current period. This represents the (absolute) standard deviation of load power at multiple consecutive time points within the current period. This represents the average power consumption at multiple consecutive time points within the current period. Considering that the (absolute) standard deviation varies with the baseline power consumption—for example, a standard deviation of 5kW is considered a large fluctuation during low-power periods, but a small fluctuation during high-power periods—this embodiment uses the relative standard deviation as the power consumption fluctuation value for the current period. This eliminates the influence of the baseline power consumption on fluctuation determination and more objectively reflects the relative fluctuation range of the load during the current period.

[0099] As can be seen from the above, this embodiment dynamically adjusts the preset proportional coefficient based on the fluctuation of the power load, which can reduce the ineffective discharge action of the energy storage system and reduce energy conversion loss while ensuring the stability of the incoming power of the power grid, thereby extending the service life of the energy storage system.

[0100] In one embodiment of this application, the energy storage system includes multiple energy storage cabinets connected in parallel, and the method for determining the rated discharge power of the energy storage system includes:

[0101] Obtain the energy storage status parameters corresponding to each of the multiple energy storage cabinets;

[0102] The energy storage status assessment value of each energy storage cabinet is determined based on the energy storage status parameters of each energy storage cabinet.

[0103] The discharge power limit for each energy storage cabinet is determined based on the energy storage status assessment value and the rated discharge power of each energy storage cabinet.

[0104] The rated discharge power of the energy storage system is obtained by summing the discharge power limits of each energy storage cabinet.

[0105] In this embodiment, the energy storage status parameters of each energy storage cabinet include the energy storage cabinet's State of Health (SOH) parameters, consistency parameters, aging parameters, and fault parameters. The consistency parameters include the voltage range and temperature range of individual cells, the aging parameters include the number of charge-discharge cycles and the equivalent battery internal resistance, and the fault parameters include the fault type and the corresponding fault time.

[0106] Based on this, the energy storage status level of each energy storage cabinet is determined according to its energy storage status parameters, including:

[0107] The consistency assessment value for each energy storage cabinet is determined based on the voltage range and temperature range of each individual cell in each energy storage cabinet.

[0108] The aging status assessment value of each energy storage cabinet is determined based on the number of charge-discharge cycles and the equivalent battery internal resistance of each cabinet.

[0109] The fault status assessment value of each energy storage cabinet is determined based on the fault type and corresponding fault time of each energy storage cabinet.

[0110] The energy storage status assessment value of each energy storage cabinet is obtained by weighted summing of the health status parameters, consistency assessment value, aging status assessment value and fault status assessment value.

[0111] In this embodiment, each energy storage cabinet contains multiple individual batteries connected in series and parallel, and each cabinet is equipped with a Battery Management System (BMS). The BMS collects parameters such as voltage, current, temperature, internal resistance, remaining capacity (SOC), state of health (SOH), fault type, and corresponding fault time of the individual batteries within the cabinet. Further, based on the individual battery health parameters and the series-parallel topology, the BMS can obtain the energy storage cabinet's health parameters through the "bottleneck effect" or weighted calculation. Similarly, based on the individual battery internal resistance and the series-parallel topology, the BMS can obtain the equivalent battery internal resistance of the energy storage cabinet through the "bottleneck effect" or weighted calculation. Simultaneously, the BMS can calculate the maximum / minimum voltage and temperature values ​​of individual batteries at the same time, and obtain the voltage and temperature ranges of the individual batteries in the energy storage cabinet through difference calculation. Furthermore, the BMS can automatically count the number of charge-discharge cycles based on the changes in the energy storage cabinet's charge-discharge capacity and a preset counting rule.

[0112] Based on this, the consistency assessment value for each energy storage unit can be calculated using the following formula:

[0113] ;

[0114] in,

[0115] ;

[0116] ;

[0117] In the above formula, Indicates the consistency assessment value. This represents the voltage consistency assessment value. This indicates the temperature consistency assessment value. This indicates the extreme voltage difference of a single cell. This indicates the preset voltage range alarm threshold (e.g., 50mV), representing the voltage range of a single cell. The larger the value, the higher the corresponding voltage consistency assessment value. The smaller, when When this occurs, it indicates that a differential pressure over-limit fault has occurred, and the corresponding voltage consistency assessment value is... ; This indicates an extreme temperature difference in a single cell. This indicates the preset temperature range alarm threshold (e.g., 5℃), and the temperature range of a single cell. The larger the value, the higher the corresponding temperature consistency assessment value. The smaller, when When this occurs, it indicates that a temperature difference exceeding the limit fault has occurred, and the corresponding temperature consistency assessment value is... ; , This represents the weighting coefficient, which can all be 0.5.

[0118] Meanwhile, the aging status assessment value of each energy storage cabinet can be calculated using the following formula:

[0119] ;

[0120] in,

[0121] ;

[0122] In the above formula, This indicates the aging status assessment value. This represents the evaluation value for the number of charge-discharge cycles. This represents the equivalent internal resistance assessment value of the battery. Indicates the number of charge-discharge cycles. This indicates the rated number of cycles (e.g., 6000) and the number of charge / discharge cycles of the energy storage cabinet. The larger the value, the higher the corresponding charge-discharge cycle count assessment value. The smaller, when When this time, it indicates that the energy storage cabinet has exceeded its rated cycle life, and the corresponding charge / discharge cycle count assessment value is... ; This represents the equivalent internal resistance of the battery. This indicates the initial equivalent internal resistance of the energy storage cabinet at the factory, and the equivalent battery internal resistance. The larger the value, the higher the corresponding equivalent battery internal resistance assessment value. The smaller the value, the more severe the aging is considered when the equivalent internal resistance of the battery exceeds three times the initial equivalent internal resistance. ; , The weighting coefficients are represented by the equivalent battery internal resistance, which more directly characterizes the performance degradation of the batteries within the energy storage cabinet. An increase in the equivalent battery internal resistance leads to decreased charging and discharging efficiency, increased heat loss, and reduced usable capacity. Therefore, the weighting coefficients can be... Set to 0.4, Set it to 0.6.

[0123] Simultaneously, multiple fault types can be classified into Level I, Level II, and Level III faults based on their severity. For example, Level I faults may include serious faults such as individual battery overvoltage / undervoltage, cell overtemperature, or short circuit warnings; Level II faults may include general faults such as BMS communication interruption, abnormal fluctuations in charging / discharging power, or fan failure; and Level III faults may include minor faults such as individual battery voltage / temperature differences approaching thresholds or SOC calibration deviations. Based on this, the fault status assessment value for each energy storage cabinet can be calculated using the following formula:

[0124] ;

[0125] in, This represents the fault status assessment value, where i=1,2,3 correspond to Level I, Level II, and Level III faults, respectively. This represents the fault status assessment value corresponding to the i-th fault level. This represents the weighting coefficient corresponding to the i-th fault level. For example, the weighting coefficient for level I faults can be 0.5, the weighting coefficient for level II faults can be 0.35, and the weighting coefficient for level III faults can be 0.15. The calculation formula is as follows:

[0126] ;

[0127] In the above formula, This represents the number of times the i-th fault level occurs within a set time period (e.g., one week). This represents the maximum number of times the i-th fault level occurs within a set time period (e.g., It can be 1, It can be 3. (can be 10) The larger the value, the higher the corresponding fault condition assessment value. The larger, when At that time, the fault status assessment value To reach the maximum, that is .

[0128] Based on the consistency assessment value, aging status assessment value, and fault status assessment value of each energy storage cabinet, the energy storage status assessment value of each energy storage cabinet is obtained by weighted summing of its health status parameters, consistency assessment value, aging status assessment value, and fault status assessment value. The calculation formula is as follows:

[0129] ;

[0130] In the above formula, This represents the energy storage status assessment value for each energy storage unit. This indicates the health status parameters of each energy storage unit. , , , All are weighted coefficients. Among them, State of Health (SOH) directly determines the available capacity and charge / discharge efficiency of the energy storage cabinet, and is the core performance indicator with the highest weight, which can be set to 0.4. The voltage range and temperature range of individual cells are related to the uniformity of individual cells, and the weight of the consistency assessment value can be set to 0.25. The number of charge / discharge cycles and the equivalent battery internal resistance reflect the battery's lifespan degradation trend and affect long-term operating costs, so the weight of the aging state assessment value can be set to 0.2. Fault parameters are time-sensitive indicators, and the impact of historical faults can be eliminated through operation and maintenance, so the weight of the fault state assessment value can be set to 0.15.

[0131] The State of Energy Storage (SOH) value is a comprehensive quantitative result of the energy storage cabinet's State of Health (SOH), consistency, aging degree, and fault status. The magnitude of the SOH value characterizes the actual power output capacity and operational risk of the energy storage cabinet. A higher SOH value indicates better overall performance, stronger actual power output capacity, and lower operational risk; conversely, a lower SOH value indicates poorer overall performance, weaker actual power output capacity, and higher operational risk. In existing technologies, all energy storage cabinets operate at the same output level. Energy storage cabinets with low SOH values ​​become the "weak link" of the system, not only exhibiting low output efficiency and high risk themselves but also limiting the power output of the entire energy storage system.

[0132] To avoid the above problems, this embodiment multiplies the energy storage status assessment value of each energy storage cabinet by the rated discharge power to obtain the discharge power limit of each energy storage cabinet. For energy storage cabinets with larger energy storage status assessment values, higher discharge power is allowed to be output, which can fully release the performance potential. For energy storage cabinets with smaller energy storage status assessment values, the operating load can be reduced by limiting the discharge power, thus avoiding safety risks such as overheating, overcharging and over-discharging.

[0133] Finally, the discharge power limits of each energy storage cabinet are summed up to obtain the rated discharge power of the energy storage system, which allows the discharge control to accurately match the actual output capacity of the energy storage system.

[0134] In one embodiment of this application, the microgrid control method for photovoltaic-storage parks further includes:

[0135] If the power load is less than the preset third control threshold and the current period is a low electricity price period, control the grid to charge the energy storage system.

[0136] The methods for determining the third control threshold include:

[0137] The upper limit of the load is determined based on the power threshold of the incoming power grid and the preset load redundancy coefficient;

[0138] The third control threshold is determined based on the upper limit of the load and the minimum charging power of the energy storage system.

[0139] In this embodiment, if the power of the electrical load is less than the preset third control threshold, it indicates that the power of the electrical load is small and there is a surplus of grid energy. If it is during a low electricity price period, the surplus grid energy can be sent to the energy storage system for storage to make full use of the low-priced electricity during the low-price period and reduce the charging cost of energy storage. At this time, the grid incoming power is equal to the sum of the power of the park's electrical load and the charging power of energy storage.

[0140] Specifically, when setting the third control threshold, in order to ensure that the grid incoming power does not exceed the grid incoming power threshold when the power of the park's electricity load and the energy storage charging power are superimposed, a load redundancy coefficient (e.g., 0.9) can be set. The grid incoming power threshold and the load redundancy coefficient are multiplied to obtain the upper limit of the load. The third control threshold should be less than the upper limit of the load. Furthermore, in order to avoid the charging power of the energy storage system being too small and below the minimum charging power, resulting in offset charging, this embodiment subtracts the minimum charging power of the energy storage system from the upper limit of the load to obtain the third control threshold.

[0141] It should be noted that when the microgrid controller controls the grid to charge the energy storage system, it needs to consider the current state of charge (SOC) of the energy storage system. The grid will only control the charging of the energy storage system when the current SOC of the energy storage system is less than the upper limit of SOCmax (80%~90% for lithium batteries) to avoid overcharging of the energy storage system.

[0142] As can be seen from the above, this embodiment can avoid the over-limit of the grid incoming power caused by the superposition of the park's power load power and the energy storage charging power through the upper limit constraint of the load. On the other hand, the introduction of the minimum charging power of energy storage avoids the risk of reduced charging efficiency and equipment damage caused by low power charging.

[0143] Based on the same inventive concept, this application also provides a photovoltaic-storage park microgrid control device for implementing the above-mentioned photovoltaic-storage park microgrid control method. The solution provided by this device is similar to the implementation scheme described in the above method. Therefore, the specific limitations of one or more photovoltaic-storage park microgrid control device embodiments provided below can be found in the limitations of the photovoltaic-storage park microgrid control method described above, and will not be repeated here.

[0144] This application provides a microgrid control device for a photovoltaic-storage park, which is installed in a microgrid controller. The microgrid controller is installed in the photovoltaic-storage park microgrid system, which also includes an energy storage system. The energy storage system is communicatively connected to the microgrid controller and is connected in parallel with the power grid. Figure 3 As shown, the microgrid control device 20 of the photovoltaic-storage park includes: a data acquisition module 21 and a charge-discharge control module 22.

[0145] Among them, the data acquisition module 21 is used to acquire the power load and grid incoming power of the photovoltaic and energy storage park;

[0146] The charging and discharging control module 22 is used to determine a first control threshold when the power of the electricity load is greater than a preset power threshold of the grid incoming line and the current time period is a period of flat electricity price, and to control the energy storage system to discharge to the electricity load when the power of the grid incoming line is greater than the first control threshold.

[0147] The method for determining the first control threshold includes:

[0148] The first discharge power is determined based on the rated discharge power of the energy storage system and a preset proportional coefficient.

[0149] The difference between the incoming power threshold of the power grid and the predicted average load power for the current period is calculated, and this difference is used as the second discharge power; wherein, the predicted average load power for the current period is obtained based on historical data of electricity load power;

[0150] The minimum power between the first discharge power and the second discharge power is taken as the third discharge power;

[0151] The difference between the preset power threshold of the incoming power grid and the third discharge power is used as the first control threshold.

[0152] In one embodiment of this application, the charge / discharge control module 22 is specifically used for:

[0153] Obtain power load sequences for multiple historical dates; each historical date's power load sequence includes power load at multiple consecutive time points within that historical date.

[0154] According to the preset time length, the power consumption sequence of each historical date is divided into multiple time windows, and the power consumption sequence within each time window is a subsequence;

[0155] Calculate the average power of the electrical load for each subsequence to obtain the average load power of the subsequence;

[0156] For each time window, the average of the average load power of the subsequences of multiple historical dates within that time window is taken as the historical average load power within that time window;

[0157] Determine the time window to which the current period belongs as the target time window, and use the historical average load power within the target time window as the predicted average load power value for the current period.

[0158] In one embodiment of this application, the charge / discharge control module 22 is specifically used for:

[0159] Calculate the power load fluctuation value for the current period;

[0160] If the power fluctuation value of the current period's electricity load is greater than the preset fluctuation threshold, the preset proportional coefficient will be set as the first coefficient.

[0161] If the power fluctuation value of the current period is less than or equal to the preset fluctuation threshold, the preset proportional coefficient is set as the second coefficient.

[0162] The first coefficient is greater than the second coefficient.

[0163] In one embodiment of this application, the energy storage system includes multiple energy storage cabinets connected in parallel; the charge / discharge control module 22 is specifically used for:

[0164] Obtain the energy storage status parameters corresponding to each of the multiple energy storage cabinets;

[0165] The energy storage status assessment value of each energy storage cabinet is determined based on the energy storage status parameters of each energy storage cabinet.

[0166] The discharge power limit for each energy storage cabinet is determined based on the energy storage status assessment value and the rated discharge power of each energy storage cabinet.

[0167] The rated discharge power of the energy storage system is obtained by summing the discharge power limits of each energy storage cabinet.

[0168] In one embodiment of this application, the energy storage state parameters include health state parameters, individual cell voltage range, individual cell temperature range, charge / discharge cycle count, equivalent battery internal resistance, fault type, and corresponding fault time; the charge / discharge control module 22 is further used for:

[0169] The consistency assessment value for each energy storage cabinet is determined based on the voltage range and temperature range of each individual cell in each energy storage cabinet.

[0170] The aging status assessment value of each energy storage cabinet is determined based on the number of charge-discharge cycles and the equivalent battery internal resistance of each cabinet.

[0171] The fault status assessment value of each energy storage cabinet is determined based on the fault type and corresponding fault time of each energy storage cabinet.

[0172] The energy storage status assessment value of each energy storage cabinet is obtained by weighted summing of the health status parameters, consistency assessment value, aging status assessment value and fault status assessment value.

[0173] In one embodiment of this application, the charge / discharge control module 22 is specifically used for:

[0174] If the power of the electricity load is greater than the preset power threshold of the grid incoming line, and the current period is a low electricity price period, a second control threshold is determined, and when the power of the grid incoming line is greater than the second control threshold, the energy storage system is controlled to discharge to the electricity load.

[0175] The determination method for the second control threshold includes:

[0176] Obtain the minimum discharge power of the energy storage system;

[0177] The correction amount is determined based on the historical power load fluctuation value corresponding to the current time period;

[0178] The fourth discharge power is determined based on the minimum discharge power and correction amount of the energy storage system;

[0179] The second control threshold is determined based on the grid incoming power threshold and the fourth discharge power.

[0180] In one embodiment of this application, the charge / discharge control module 22 is specifically used for:

[0181] If the power load is less than the preset third control threshold and the current period is a low electricity price period, control the grid to charge the energy storage system.

[0182] The methods for determining the third control threshold include:

[0183] The upper limit of the load is determined based on the power threshold of the incoming power grid and the preset load redundancy coefficient;

[0184] The third control threshold is determined based on the upper limit of the load and the minimum charging power of the energy storage system.

[0185] See Figure 4 , Figure 4 This is a schematic block diagram of an electronic device provided in one embodiment of this application. The electronic device can be a microgrid controller in a photovoltaic-storage park microgrid system. Figure 4The electronic device 300 in this embodiment may include one or more processors 301, one or more input devices 302, one or more output devices 303, and one or more memories 304. The processors 301, input devices 302, output devices 303, and memories 304 communicate with each other via a communication bus 305. The memories 304 store computer programs, including program instructions. The processors 301 execute the program instructions stored in the memories 304. Specifically, the processors 301 are configured to invoke the program instructions to perform the functions of each module / unit in the above-described device embodiments, for example... Figure 3 The functions of the data acquisition module 21 and the charge / discharge control module 22 are shown.

[0186] It should be understood that, in the embodiments of this application, the processor 301 may be a central processing unit (CPU), but it may also be other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. The general-purpose processor may be a microprocessor or any conventional processor.

[0187] Input device 302 may include a touchpad, a fingerprint sensor (for collecting the user's fingerprint information and fingerprint orientation information), a microphone, etc., and output device 303 may include a display (LCD, etc.), a speaker, etc.

[0188] The memory 304 may include read-only memory and random access memory, and provides instructions and data to the processor 301. A portion of the memory 304 may also include non-volatile random access memory. For example, the memory 304 may also store preset information such as the grid incoming power threshold, time duration, and load redundancy factor.

[0189] In specific implementations, the processor 301, input device 302, and output device 303 described in the embodiments of this application can execute the implementation method described in the photovoltaic-storage park microgrid control method provided in the embodiments of this application, or they can execute the implementation method of the electronic device described in the embodiments of this application, which will not be repeated here.

[0190] In another embodiment of this application, a computer-readable storage medium is provided. This computer-readable storage medium stores a computer program, which includes program instructions. When executed by a processor, the program instructions implement all or part of the processes in the methods described above. Alternatively, the computer program can instruct related hardware to complete the process. The computer program can be stored in a computer-readable storage medium, and when executed by a processor, it can implement the steps of the various method embodiments described above. The computer program includes computer program code, which can be in the form of source code, object code, executable files, or certain intermediate forms. The computer-readable medium can include any entity or device capable of carrying computer program code, a recording medium, a USB flash drive, a portable hard drive, a magnetic disk, an optical disk, a computer memory, a read-only memory (ROM), a random access memory (RAM), an electrical carrier signal, a telecommunication signal, and a software distribution medium, etc.

[0191] The computer-readable storage medium can be an internal storage unit of the electronic device in any of the foregoing embodiments, such as a hard disk or memory of the electronic device. The computer-readable storage medium can also be an external storage device of the electronic device, such as a plug-in hard disk, smart media card (SMC), secure digital card (SD), flash card, etc., provided on the electronic device. Furthermore, the computer-readable storage medium can include both internal and external storage units of the electronic device. The computer-readable storage medium is used to store computer programs and other programs and data required by the electronic device. The computer-readable storage medium can also be used to temporarily store data that has been output or will be output.

[0192] Those skilled in the art will recognize that the modules / units and algorithm steps of the various examples described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, computer software, or a combination of both. To clearly illustrate the interchangeability of hardware and software, the components and steps of the various examples have been generally described in terms of functionality in the foregoing description. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementations should not be considered beyond the scope of this application.

[0193] Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the specific working process of the electronic devices and units described above can be referred to the corresponding process in the foregoing method embodiments, and will not be repeated here.

[0194] In the several embodiments provided in this application, it should be understood that the disclosed electronic devices and methods can be implemented in other ways. For example, the device embodiments described above are merely illustrative. For instance, the division of modules / units is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple modules, units, or components may be combined or integrated into another system, or some features may be ignored or not executed. In addition, the mutual coupling or direct coupling or communication connection shown or discussed may be indirect coupling or communication connection through some interfaces or modules / units, or it may be an electrical, mechanical, or other form of connection.

[0195] The modules / units described as separate components may or may not be physically separate. Similarly, the components shown as modules / units may or may not be physical modules / units; they may be located in one place or distributed across multiple network modules / units. Some or all of the modules / units can be selected to achieve the purpose of the embodiments of this application, depending on actual needs.

[0196] Furthermore, the functional modules / units in the various embodiments of this application can be integrated into one processing module / unit, or each module / unit can exist physically separately, or two or more modules / units can be integrated into one module / unit. The integrated modules / units described above can be implemented in hardware or in the form of software functional modules / units.

[0197] The above are merely specific embodiments of this application, but the scope of protection of this application is not limited thereto. Any person skilled in the art can easily conceive of various equivalent modifications or substitutions within the technical scope disclosed in this application, and these modifications or substitutions should all be covered within the scope of protection of this application. Therefore, the scope of protection of this application should be determined by the scope of the claims.

Claims

1. A microgrid control method for a photovoltaic-storage park, applied to a photovoltaic-storage park microgrid system, wherein the photovoltaic-storage park microgrid system includes an energy storage system and a microgrid controller, the energy storage system is communicatively connected to the microgrid controller, and the energy storage system is connected in parallel with the power grid, characterized in that: The method is executed by the microgrid controller, and the method includes: Obtain the power load and grid incoming power of the photovoltaic and energy storage park; If the power of the electricity load is greater than the preset power threshold of the grid incoming line, and the current time period is a period of flat electricity price, a first control threshold is determined, and when the power of the grid incoming line is greater than the first control threshold, the energy storage system is controlled to discharge to the electricity load. The method for determining the first control threshold includes: The first discharge power is determined based on the rated discharge power of the energy storage system and a preset proportional coefficient. The difference between the power grid incoming power threshold and the predicted average load power for the current period is calculated, and this difference is used as the second discharge power; wherein, the predicted average load power for the current period is obtained based on historical data of the power load. The minimum power between the first discharge power and the second discharge power is taken as the third discharge power; The difference between the preset power grid incoming power threshold and the third discharge power is used as the first control threshold. The method for determining the average load power forecast value for the current time period includes: Obtain power load sequences for multiple historical dates; each historical date's power load sequence includes power load at multiple consecutive time points within that historical date. According to the preset time length, the power consumption sequence of each historical date is divided into multiple time windows, and the power consumption sequence within each time window is a subsequence; Calculate the average power of the electrical load for each subsequence to obtain the average load power of the subsequence; For each time window, the average of the average load power of the subsequences of multiple historical dates within that time window is taken as the historical average load power within that time window; Determine the time window to which the current period belongs as the target time window, and use the historical average load power within the target time window as the predicted average load power value for the current period.

2. The microgrid control method for photovoltaic-storage parks as described in claim 1, characterized in that, The method for determining the preset proportional coefficient includes: Calculate the power load fluctuation value for the current period; If the power fluctuation value of the current period's electricity load is greater than the preset fluctuation threshold, the preset proportional coefficient is set as the first coefficient; If the power fluctuation value of the current period is less than or equal to the preset fluctuation threshold, the preset proportional coefficient is set as the second coefficient; Wherein, the first coefficient is greater than the second coefficient.

3. The microgrid control method for photovoltaic-storage parks as described in claim 1, characterized in that, The energy storage system includes multiple energy storage cabinets connected in parallel. The method for determining the rated discharge power of the energy storage system includes: Obtain the energy storage status parameters corresponding to each of the multiple energy storage cabinets; The energy storage status assessment value of each energy storage cabinet is determined based on the energy storage status parameters of each energy storage cabinet. The discharge power limit for each energy storage cabinet is determined based on the energy storage status assessment value and the rated discharge power of each energy storage cabinet. The rated discharge power of the energy storage system is obtained by summing the discharge power limits of each energy storage cabinet.

4. The microgrid control method for photovoltaic-storage parks as described in claim 3, characterized in that, The energy storage status parameters include health status parameters, individual cell voltage range, individual cell temperature range, charge / discharge cycle count, equivalent battery internal resistance, fault type, and corresponding fault time. The process of determining the energy storage status assessment value for each energy storage cabinet based on its energy storage status parameters includes: The consistency assessment value for each energy storage cabinet is determined based on the voltage range and temperature range of each individual cell in each energy storage cabinet. The aging status assessment value of each energy storage cabinet is determined based on the number of charge-discharge cycles and the equivalent battery internal resistance of each cabinet. The fault status assessment value of each energy storage cabinet is determined based on the fault type and corresponding fault time of each energy storage cabinet. The energy storage status assessment value of each energy storage cabinet is obtained by weighted summing of the health status parameters, consistency assessment value, aging status assessment value and fault status assessment value.

5. The microgrid control method for photovoltaic-storage parks as described in claim 1, characterized in that, Also includes: If the power of the electrical load is greater than the preset power threshold of the grid incoming line, and the current period is a low electricity price period, a second control threshold is determined, and when the power of the grid incoming line is greater than the second control threshold, the energy storage system is controlled to discharge to the electrical load. The method for determining the second control threshold includes: Obtain the minimum discharge power of the energy storage system; The correction amount is determined based on the historical power load fluctuation value corresponding to the current time period; The fourth discharge power is determined based on the minimum discharge power of the energy storage system and the correction amount. The second control threshold is determined based on the power grid incoming power threshold and the fourth discharge power.

6. The microgrid control method for photovoltaic-storage parks as described in claim 1, characterized in that, Also includes: If the power load is less than the preset third control threshold, and the current period is a low electricity price period, the power grid is controlled to charge the energy storage system. The method for determining the third control threshold includes: The upper limit of the load is determined based on the power threshold of the power grid incoming line and the preset load redundancy coefficient; The third control threshold is determined based on the load limit and the minimum charging power of the energy storage system.

7. A microgrid control device for a photovoltaic-storage park, disposed in a microgrid controller, the microgrid controller being disposed in the photovoltaic-storage park microgrid system, the photovoltaic-storage park microgrid system further comprising an energy storage system, the energy storage system being communicatively connected to the microgrid controller, and the energy storage system being connected in parallel with the power grid, characterized in that: The device includes: The data acquisition module is used to acquire the power load and incoming power of the photovoltaic-storage park. The charging and discharging control module is used to determine a first control threshold when the power of the electrical load is greater than a preset power threshold of the grid and the current time period is a period of flat electricity price, and to control the energy storage system to discharge to the electrical load when the power of the grid is greater than the first control threshold. The method for determining the first control threshold includes: The first discharge power is determined based on the rated discharge power of the energy storage system and a preset proportional coefficient. The difference between the power grid incoming power threshold and the predicted average load power for the current period is calculated, and this difference is used as the second discharge power; wherein, the predicted average load power for the current period is obtained based on historical data of the electricity load power; The minimum power between the first discharge power and the second discharge power is taken as the third discharge power; The difference between the preset power grid incoming power threshold and the third discharge power is used as the first control threshold. The charge / discharge control module is specifically used for: Obtain power load sequences for multiple historical dates; each historical date's power load sequence includes power load at multiple consecutive time points within that historical date. According to the preset time length, the power consumption sequence of each historical date is divided into multiple time windows, and the power consumption sequence within each time window is a subsequence; Calculate the average power of the electrical load for each subsequence to obtain the average load power of the subsequence; For each time window, the average of the average load power of the subsequences of multiple historical dates within that time window is taken as the historical average load power within that time window; Determine the time window to which the current period belongs as the target time window, and use the historical average load power within the target time window as the predicted average load power value for the current period.

8. An electronic device comprising a memory, a processor, and a computer program stored in the memory and running on the processor, characterized in that, When the processor executes the computer program, it implements the steps of the method as described in any one of claims 1 to 6.

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

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