A microgrid dispatching method, dispatching system, storage medium, and program product

Abstract

This invention relates to a microgrid dispatching method, dispatching system, storage medium, and program product, pertaining to the field of microgrid operation and control. Implementing this method, the dispatching system collects real-time data on distributed photovoltaic power generation and local load power within the microgrid, dynamically calculates the fluctuation rate of the power difference between the two, and adaptively adjusts the power dead zone threshold accordingly, effectively avoiding frequent responses from energy storage batteries to small power fluctuations. Simultaneously, the dispatching system establishes a battery aging cost function model considering multiple factors such as the energy storage battery's state of charge, health status, and temperature. It calculates the battery aging cost value generated by the energy storage battery executing effective demand power commands and compares it with the grid interaction cost value of the microgrid purchasing power from the grid, thereby achieving economic optimization of energy storage battery dispatching. This method ensures the stability of the microgrid power balance while maximizing the lifespan of the energy storage batteries, improving the economic efficiency of microgrid operation.

Description

Technical Field

[0001] This application relates to the field of microgrid operation and control, and in particular to a microgrid dispatching method, dispatching system, storage medium and program product. Background Technology

[0002] Microgrids, by integrating distributed power sources (such as photovoltaic power generation), energy storage devices, and local loads, can achieve autonomous supply and demand balance, effectively improving the economy and reliability of grid operation. Energy storage devices play a crucial role in microgrids, smoothing out intermittent fluctuations in photovoltaic power generation, maintaining power balance, and ensuring power supply stability.

[0003] In related technologies, microgrid dispatching methods typically employ rule-based energy management strategies to control the charging and discharging behavior of energy storage devices. Specifically, the dispatching system monitors photovoltaic power generation and local load power in real time, calculating the difference to determine net power demand. To prevent energy storage devices from frequently activating in response to small power fluctuations, a fixed power threshold or dead zone is usually preset in the control logic. When the net power demand exceeds the power threshold or dead zone, the dispatching system determines that energy storage intervention is necessary.

[0004] However, the aforementioned microgrid dispatching methods have certain limitations in practical applications. Due to the strong randomness and time-varying nature of photovoltaic power generation and load electricity consumption, their fluctuation characteristics vary greatly at different times. Even with the use of fixed power thresholds or dead zones, energy storage devices will frequently respond to power fluctuations, leading to battery performance degradation and reduced lifespan. Summary of the Invention

[0005] This application provides a microgrid dispatching method, dispatching system, storage medium, and program product, which are used to maximize the service life of energy storage batteries while ensuring the power balance stability of the microgrid.

[0006] Firstly, this application provides a microgrid dispatching method applied to a dispatching system. The method includes: collecting real-time operating data of the microgrid, including at least distributed photovoltaic power generation, local load power, energy storage battery charge index, energy storage battery health index, and energy storage battery temperature; determining the difference between distributed photovoltaic power generation and local load power as a power difference; calculating the fluctuation rate of the power difference based on a sliding time window; and adjusting a power dead zone threshold according to the fluctuation rate, whereby the power dead zone threshold represents the microgrid's response sensitivity to power fluctuations; filtering the power difference based on the power dead zone threshold; and outputting an effective demand power command. The power demand command includes the power value that the energy storage battery needs to respond to. A positive power value indicates that the energy storage battery needs to be charged to absorb excess power, while a negative power value indicates that the energy storage battery needs to be discharged to make up for the power gap. The power value in the effective demand power command, the energy storage battery charge index, the energy storage battery health index, and the energy storage battery temperature are input into the battery aging cost function model to calculate the battery aging cost value generated by executing the effective demand power command. If the effective demand power command indicates that the energy storage battery needs to be discharged, the battery aging cost value is compared with the grid interaction cost value calculated based on the real-time electricity purchase price to generate the final power dispatch command to control the energy storage battery to perform the discharge action.

[0007] By adopting the above technical solution, the dispatch system collects the distributed photovoltaic power generation and local load power of the microgrid in real time, dynamically calculates the fluctuation rate of the power difference between the two, and adaptively adjusts the power dead zone threshold accordingly, effectively avoiding frequent responses of energy storage batteries to small power fluctuations. Simultaneously, the dispatch system also establishes a battery aging cost function model considering multiple factors such as the state of charge, health status, and temperature of the energy storage batteries. It calculates the battery aging cost value generated by the energy storage batteries executing effective demand power commands and compares it with the grid interaction cost value of the microgrid purchasing electricity from the grid, thereby achieving economic optimization of energy storage battery dispatch. This adaptive dispatch strategy based on multi-dimensional evaluation not only ensures the stability of the microgrid power balance but also maximizes the lifespan of the energy storage batteries, improving the economic efficiency of microgrid operation.

[0008] In conjunction with some embodiments of the first aspect, in some embodiments, before the step of collecting real-time operating data of the microgrid, which includes at least distributed photovoltaic power generation, local load power, energy storage battery charge index, energy storage battery health index, and energy storage battery temperature, the method further includes: setting an initial default power dead zone and a maximum dead zone power limit, wherein the maximum dead zone power limit is equal to the maximum instantaneous power exchange deviation value allowed at the microgrid grid connection point; and initializing the power dead zone threshold to the initial default power dead zone.

[0009] By adopting the above technical solution, the dispatching system pre-sets the initial default power dead zone and the maximum dead zone power limit, and initializes the power dead zone threshold to the initial default power dead zone, providing a reasonable reference benchmark and constraint boundary for subsequent dynamic adjustment of the power dead zone threshold. The maximum dead zone power limit is equal to the maximum allowable instantaneous power exchange deviation value at the microgrid grid connection point, ensuring that the adjustment of the power dead zone threshold will not exceed the range of safe system operation and guaranteeing the security of interaction between the microgrid and the main grid.

[0010] In conjunction with some embodiments of the first aspect, in some embodiments, the fluctuation rate of the power difference is calculated based on a sliding time window, and the power dead zone threshold is adjusted according to the fluctuation rate. The power dead zone threshold represents the microgrid's response sensitivity to power fluctuations. Specifically, this includes: calculating the fluctuation variance of the power difference within the sliding time window to obtain the fluctuation rate; if the fluctuation rate exceeds a preset high-frequency jitter threshold and the absolute value of the power difference is less than the maximum instantaneous power exchange deviation, then the current power dead zone threshold is increased by a preset first step size until the maximum dead zone power limit is reached; if the fluctuation rate does not exceed the preset high-frequency jitter threshold, then the current power dead zone threshold is decreased by a preset second step size until it is restored to the initial default power dead zone; after adjusting the current power dead zone threshold, an updated power dead zone threshold is obtained.

[0011] By adopting the above technical solution, the dispatching system calculates the fluctuation variance of the power difference through a sliding time window, achieving real-time assessment of power fluctuation characteristics. When the fluctuation rate exceeds a preset high-frequency jitter threshold and the absolute value of the power difference is less than the maximum instantaneous power exchange deviation, the dispatching system automatically increases the power dead zone threshold to suppress frequent responses; when the fluctuation rate does not exceed the preset high-frequency jitter threshold, the dispatching system gradually decreases the power dead zone threshold to improve response sensitivity. This bidirectional dynamic adjustment mechanism based on power fluctuation characteristics can effectively suppress frequent responses of energy storage batteries to small instantaneous fluctuations while maintaining the timely response capability of energy storage batteries to large power fluctuations, thus improving the adaptability and reliability of energy storage dispatching.

[0012] In conjunction with some embodiments of the first aspect, in some embodiments, based on a power dead zone threshold, the power difference is filtered to output a valid demand power command. The valid demand power command includes the power value that the energy storage battery needs to respond to. A positive power value indicates that the energy storage battery needs to be charged to absorb excess power, and a negative power value indicates that the energy storage battery needs to be discharged to make up for the power gap. Specifically, if the absolute value of the power difference is less than the power dead zone threshold, the power difference is set to zero; if the absolute value of the power difference is greater than or equal to the power dead zone threshold, a valid demand power command is generated based on the power difference.

[0013] By adopting the above technical solution, for power differences whose absolute value is less than the power dead zone threshold, the scheduling system sets them to zero, avoiding unnecessary responses from energy storage batteries to minor power fluctuations. For power differences whose absolute value is greater than or equal to the power dead zone threshold, the scheduling system generates corresponding valid demand power commands. This hierarchical processing mechanism ensures timely response to significant power fluctuations while avoiding frequent switching of operating states by energy storage batteries. This method, by setting a reasonable power difference filtering strategy, effectively reduces the frequency of energy storage battery usage, decreases the number of charge-discharge cycles, extends equipment lifespan, and ensures stable operation of the microgrid, thereby improving overall operating efficiency and economy.

[0014] In conjunction with some embodiments of the first aspect, in some embodiments, the power value in the effective demand power command, the energy storage battery charge index, the energy storage battery health index, and the energy storage battery temperature are input into the battery aging cost function model to calculate the battery aging cost value generated by executing the effective demand power command. Specifically, this includes: obtaining a preset basic depreciation cost per unit throughput of the battery; determining a charge index penalty factor based on the energy storage battery charge index, where the greater the deviation of the energy storage battery charge index from the preset intermediate operating range, the larger the charge index penalty factor; determining a health index correction factor based on the energy storage battery health index, where the lower the energy storage battery health index, the larger the health index correction factor; determining a temperature influence factor based on the energy storage battery temperature, where the greater the deviation of the energy storage battery temperature from the optimal operating temperature range, the larger the temperature influence factor; and calculating the battery aging cost value based on the basic depreciation cost per unit throughput of the battery, the charge index penalty factor, the health index correction factor, the temperature influence factor, and the power value in the effective demand power command.

[0015] By adopting the above technical solutions, the scheduling system considers the basic depreciation cost per unit throughput of batteries and introduces multiple influencing factors such as charge index penalty factor, health index correction factor, and temperature influence factor, thus achieving precise quantification of the cost of energy storage battery usage. The battery aging cost function model accurately reflects the actual wear and tear of energy storage batteries under different operating conditions through multi-dimensional evaluation of battery operating status. This multi-factor-based cost assessment mechanism provides a reliable economic basis for energy storage scheduling decisions, effectively balancing the relationship between system response requirements and equipment lifespan protection, and improving the utilization efficiency of the energy storage system.

[0016] In conjunction with some embodiments of the first aspect, in some embodiments, if the effective demand power command indicates that the energy storage battery needs to discharge, the battery aging cost value is compared with the grid interaction cost value calculated based on the real-time electricity purchase price, and a final power dispatch command is generated to control the energy storage battery to perform the discharge action. Specifically, this includes: if the effective demand power command indicates that the energy storage battery needs to discharge, obtaining the real-time electricity purchase price of the microgrid from the grid, calculating the product of the absolute value of the power value in the effective demand power command and the real-time electricity purchase price to obtain the grid interaction cost value; determining whether the battery aging cost value is greater than the grid interaction cost value; if so, prohibiting the energy storage battery from responding; if not, determining the effective demand power command as the final power dispatch command.

[0017] By adopting the above technical solution, the dispatch system compares the battery aging cost with the grid interaction cost of the microgrid purchasing electricity from the grid in real time to determine whether to execute an energy storage discharge operation. When the battery aging cost is greater than the grid interaction cost, the dispatch system chooses to purchase electricity directly from the grid instead of consuming the energy storage battery's lifespan; otherwise, it executes the energy storage discharge command. This economically based decision-making mechanism achieves optimal allocation of energy storage resources, avoids uneconomical energy storage dispatching behavior, and effectively controls the usage cost of energy storage batteries.

[0018] In conjunction with some embodiments of the first aspect, in some embodiments, after inputting the power value, energy storage battery charge index, energy storage battery health index, and energy storage battery temperature from the effective demand power command into the battery aging cost function model to calculate the battery aging cost value generated by executing the effective demand power command, the method further includes: if the effective demand power command indicates that the energy storage battery needs to be charged, then obtaining the real-time grid-connected electricity price of the microgrid selling electricity to the grid, calculating the product of the power value in the effective demand power command and the real-time grid-connected electricity price to obtain the potential value of electricity sales revenue; determining whether the battery aging cost value is greater than the potential value of electricity sales revenue; if so, prohibiting the energy storage battery from responding; if not, determining the effective demand power command as the final power dispatch command.

[0019] By adopting the above technical solution, the dispatch system compares the battery aging cost with the potential revenue from selling electricity from the microgrid to the grid in real time to determine whether to execute an energy storage charging operation. When the battery aging cost is greater than the potential revenue, the dispatch system abandons charging to avoid unnecessary energy storage battery depletion; otherwise, it executes the energy storage charging command. This charging decision-making mechanism based on revenue assessment ensures the economic rationality of energy storage charging operations, avoids economic losses caused by improper charging, maximizes the value of energy storage resources, and improves the economic efficiency of the microgrid.

[0020] In a second aspect, embodiments of this application provide a scheduling system comprising: one or more processors and a memory; the memory is coupled to the one or more processors and is used to store computer program code, the computer program code including computer instructions, wherein the one or more processors invoke the computer instructions to cause the scheduling system to perform the method described in the first aspect and any possible implementation thereof.

[0021] Thirdly, embodiments of this application provide a computer program product containing instructions that, when the computer program product is run on a scheduling system, cause the scheduling system to execute the method described in the first aspect and any possible implementation thereof.

[0022] Fourthly, embodiments of this application provide a computer-readable storage medium including instructions that, when executed on a scheduling system, cause the scheduling system to perform the method described in the first aspect and any possible implementation thereof.

[0023] Understandably, the scheduling system provided in the second aspect, the computer program product provided in the third aspect, and the computer storage medium provided in the fourth aspect are all used to execute the methods provided in the embodiments of this application. Therefore, the beneficial effects they can achieve can be referred to the beneficial effects in the corresponding methods, and will not be repeated here.

[0024] One or more technical solutions provided in the embodiments of this application have at least the following technical effects or advantages: 1. By adopting the above technical solution, the dispatch system collects the distributed photovoltaic power generation and local load power of the microgrid in real time, dynamically calculates the fluctuation rate of the power difference between the two, and adaptively adjusts the power dead zone threshold accordingly, effectively avoiding frequent responses of energy storage batteries to small power fluctuations. Simultaneously, the dispatch system also establishes a battery aging cost function model considering multiple factors such as the state of charge, health status, and temperature of the energy storage batteries. It calculates the battery aging cost value generated by the energy storage batteries executing effective demand power commands and compares it with the grid interaction cost value of the microgrid purchasing electricity from the grid, thereby achieving economic optimization of energy storage battery dispatch. This adaptive dispatch strategy based on multi-dimensional evaluation not only ensures the stability of the microgrid power balance but also maximizes the lifespan of the energy storage batteries, improving the economic efficiency of microgrid operation.

[0025] 2. By adopting the above technical solution, the dispatching system calculates the fluctuation variance of the power difference through a sliding time window, achieving real-time assessment of power fluctuation characteristics. When the fluctuation rate exceeds the preset high-frequency jitter threshold and the absolute value of the power difference is less than the maximum instantaneous power exchange deviation, the dispatching system automatically increases the power dead zone threshold to suppress frequent responses; when the fluctuation rate does not exceed the preset high-frequency jitter threshold, the dispatching system gradually decreases the power dead zone threshold to improve response sensitivity. This bidirectional dynamic adjustment mechanism based on power fluctuation characteristics can effectively suppress the frequent responses of energy storage batteries to small instantaneous fluctuations while maintaining the timely response capability of energy storage batteries to large power fluctuations, thus improving the adaptability and reliability of energy storage dispatching.

[0026] 3. By adopting the above technical solution, for power differences whose absolute value is less than the power dead zone threshold, the scheduling system sets them to zero, avoiding unnecessary responses from the energy storage battery to small power fluctuations. For power differences whose absolute value is greater than or equal to the power dead zone threshold, the scheduling system generates corresponding valid demand power commands. This hierarchical processing mechanism ensures timely response to significant power fluctuations while avoiding frequent switching of the energy storage battery's operating state. This method, by setting a reasonable power difference filtering strategy, effectively reduces the frequency of energy storage battery usage, reduces the number of charge-discharge cycles, extends equipment lifespan, and ensures stable operation of the microgrid, thereby improving overall operating efficiency and economy. Attached Figure Description

[0027] Figure 1 This is a flowchart illustrating a microgrid scheduling method in an embodiment of this application; Figure 2 This is another flowchart illustrating the microgrid scheduling method in this application embodiment; Figure 3 This is a schematic diagram of the physical device structure of the scheduling system in the embodiments of this application. Detailed Implementation

[0028] The terminology used in the following embodiments of this application is for the purpose of describing particular embodiments only and is not intended to be limiting of this application. As used in the specification of this application, the singular expressions “a,” “an,” “the,” “the,” and “this” are intended to include the plural expressions as well, unless the context clearly indicates otherwise. It should also be understood that the term “and / or” as used in this application refers to any or all possible combinations including one or more of the listed items.

[0029] Hereinafter, the terms "first" and "second" are used for descriptive purposes only and should not be construed as implying or suggesting relative importance or implicitly indicating the number of indicated technical features. Thus, a feature defined as "first" or "second" may explicitly or implicitly include one or more of that feature, and in the description of the embodiments of this application, unless otherwise stated, "multiple" means two or more.

[0030] The following describes the process of the method provided in this implementation. Please refer to [link / reference]. Figure 1 This is a flowchart illustrating a microgrid scheduling method in an embodiment of this application.

[0031] S101. Collect real-time operating data of the microgrid. The real-time operating data shall include at least the distributed photovoltaic power generation, local load power, energy storage battery charge index, energy storage battery health index, and energy storage battery temperature. Microgrids refer to small-scale power generation and distribution systems composed of distributed power sources, energy storage devices, and local loads. Distributed photovoltaic (PV) power generation refers to the actual output power of a PV system (a type of distributed power source) at a given moment, measured in kilowatts (kW). Local load power represents the actual power consumption of a local load at a given moment, also measured in kilowatts (kW). The charge index of an energy storage battery is the percentage of its remaining charge relative to its rated charge. The health index of an energy storage battery indicates the degree of capacity degradation; it is the percentage of the battery's maximum capacity relative to its initial capacity at the current moment. The temperature of an energy storage battery refers to its actual operating temperature, measured in degrees Celsius (°C).

[0032] Specifically, the dispatch system collects data on the microgrid's operation in real time through various sensors and measuring devices: for distributed photovoltaic power generation, the AC output power of the photovoltaic inverter can be measured through power metering devices; for local load power, the total power of each electrical device can be measured through smart meters; for energy storage battery parameters, the energy storage battery charge index, energy storage battery health index, and energy storage battery temperature are collected through the energy storage battery management system. The sampling period for all data is typically at the millisecond level to ensure the real-time performance and accuracy of the data.

[0033] S102. The difference between the distributed photovoltaic power generation power and the local load power is determined as the power difference. The fluctuation rate of the power difference is calculated based on the sliding time window, and the power dead zone threshold is adjusted according to the fluctuation rate. The power dead zone threshold represents the microgrid's response sensitivity to power fluctuations. The power difference represents the instantaneous difference between the distributed photovoltaic power generation and the local load power; a positive value indicates overgeneration, and a negative value indicates underpowerment. The sliding time window is a fixed-length period (e.g., 5 minutes) that is continuously updated over time. The fluctuation rate refers to the degree of fluctuation in the power difference within the sliding time window, which can be quantified by calculating statistical indicators such as variance. The power dead zone threshold represents the minimum power fluctuation value that triggers an energy storage response, used to filter out minor fluctuations.

[0034] Specifically, first, the dispatch system calculates the algebraic difference between the distributed photovoltaic power generation and the local load power to obtain the power difference value. Then, based on a preset sliding time window (e.g., 10 seconds), the dispatch system calculates the statistical variance of the power difference sequence within the sliding window as the fluctuation rate. According to the magnitude of the fluctuation rate, the dispatch system dynamically adjusts the power dead zone threshold: increasing the power dead zone threshold to reduce response sensitivity when fluctuations are severe, and decreasing the power dead zone threshold to improve response timeliness when fluctuations are mild. This adaptive adjustment mechanism can effectively balance system responsiveness and stability.

[0035] Optionally, under normal circumstances, the fluctuation rate of the power difference is calculated based on the sliding time window, and the power dead zone threshold is adjusted according to the fluctuation rate. The power dead zone threshold represents the microgrid's response sensitivity to power fluctuations and can be achieved in the following ways, without limitation: Calculate the fluctuation variance of the power difference within the sliding time window to obtain the fluctuation rate; if the fluctuation rate exceeds the preset high-frequency jitter threshold and the absolute value of the power difference is less than the maximum instantaneous power exchange deviation, then increase the current power dead zone threshold by a preset first step size until the maximum dead zone power limit is reached; if the fluctuation rate does not exceed the preset high-frequency jitter threshold, then decrease the current power dead zone threshold by a preset second step size until it is restored to the initial default power dead zone; after adjusting the current power dead zone threshold, the updated power dead zone threshold is obtained.

[0036] The variance of fluctuation refers to the average of the squares of the deviations of the power difference from the average value, used to quantify the dispersion of data fluctuations. The preset high-frequency jitter threshold is a standard for judging whether power fluctuations are too frequent; if the variance of fluctuation is greater than the preset high-frequency jitter threshold, it indicates that power fluctuations are too frequent. The preset first step length represents the adjustment amount when increasing the power dead zone, such as 0.5kW. The preset second step length represents the adjustment amount when decreasing the power dead zone, such as 0.2kW. The power dead zone threshold represents the microgrid's tolerance to power fluctuations and determines whether to trigger an energy storage response.

[0037] Specifically, the scheduling system maintains a sliding time window (e.g., 5 minutes) and continuously records power differences. During each call, the scheduling system calculates the mean of all power differences within the sliding time window, then calculates the square of the difference between each power difference and the mean, and takes the average of these squared values ​​as the variance, i.e., the rate of change of fluctuation. For example, assuming 300 power difference samples are collected within a 5-minute sliding time window, the calculation steps are: calculate the average of the 300 power difference samples, assuming it is 2kW; calculate the difference between each power difference sample and the average of 2kW; square each difference; sum all the squared values; and finally divide by 300 to obtain the final variance.

[0038] The scheduling system compares the calculated fluctuation rate (150kW²) with a preset high-frequency jitter threshold (e.g., 100kW²): If the fluctuation rate exceeds the preset high-frequency jitter threshold, it indicates that the power fluctuation is relatively severe. The dispatch system simultaneously checks whether the absolute value of the current power difference is less than the maximum instantaneous power exchange deviation (e.g., 15% of the microgrid's rated capacity of 100kW, i.e., 15kW). If all the above conditions are met, the current power dead zone threshold is increased by a preset first step length (0.5kW), such as from 2kW to 2.5kW. If the new power dead zone threshold does not exceed the maximum dead zone power limit (e.g., 12kW), the new power dead zone threshold is adopted; otherwise, it remains at the maximum dead zone power limit.

[0039] If the rate of change of fluctuation does not exceed the preset high-frequency jitter threshold, it indicates that the power fluctuation is stabilizing. At this time, the scheduling system will reduce the power dead zone threshold by a preset second step (0.2kW), such as from 2.5kW to 2.3kW. This adjustment will continue until it returns to the initial default power dead zone (such as 2kW).

[0040] This dynamic adjustment mechanism can reduce the response frequency by increasing the dead zone when power fluctuates drastically, and improve the response sensitivity by decreasing the dead zone when power is stable, thus achieving adaptive optimization of energy storage scheduling.

[0041] S103. Based on the power dead zone threshold, filter the power difference and output the effective demand power command. The effective demand power command includes the power value that the energy storage battery needs to respond to. A positive power value indicates that the energy storage battery needs to be charged to absorb excess power, and a negative power value indicates that the energy storage battery needs to be discharged to make up for the power gap. Filtering refers to the process of selecting power differences based on a power dead zone threshold. Effective demand power command refers to the power adjustment command that the energy storage battery needs to actually respond to after filtering. The power value indicates the specific power required for the energy storage battery to charge or discharge, and its sign indicates the direction of charging or discharging. Charging means storing electrical energy into the energy storage battery, and discharging means releasing electrical energy from the energy storage battery.

[0042] Specifically, the dispatch system compares the absolute value of the real-time power difference with the current power dead zone threshold: when the absolute value of the real-time power difference is less than the current power dead zone threshold, it indicates that the power fluctuation is small, and the power difference is set to zero, without triggering an energy storage response; when the absolute value of the real-time power difference is greater than or equal to the current power dead zone threshold, it indicates that the power fluctuation is significant, requiring energy storage intervention for regulation. In this case, the power difference is issued to the energy storage battery as an effective demand power command. A positive power value indicates excess power generation, requiring energy storage charging to absorb it; a negative power value indicates insufficient power supply, requiring energy storage discharging to supplement it. This tiered processing mechanism can avoid frequent responses from energy storage batteries to small power fluctuations.

[0043] Optionally, under normal circumstances, based on the power dead zone threshold, the power difference is filtered to output a valid demand power command. The valid demand power command includes the power value that the energy storage battery needs to respond to. A positive power value indicates that the energy storage battery needs to be charged to absorb excess power, and a negative power value indicates that the energy storage battery needs to be discharged to make up for the power gap. This can be achieved in the following ways, without limitation: if the absolute value of the power difference is less than the power dead zone threshold, the power difference is set to zero; if the absolute value of the power difference is greater than or equal to the power dead zone threshold, a valid demand power command is generated based on the power difference.

[0044] Suppose that the power dead zone threshold of a microgrid is set to 2kW at the current moment: At a certain time t1, the distributed photovoltaic power generation was monitored to be 15kW, and the local load power was 14.5kW; Calculate the power difference: 15kW - 14.5kW = 0.5kW (a positive value indicates excess power generation); Calculate the absolute value of the power difference: |0.5kW|=0.5kW<2kW (power dead zone threshold); Therefore, the power difference is set to zero, and no energy storage response command is generated.

[0045] At a certain moment t2, the distributed photovoltaic power generation suddenly dropped to 10kW, while the local load power remained at 14.5kW. Calculate the power difference: 10kW - 14.5kW = -4.5kW (a negative value indicates insufficient power supply); Calculate the absolute value of the power difference: |-4.5kW|=4.5kW>2kW (power dead zone threshold); Therefore, an effective demand power command is generated, requiring the energy storage battery to discharge 4.5kW to make up for the power gap.

[0046] At a certain moment t3, the distributed photovoltaic power generation was monitored to rise to 18kW, while the local load power remained at 14.5kW; Calculate the power difference: 18kW - 14.5kW = 3.5kW (a positive value indicates excess power generation); Calculate the absolute value of the power difference: |3.5kW|=3.5kW>2kW (power dead zone threshold); Therefore, an effective demand power command is generated, requiring the energy storage battery to charge 3.5kW to absorb the excess power.

[0047] This filtering mechanism can prevent energy storage batteries from responding frequently to small power fluctuations (such as 0.5kW), while ensuring timely adjustment to significant power fluctuations (such as 4.5kW or 3.5kW).

[0048] S104. Input the power value, energy storage battery charge index, energy storage battery health index and energy storage battery temperature from the effective demand power command into the battery aging cost function model, and calculate the battery aging cost value generated by executing the effective demand power command. The battery aging cost function model is a mathematical model used to quantify the cost of energy storage battery wear and tear, assessing battery usage costs by considering multiple influencing factors. The battery aging cost value represents the economic loss to the energy storage battery's lifespan caused by a single charge-discharge operation, expressed in yuan per hour. The power value refers to the required charge-discharge power of the energy storage battery, expressed in kW.

[0049] Specifically, the scheduling system uses a piecewise linear weighted method to calculate the battery aging cost: 1. Calculate the basic cost based on the power value in the effective demand power instruction: Divide the power value by the rated power of the microgrid to obtain the power utilization rate. When the power utilization rate is less than 30%, the basic cost is calculated at 0.5 yuan / kWh; when the power utilization rate is between 30% and 70%, it is calculated at 0.8 yuan / kWh; and when the power utilization rate exceeds 70%, it is calculated at 1.2 yuan / kWh. 2. Calculate the correction factor based on the energy storage battery charge index: When the energy storage battery charge index is in the range of 20%-80%, the correction factor is 1.0. When the energy storage battery charge index is below 20% or above 80%, the correction factor increases by 0.1 for every 5% deviation. For example, when the energy storage battery charge index is 90%, the correction factor is 1.2. 3. Correction factor calculated based on energy storage battery temperature: The correction factor is 1.0 when the energy storage battery temperature is in the range of 15-35℃. For every 5℃ that the energy storage battery temperature exceeds this range, the correction factor increases by 0.15. For example, when the energy storage battery temperature is 40℃, the correction factor is 1.3. 4. Calculate the correction coefficient based on the energy storage battery health index: When the energy storage battery health index is higher than 90%, the correction coefficient is 1.0. For every 10% decrease in the energy storage battery health index, the correction coefficient increases by 0.2. For example, when the energy storage battery health index is 70%, the correction coefficient is 1.4. The scheduling system multiplies the base cost by various correction factors and the power value in the effective demand power command to obtain the battery aging cost value.

[0050] Optionally, under normal circumstances, the power value in the effective demand power command, the energy storage battery charge index, the energy storage battery health index, and the energy storage battery temperature are input into the battery aging cost function model to calculate the battery aging cost value generated by executing the effective demand power command. This can be achieved in the following ways, without limitation: Obtain the preset basic depreciation cost per unit throughput of the battery; determine the charge index penalty factor based on the energy storage battery charge index, the greater the charge index deviates from the preset intermediate operating range, the larger the charge index penalty factor; determine the health index correction factor based on the energy storage battery health index, the lower the health index, the larger the health index correction factor; determine the temperature influence factor based on the energy storage battery temperature, the greater the temperature influence factor deviates from the optimal operating temperature range; calculate the battery aging cost value based on the basic depreciation cost per unit throughput of the battery, the charge index penalty factor, the health index correction factor, the temperature influence factor, and the power value in the effective demand power command.

[0051] Specifically, first, the dispatch system obtains the preset basic depreciation cost per unit throughput of the battery (e.g., 0.5 yuan / kWh). Then, the dispatch system determines the charge index penalty factor based on the battery's charge index: when the charge index deviates from the preset intermediate operating range of 20%-80%, the charge index penalty factor increases with the degree of deviation, up to a maximum of 3 times. Simultaneously, the dispatch system calculates a health index correction factor based on the battery's health index: when the battery's health index is below 80%, the health index correction factor begins to increase significantly, up to a maximum of 2 times. Furthermore, the dispatch system also considers the impact of battery temperature: when the battery temperature deviates from the optimal operating temperature range of 15-35℃, the temperature impact factor increases with the degree of deviation, up to a maximum of 1.5 times. Finally, the dispatch system multiplies the basic depreciation cost per unit throughput of the battery by the charge index penalty factor, the health index correction factor, and the temperature impact factor, and then multiplies this by the power value to obtain the battery aging cost value for this operation (e.g., 2.35 yuan / hour). This multi-factor evaluation mechanism can accurately reflect the actual cost of energy storage under different operating conditions.

[0052] S105. If the effective demand power command indicates that the energy storage battery needs to be discharged, the battery aging cost value is compared with the grid interaction cost value calculated based on the real-time electricity purchase price, and a final power dispatch command is generated to control the energy storage battery to perform the discharge action.

[0053] The real-time electricity purchase price refers to the price per unit of electricity that the microgrid buys from the external grid, expressed in yuan / kWh, and typically varies over time. The grid interaction cost represents the cost per unit of time for the microgrid to purchase electricity from the external grid to meet its electricity demand, expressed in yuan per hour. The final power dispatch command refers to the energy storage control command determined after economic evaluation. The discharge action represents the process of the energy storage battery releasing electrical energy into the microgrid.

[0054] Specifically, firstly, the dispatch system obtains the real-time electricity purchase price for the current period (e.g., 1.2 yuan / kWh), multiplies it by the absolute value of the power value in the effective demand power command (e.g., 2kW), and obtains the grid interaction cost value (2.4 yuan / hour) that the microgrid would incur if it directly purchased electricity from the external grid. Then, the dispatch system compares this grid interaction cost value with the aforementioned battery aging cost value: if the battery aging cost value is larger, it indicates that using energy storage to supplement power is uneconomical, and in this case, energy storage discharge is prohibited, and electricity is purchased from the external grid instead; if the battery aging cost value is smaller, it indicates that using energy storage is more economical, and in this case, the effective demand power command is issued as the final power dispatch command to the energy storage battery. This cost-based decision-making mechanism enables the economical and optimal allocation of energy storage resources.

[0055] By adopting the above technical solution, the dispatch system collects the distributed photovoltaic power generation and local load power of the microgrid in real time, dynamically calculates the fluctuation rate of the power difference between the two, and adaptively adjusts the power dead zone threshold accordingly, effectively avoiding frequent responses of energy storage batteries to small power fluctuations. Simultaneously, the dispatch system also establishes a battery aging cost function model considering multiple factors such as the state of charge, health status, and temperature of the energy storage batteries. It calculates the battery aging cost value generated by the energy storage batteries executing effective demand power commands and compares it with the grid interaction cost value of the microgrid purchasing electricity from the grid, thereby achieving economic optimization of energy storage battery dispatch. This adaptive dispatch strategy based on multi-dimensional evaluation not only ensures the stability of the microgrid power balance but also maximizes the lifespan of the energy storage batteries, improving the economic efficiency of microgrid operation.

[0056] The following provides a more detailed description of the process of the method provided in this implementation. Please refer to [link / reference]. Figure 2 This is another flowchart illustrating the microgrid scheduling method in this application embodiment.

[0057] S201. Set the initial default power dead zone and the maximum dead zone power limit. The maximum dead zone power limit is equal to the maximum instantaneous power exchange deviation value allowed at the microgrid grid connection point.

[0058] The initial default power dead zone refers to the basic allowable power fluctuation range set when the microgrid starts up, used to filter out minor power fluctuations, and is typically set to 1-3% of the microgrid's rated capacity. The maximum dead zone power limit refers to the maximum adjustable range of the power dead zone threshold, used to limit its expansion. The microgrid grid connection point is the point of connection between the microgrid and the external power grid, also known as the point of common coupling (PCC). The maximum instantaneous power exchange deviation value represents the maximum allowable power fluctuation amplitude at the microgrid grid connection point, specified by grid operation specifications, and is typically 10-15% of the rated exchange capacity of power flow between the microgrid and the external power grid.

[0059] Specifically, firstly, the dispatch system determines the initial default power dead zone based on the microgrid's rated capacity (e.g., 100kW), for example, taking 2% of the microgrid's rated capacity, i.e., 2kW. Then, the dispatch system obtains the maximum instantaneous power exchange deviation value at the microgrid's grid connection point. This maximum instantaneous power exchange deviation value is usually explicitly specified in the microgrid's grid connection permit, for example, taking 12% of the microgrid's rated capacity, i.e., 12kW. This limit is directly used as the maximum dead zone power upper limit, ensuring that even if the power dead zone is dynamically adjusted during subsequent microgrid operation, it will not exceed the fluctuation limits required for grid connection.

[0060] S202. Initialize the power dead zone threshold to the initial default power dead zone.

[0061] The power dead zone threshold refers to the allowable range of power fluctuations currently in use, used to determine whether an energy storage response needs to be triggered. Initialization refers to the parameter assignment process during microgrid startup. The setting of the power dead zone threshold directly affects the response frequency and sensitivity of the energy storage battery; an excessively high threshold reduces response timeliness, while an excessively low threshold leads to frequent adjustments.

[0062] Specifically, the dispatch system directly assigns the initial default power dead zone value (e.g., 2kW) set in step S201 to the power dead zone threshold variable. This initial default power dead zone serves as the baseline value for the power dead zone threshold when the microgrid starts operating. Subsequently, during microgrid operation, the dispatch system dynamically adjusts the power dead zone threshold based on actual power fluctuations. The initial default power dead zone should be appropriately determined: too small a value will lead to frequent responses from energy storage during the initial microgrid startup, while too large a value may miss necessary adjustment opportunities. Therefore, a relatively conservative initial value is usually chosen, and then optimized and adjusted later based on actual conditions.

[0063] S203. Collect real-time operating data of the microgrid. The real-time operating data shall include at least the distributed photovoltaic power generation, local load power, energy storage battery charge index, energy storage battery health index, and energy storage battery temperature.

[0064] For details, please refer to step S101, which will not be repeated here.

[0065] S204. The difference between the distributed photovoltaic power generation and the local load power is determined as the power difference. The fluctuation rate of the power difference is calculated based on the sliding time window, and the power dead zone threshold is adjusted according to the fluctuation rate. The power dead zone threshold represents the microgrid's response sensitivity to power fluctuations.

[0066] For details, please refer to step S102, which will not be repeated here.

[0067] S205. Based on the power dead zone threshold, filter the power difference and output the effective demand power command. The effective demand power command includes the power value that the energy storage battery needs to respond to. A positive power value indicates that the energy storage battery needs to be charged to absorb excess power, and a negative power value indicates that the energy storage battery needs to be discharged to make up for the power gap.

[0068] For details, please refer to step S103, which will not be repeated here.

[0069] S206. Input the power value, energy storage battery charge index, energy storage battery health index and energy storage battery temperature from the effective demand power command into the battery aging cost function model, and calculate the battery aging cost value generated by executing the effective demand power command.

[0070] For details, please refer to step S104, which will not be repeated here.

[0071] S207. If the effective demand power command indicates that the energy storage battery needs to be charged, then obtain the real-time grid-connected electricity price of the microgrid selling electricity to the grid, calculate the product of the power value in the effective demand power command and the real-time grid-connected electricity price, and obtain the potential value of the electricity sales revenue.

[0072] The real-time grid connection price refers to the price per unit of electricity sold by the microgrid to the external grid, expressed in yuan / kWh, and typically varies over time. The potential revenue from electricity sales represents the economic income per unit time that the microgrid can obtain by directly selling surplus electricity to the external grid, expressed in yuan per hour. The effective demand power command indicating the need for energy storage battery charging indicates that the power value in the effective demand power command is positive; the power value in the effective demand power command refers to the charging power of the energy storage battery, expressed in kilowatts (kW).

[0073] Specifically, first, the dispatch system obtains the real-time feed-in tariff for the current time period from the power grid dispatch center (e.g., 0.3 yuan / kWh during off-peak hours, 0.5 yuan / kWh during normal hours, and 0.8 yuan / kWh during peak hours). Then, the dispatch system multiplies the power value in the effective demand power command (e.g., 5kW) with the real-time feed-in tariff (e.g., 0.8 yuan / kWh) to calculate the potential revenue from selling electricity to the grid instead of charging the energy storage battery (e.g., 5kW × 0.8 yuan / kWh = 4 yuan / hour).

[0074] S208. Determine whether the cost of battery aging is greater than the potential revenue from electricity sales.

[0075] Specifically, the scheduling system directly compares the previously calculated battery aging cost (e.g., 1.2 yuan / hour) with the potential electricity sales revenue (e.g., 1 yuan / hour): when the battery aging cost is greater than the potential electricity sales revenue, charging and storage will actually cause economic losses; when the battery aging cost is less than or equal to the potential electricity sales revenue, charging and storage is more economical.

[0076] S209. If so, disable the energy storage battery response.

[0077] Among them, prohibiting the energy storage battery from responding means that the energy storage battery does not perform charging operations.

[0078] Specifically, if the cost of battery aging exceeds the potential revenue from electricity sales, the dispatch system will directly reject the current charging demand, stop generating control commands for the energy storage battery, and instead sell all the excess power back to the grid.

[0079] S210. If not, the effective demand power command will be determined as the final power dispatch command.

[0080] The final power dispatch command refers to the energy storage control command that is determined to be executed after an economic assessment.

[0081] Specifically, if the battery aging cost is less than or equal to the potential revenue from electricity sales, the dispatch system directly converts the effective demand power command generated in the preceding steps into a final power dispatch command, including specific parameters such as charging power value and execution time. Simultaneously, the dispatch system sends this final power dispatch command to both the energy storage management system (for executing charging control) and the grid-connected control system (for adjusting external power exchange). This command transmission mechanism ensures that each subsystem coordinates and consistently executes the predetermined dispatch strategy, achieving optimal energy storage dispatch in terms of economics.

[0082] S211. If the effective demand power command indicates that the energy storage battery needs to be discharged, then obtain the real-time electricity purchase price of the microgrid from the grid, calculate the product of the absolute value of the power value in the effective demand power command and the real-time electricity purchase price, and obtain the grid interaction cost value.

[0083] The real-time electricity purchase price refers to the price per unit of electricity that the microgrid buys from the external grid, expressed in yuan / kWh. It is typically higher than the real-time grid connection price and varies over time. The grid interaction cost represents the cost per unit time that the microgrid incurs when purchasing electricity from the external grid to meet its electricity demand, expressed in yuan per hour. The effective demand power command indicates that the energy storage battery needs to discharge; this indicates a negative power value in the effective demand power command. The absolute value of the effective demand power command refers to the magnitude of the energy storage battery discharge power, the value after removing the negative sign, expressed in kilowatts (kW).

[0084] Specifically, first, the dispatch system obtains the real-time electricity purchase price for the current time period from the power grid dispatch center (e.g., 0.4 yuan / kWh during off-peak hours, 0.8 yuan / kWh during normal hours, and 1.2 yuan / kWh during peak hours). Then, the dispatch system multiplies the absolute value of the power value in the effective demand power command (e.g., 5kW) with the real-time electricity purchase price (e.g., 1.2 yuan / kWh) to calculate the cost that would be incurred if the energy storage battery did not discharge and instead purchased electricity from the external grid (e.g., 5kW × 1.2 yuan / kWh = 6 yuan / hour).

[0085] S212. Determine whether the battery aging cost is greater than the grid interaction cost.

[0086] Specifically, the dispatch system directly compares the previously calculated battery aging cost (e.g., 1.8 yuan / hour) with the grid interaction cost (e.g., 1.5 yuan / hour): when the battery aging cost is greater than the grid interaction cost, using energy storage will increase the system operating cost; when the battery aging cost is less than or equal to the grid interaction cost, using energy storage is more economical.

[0087] S213. If so, disable the energy storage battery response.

[0088] Among them, prohibiting the energy storage battery from responding means that the energy storage battery does not perform a discharge operation.

[0089] Specifically, if the cost of battery aging exceeds the cost of grid interaction, the dispatch system will directly reject the current discharge demand, stop generating control commands for the energy storage battery, and instead purchase electricity from the grid.

[0090] S214. If not, the effective demand power command will be determined as the final power dispatch command.

[0091] The final power dispatch command refers to the energy storage control command that is determined to be executed after an economic assessment.

[0092] Specifically, if the battery aging cost is less than or equal to the grid interaction cost, the dispatch system directly converts the effective demand power command generated in the preceding steps into a final power dispatch command, including specific parameters such as discharge power value and execution time. Simultaneously, the dispatch system sends this final power dispatch command to both the energy storage management system (for executing discharge control) and the grid-connected control system (for adjusting external power exchange). This command transmission mechanism ensures that each subsystem coordinates and consistently executes the predetermined dispatch strategy, achieving optimal energy storage dispatch in terms of economics.

[0093] The scheduling system in the embodiments of this invention is described below from the perspective of hardware processing. Please refer to [link / reference needed]. Figure 3 This is a schematic diagram of the physical device structure of the scheduling system in an embodiment of this application.

[0094] It should be noted that, Figure 3 The structure of the scheduling system shown is merely an example and should not impose any limitations on the functionality and scope of use of the embodiments of the present invention.

[0095] like Figure 3 As shown, the scheduling system includes a CPU 301, which can perform various appropriate actions and processes based on a program stored in the read-only memory ROM 302 or a program loaded from the storage section 308 into the random access memory RAM 303, such as executing the methods described in the above embodiments. The RAM 303 also stores various programs and data required for system operation. The CPU 301, ROM 302, and RAM 303 are interconnected via a bus 304. An I / O interface 305 is also connected to the bus 304.

[0096] The following components are connected to I / O interface 305: input section 306 including audio input devices, push-button switches, etc.; output section 307 including a liquid crystal display (LCD) and audio output devices, indicator lights, etc.; storage section 308 including a hard disk, etc.; and communication section 309 including a network interface card such as a LAN (Local Area Network) card, modem, etc. Communication section 309 performs communication processing via a network such as the Internet. Drive 310 is also connected to I / O interface 305 as needed. Removable media 311, such as a disk, optical disk, magneto-optical disk, semiconductor memory, etc., are installed on drive 310 as needed so that computer programs read from them can be installed into storage section 308 as needed.

[0097] In particular, according to embodiments of the present invention, the processes described above with reference to the flowcharts can be implemented as computer software programs. For example, embodiments of the present invention include a computer program product comprising a computer program carried on a computer-readable medium, the computer program containing computer programs for performing the methods shown in the flowcharts. In such embodiments, the computer program can be downloaded and installed from a network via communication section 309, and / or installed from removable medium 311. When the computer program is executed by CPU 301, it performs the various functions defined in the present invention.

[0098] It should be noted that specific examples of computer-readable storage media may include, but are not limited to: electrical connections having one or more wires, portable computer disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM), flash memory, optical fiber, portable compact disc read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination thereof. In this invention, a computer-readable storage medium can be any tangible medium containing or storing a program that can be used by or in conjunction with an instruction execution system, apparatus, or device.

[0099] The flowcharts and block diagrams in the accompanying drawings illustrate the architecture, functionality, and operation of possible implementations of systems, methods, and computer program products according to various embodiments of the present invention. Each block in a flowchart or block diagram may represent a module, program segment, or portion of code, which contains one or more executable instructions for implementing a specified logical function. It should also be noted that in some alternative implementations, the functions indicated in the blocks may occur in a different order than those shown in the drawings.

[0100] Specifically, the scheduling system in this embodiment includes a processor and a memory. The memory stores a computer program, and when the computer program is executed by the processor, it implements the microgrid scheduling method provided in the above embodiment.

[0101] In another aspect, the present invention also provides a computer-readable storage medium, which may be included in the scheduling system described in the above embodiments; or it may exist independently and not be assembled into the scheduling system. The storage medium carries one or more computer programs, which, when executed by a processor of the scheduling system, cause the scheduling system to implement the microgrid scheduling method provided in the above embodiments.

[0102] The above-described embodiments are only used to illustrate the technical solutions of this application, and are not intended to limit it. Although this application has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of this application.

[0103] As used in the above embodiments, depending on the context, the term "when..." can be interpreted as meaning "if...", "after...", "in response to determining...", or "in response to detecting...". Similarly, depending on the context, the phrase "when determining..." or "if (the stated condition or event) is interpreted as meaning "if determining...", "in response to determining...", "when (the stated condition or event) is detected", or "in response to detecting (the stated condition or event)".

[0104] 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. This program can be stored in a computer-readable storage medium, and when executed, it can include the processes described in the above method embodiments. The aforementioned storage medium includes various media capable of storing program code, such as ROM or random access memory (RAM), magnetic disks, or optical disks.

Claims

1. A microgrid dispatching method, characterized in that, Applied to a scheduling system, the method includes: Collect real-time operating data of the microgrid, including at least distributed photovoltaic power generation, local load power, energy storage battery charge index, energy storage battery health index, and energy storage battery temperature; The difference between the distributed photovoltaic power generation and the local load power is defined as the power difference. The fluctuation rate of the power difference is calculated based on a sliding time window, and the power dead zone threshold is adjusted according to the fluctuation rate. The power dead zone threshold represents the microgrid's response sensitivity to power fluctuations. Based on the power dead zone threshold, the power difference is filtered and an effective demand power command is output. The effective demand power command includes the power value that the energy storage battery needs to respond to. A positive power value indicates that the energy storage battery needs to be charged to absorb excess power, and a negative power value indicates that the energy storage battery needs to be discharged to make up for the power gap. The power value in the effective demand power command, the energy storage battery charge index, the energy storage battery health index, and the energy storage battery temperature are input into the battery aging cost function model to calculate the battery aging cost value generated by executing the effective demand power command. If the effective demand power command indicates that the energy storage battery needs to be discharged, the battery aging cost value is compared with the grid interaction cost value calculated based on the real-time electricity purchase price, and a final power dispatch command is generated to control the energy storage battery to perform the discharge action.

2. The method according to claim 1, characterized in that, Before the step of collecting real-time operating data of the microgrid, which includes at least distributed photovoltaic power generation, local load power, energy storage battery charge index, energy storage battery health index, and energy storage battery temperature, the method further includes: Set an initial default power dead zone and a maximum dead zone power limit, wherein the maximum dead zone power limit is equal to the maximum instantaneous power exchange deviation value allowed at the microgrid grid connection point; The power dead zone threshold is initialized to the initial default power dead zone.

3. The method according to claim 2, characterized in that, The process involves calculating the fluctuation rate of the power difference based on a sliding time window and adjusting the power dead zone threshold according to the fluctuation rate. The power dead zone threshold represents the microgrid's response sensitivity to power fluctuations, and specifically includes: Calculate the fluctuation variance of the power difference within the sliding time window to obtain the fluctuation rate of change; If the fluctuation rate exceeds the preset high-frequency jitter threshold and the absolute value of the power difference is less than the maximum instantaneous power exchange deviation value, then the current power dead zone threshold is increased by the preset first step length until the maximum dead zone power limit is reached. If the fluctuation rate does not exceed the preset high-frequency jitter threshold, the current power dead zone threshold is reduced by a preset second step size until it is restored to the initial default power dead zone. After adjusting the current power dead zone threshold, the updated power dead zone threshold is obtained.

4. The method according to claim 3, characterized in that, The process involves filtering the power difference based on the power dead zone threshold and outputting a valid power demand command. This valid power demand command includes the power value that the energy storage battery needs to respond to. A positive power value indicates that the energy storage battery needs to be charged to absorb excess power, while a negative power value indicates that the energy storage battery needs to be discharged to fill the power gap. Specifically, this includes: If the absolute value of the power difference is less than the power dead zone threshold, the power difference is set to zero; If the absolute value of the power difference is greater than or equal to the power dead zone threshold, the effective demand power command is generated based on the power difference.

5. The method according to claim 1, characterized in that, The step of inputting the power value in the effective demand power command, the energy storage battery charge index, the energy storage battery health index, and the energy storage battery temperature into the battery aging cost function model to calculate the battery aging cost value generated by executing the effective demand power command specifically includes: Obtain the preset basic depreciation cost per unit of battery throughput; A charge index penalty factor is determined based on the energy storage battery charge index. The greater the deviation of the energy storage battery charge index from the preset intermediate operating range, the larger the charge index penalty factor. A health index correction factor is determined based on the energy storage battery health index. The lower the energy storage battery health index, the larger the health index correction factor. The temperature influence factor is determined based on the temperature of the energy storage battery. The greater the deviation of the energy storage battery temperature from the optimal operating temperature range, the larger the temperature influence factor. The battery aging cost is calculated based on the battery unit throughput basic depreciation cost, the charge index penalty factor, the health index correction factor, the temperature influence factor, and the power value in the effective demand power command.

6. The method according to claim 5, characterized in that, If the effective demand power command indicates that the energy storage battery needs to be discharged, the battery aging cost value is compared with the grid interaction cost value calculated based on the real-time electricity purchase price, and a final power dispatch command is generated to control the energy storage battery to perform a discharge action, specifically including: If the effective demand power command indicates that the energy storage battery needs to be discharged, then the real-time electricity purchase price of the microgrid from the grid is obtained, and the product of the absolute value of the power value in the effective demand power command and the real-time electricity purchase price is calculated to obtain the grid interaction cost value. Determine whether the battery aging cost value is greater than the grid interaction cost value; If so, disable the energy storage battery response; If not, the valid demand power instruction is determined as the final power scheduling instruction.

7. The method according to claim 1, characterized in that, After the step of inputting the power value in the effective demand power command, the energy storage battery charge index, the energy storage battery health index, and the energy storage battery temperature into the battery aging cost function model to calculate the battery aging cost value generated by executing the effective demand power command, the method further includes: If the effective demand power command indicates that the energy storage battery needs to be charged, then the real-time grid-connected electricity price of the microgrid sold to the grid is obtained, and the product of the power value in the effective demand power command and the real-time grid-connected electricity price is calculated to obtain the potential value of electricity sales revenue. Determine whether the battery aging cost is greater than the potential revenue from electricity sales; If so, disable the energy storage battery response; If not, the valid demand power instruction is determined as the final power scheduling instruction.

8. A scheduling system, characterized in that, The scheduling system includes: one or more processors and a memory; the memory is coupled to the one or more processors, the memory is used to store computer program code, the computer program code including computer instructions, and the one or more processors invoke the computer instructions to cause the scheduling system to perform the method as described in any one of claims 1-7.

9. A computer-readable storage medium comprising instructions, characterized in that, When the instruction is executed on the scheduling system, it causes the scheduling system to perform the method as described in any one of claims 1-7.

10. A computer program product, characterized in that, When the computer program product is run on a scheduling system, the scheduling system performs the method as described in any one of claims 1-7.

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