Energy storage multi-channel fan control system

Abstract

The invention relates to the technical field of wind power generation, in particular to an energy storage multi-channel fan control method which comprises the following steps: step 1, evaluating the wind power generation potential: firstly, analyzing the climate condition of the location of each wind power generator to estimate the potential power generation capacity of the wind power generator; the pre-estimated value is used as a basis for setting the priority of the wind driven generator, and the generator with the higher pre-estimated value can obtain the higher priority; according to the scheme, through the steps of evaluating the wind power generation potential, setting the power storage interval, monitoring the power storage state, dynamically adjusting the priority of the power storage equipment, setting the priority by considering the distance factor, determining the total priority and the like, the energy utilization efficiency is effectively improved, and the power storage and transmission strategy is optimized; the energy consumption is reduced, the system stability is improved, the response speed and economy of the system are enhanced, sustainable development is supported, the operation cost is reduced, and the continuity and reliability of power supply are ensured.

Description

A multi-channel wind turbine control system for energy storage Technical Field

[0001] This invention relates to the field of wind power generation technology, and in particular to a multi-channel wind turbine control system with energy storage. Background Technology

[0002] Existing power resource allocation often fails to fully utilize renewable energy sources such as wind and solar power, resulting in a single energy structure and a lack of flexibility. Furthermore, large-scale, intensively developed new energy projects have experienced varying degrees of wind and solar curtailment, which is related to insufficient centralized control and site maintenance capabilities for wind-solar-storage complementary power sources. Currently, wind farms, solar power plants, and energy storage power stations mostly operate, forecast, and are maintained independently, lacking effective coordination and control mechanisms, leading to inefficient resource allocation.

[0003] With the increasing proportion of renewable energy generation, the stability of the power system faces challenges. The inherent strong randomness, volatility, and intermittency of renewable energy generation make it more difficult to achieve the spatiotemporal balance of power in the power system. After large-scale renewable energy is integrated into the grid, the system's ability to withstand disturbances decreases, leading to increased frequency and voltage fluctuations during system faults. Furthermore, the anti-interference capability of power electronic equipment is weaker than that of conventional electromechanical equipment. All these factors pose a threat to the stability of the power system.

[0004] Traditional power systems fail to optimize energy allocation in energy management, leading to energy waste and losses and reduced energy efficiency. Furthermore, the lack of efficient energy storage and dispatch technologies makes it impossible to meet peak-hour energy demand, resulting in uneven energy supply and hindering the maximization of economic benefits.

[0005] In pursuing economic benefits, existing power systems often neglect their environmental impact. The use of traditional energy sources such as thermal power generation has caused pollution, while the development and utilization of new energy sources have not received sufficient attention or effective management, failing to fully realize their role in improving environmental quality.

[0006] Therefore, inventors in this field propose an energy storage multi-channel wind turbine control system. By rationally dividing power generation areas and power consumption areas according to geographical location and climate conditions, and assigning priority weights to each area, the system ensures that the priority of power supply is reasonable, thereby solving the above-mentioned shortcomings, optimizing the allocation of power resources, improving the stability of the power system, enhancing economic benefits, and strengthening environmental friendliness. Summary of the Invention

[0007] Technical problem to be solved: Traditional power systems fail to achieve optimal energy allocation in energy management, resulting in energy waste and loss, and reducing energy utilization efficiency.

[0008] To address the shortcomings of existing technologies, this invention provides an energy storage multi-channel wind turbine control system, thereby solving the technical problems mentioned in the background section.

[0009] To achieve the above objectives, the present invention provides the following technical solution: a multi-path wind turbine energy storage control method, comprising the following steps: Step 1: Assessing wind power generation potential by analyzing the climate conditions of each wind turbine's location to estimate its potential power generation capacity. This estimated value will serve as the basis for prioritizing wind turbines, with higher-valued turbines receiving higher priority; Step 2: Setting energy storage range by defining the energy storage range of the energy storage devices, including minimum and maximum energy storage capacity. These two values ​​define the overall energy storage range of the energy storage devices. Furthermore, this range is further refined by setting a charging limit range, namely, valley and peak values, to guide when the energy storage devices should charge or discharge; Step 3: Monitoring energy storage status by real-time monitoring of the status of each energy storage device. These devices supply power to different electricity consumption areas. Since the electricity demand in different areas varies over time, the discharge rate of the energy storage devices will also differ. The system will continuously track the energy storage capacity of each energy storage device to ensure that they can respond accordingly to changes in electricity demand. Step 4: Dynamically adjust the priority of energy storage devices. In the initial state, all energy storage devices are set to the same priority. As the energy storage devices discharge, the system will monitor the stored capacity of each device in real time. Once the stored capacity of a device drops to the lower limit of its second interval (i.e., the interval between the valley and the peak value), the system will automatically increase the priority of that device. Conversely, when the stored capacity of a device reaches the upper limit (peak value) of the second interval, the system will decrease the priority of that device. Step 5: Consider distance factors when setting priorities. Evaluate the physical distance between each power consumption area and the power generation area, as well as the impact of line loss on power transmission. Power consumption areas closer to the power generation area will receive higher priority due to their lower power loss, while those farther away will receive lower priority due to their higher power loss. Step 6: Determine the overall priority and adjust power transmission. Combine the weight of the energy storage device priority and the distance priority to determine the overall priority. Higher priority devices will receive power distribution rights first, while lower priority devices will not receive power distribution temporarily.

[0010] In one possible implementation, the wind power generation potential assessment is calculated using the following formula: in, Indicates the first Estimated power generation potential of a single wind turbine. Indicates climatic conditions. Indicates wind speed. Indicates temperature. This represents the prediction function.

[0011] In one possible implementation, the energy storage range setting is defined by the following formula: in, Indicates the energy storage range. Indicates the minimum storage capacity. Indicates the maximum storage capacity Indicates the valley value of the second interval. This indicates the peak value of the second interval.

[0012] In one possible implementation, the dynamic adjustment of energy storage device priorities is achieved through the following algorithm: (a) Initialization: Initialize the priority weights of all energy storage devices. (a) Same value; (b) Real-time monitoring: Monitor the stored capacity of each energy storage device. (c) Priority Adjustment: When Drop to the lower limit of the second interval At that time, improve ;when Reach the upper limit of the second interval At that time, reduce (d) Power allocation: based on priority weights Distribute the output power of wind turbines : in, Indicates the first The output power of a wind turbine to an energy storage device.

[0013] In one possible implementation, the prioritization based on distance factors is achieved through the following algorithm: in It is the first Physical distance between electricity consumption area and power generation area This formula ensures that areas that are closer together have higher priority.

[0014] In one possible implementation, the total priority is achieved through the following algorithm: in, Indicates the first The priority of each wind turbine's output power to energy storage devices. Indicates the first The first Prioritize the distance between each wind turbine and the power generation area. The higher the value, the higher the priority; This refers to a multi-channel wind turbine control system based on the aforementioned energy storage multi-channel wind turbine control method. The system includes: a wind power generation potential assessment module: used to analyze the climate conditions of each wind turbine's location to estimate its potential power generation capacity and use this as the basis for prioritizing wind turbines; an energy storage range setting module: used to define the energy storage range of the energy storage devices, including minimum and maximum storage capacity, and further refine this range by setting a charging limit range, namely, valley and peak values; and an energy storage status monitoring module: used to monitor the status of each energy storage device in real time, track the storage capacity of each device, and ensure that they can meet electricity demand. The system responds accordingly to changes in demand; a dynamic priority adjustment module for energy storage devices sets all energy storage devices to the same priority in the initial state. As the energy storage devices discharge, the system monitors the storage capacity of each device in real time. Once the storage capacity of a device drops to the lower limit of its second interval (the interval between the valley and the peak value), the system automatically increases the priority of that device to ensure it can receive power from the wind turbine for rapid replenishment. Conversely, when the storage capacity of a device reaches the upper limit (peak value) of the second interval, the system decreases the priority of that device, reducing the power supply to it; a power allocation algorithm module is used to adjust the power allocation according to priority weights. Distribute the output power of wind turbines And ensure that the output power of the wind turbine matches the priority weight of the energy storage device; Feedback adjustment module: used to adjust the output power of the wind turbine according to the real-time energy storage feedback of the energy storage device in order to maintain grid stability.

[0015] In one possible implementation, the energy storage range setting module includes: an overall energy storage range definition unit for defining the overall energy storage range of the energy storage device, including the minimum energy storage capacity and the maximum energy storage capacity; and a charging limit range setting unit for further refining the energy storage range and setting the charging limit range, i.e., the valley value and the peak value.

[0016] In one possible implementation, the dynamic adjustment module for energy storage devices includes: a priority weight initialization unit, used to initialize the priority weights of all energy storage devices to the same value when the system starts; an energy storage capacity monitoring unit, used to monitor the energy storage capacity of each energy storage device in real time and adjust the priority weights according to changes in energy storage capacity; and a priority weight adjustment unit, used to adjust the priority weights according to the valley and peak values ​​of energy storage capacity to achieve optimized allocation of power resources.

[0017] In one possible implementation, the power allocation algorithm module includes: a power allocation algorithm implementation unit: used to allocate power according to priority weights. Distribute the output power of wind turbines This ensures that the output power of the wind turbine matches the priority weight of the energy storage device; the output power adjustment unit is used to adjust the output power of the wind turbine according to the real-time energy storage feedback of the energy storage device in order to maintain grid stability.

[0018] Beneficial effects compared to existing technologies: 1. This solution effectively improves energy utilization efficiency and optimizes power storage and transmission strategies by assessing wind power generation potential, setting energy storage ranges, monitoring energy storage status, dynamically adjusting the priority of energy storage devices, considering distance factors when setting priorities, and determining the overall priority. This not only reduces energy loss and improves system stability but also enhances system response speed and economy, supports sustainable development, reduces operating costs, and ensures the continuity and reliability of power supply. 2. This solution ensures that energy storage devices can respond quickly to changes in grid demand by monitoring the energy storage capacity in real time and automatically adjusting priority weights based on changes in energy storage capacity. This dynamic adjustment mechanism allows the wind power generation system to adapt more flexibly to wind fluctuations, improving system reliability and efficiency. Simultaneously, the feedback adjustment module further maintains grid stability and efficiency by monitoring the energy storage capacity in real time and adjusting the output power of the wind turbine based on real-time data. This real-time feedback mechanism enables the system to adjust the output of the wind turbine in a timely manner to cope with sudden changes in grid demand, thereby ensuring grid stability and reducing the risk of grid instability caused by fluctuations in wind power output. Attached Figure Description

[0019] The above description is merely an overview of the technical solution of the present invention. In order to better understand the technical means of the present invention and to implement it in accordance with the contents of the specification, the preferred embodiments of the present invention are described in detail below with reference to the accompanying drawings.

[0020] Figure 1 is a flowchart of a multi-channel wind turbine control method for energy storage; Figure 2 is a framework diagram of a multi-channel wind turbine control system for energy storage. Detailed Implementation

[0021] The present application will now be further described in conjunction with the accompanying drawings and specific embodiments. It should be noted that, without conflict, the various embodiments or technical features described below can be arbitrarily combined to form new embodiments.

[0022] Please refer to Figure 1. Some embodiments of this application provide a method for controlling multiple wind turbines with energy storage. The steps include: Step 1: Assessing wind power generation potential. First, analyze the climate conditions of each wind turbine's location to estimate its potential power generation capacity. This estimated value will serve as the basis for prioritizing wind turbines; turbines with higher estimated values ​​will receive higher priority. The wind power generation potential assessment is calculated using the following formula: in, Indicates the first Estimated power generation potential of a single wind turbine. Indicates climatic conditions. Indicates wind speed. Indicates temperature. This represents the prediction function.

[0023] Step 2: Define the energy storage range. Define the energy storage range of the energy storage device, including the minimum and maximum storage capacity. These two values ​​define the overall energy storage range of the device. Furthermore, refine this range by setting a charging limit range, namely the valley and peak values, to guide when the energy storage device should charge or discharge. The energy storage range is defined using the following formula: in, Indicates the energy storage range. Indicates the minimum storage capacity. Indicates the maximum storage capacity Indicates the valley value of the second interval. This indicates the peak value of the second interval.

[0024] Step 3: Monitor the status of energy storage devices. Monitor the status of each energy storage device in real time. These devices supply power to different power consumption areas. Since the power demand of different areas changes over time, the discharge rate of the energy storage devices will also be different. The system will continuously track the energy storage capacity of each energy storage device to ensure that they can respond accordingly to changes in power demand. Step 4: Dynamically adjust the priority of energy storage devices. In the initial state, the priority of all energy storage devices is set to be the same. As the energy storage devices discharge, the system will monitor the energy storage capacity of each energy storage device in real time. Once the energy storage capacity of a certain energy storage device drops to the lower limit of its second interval (i.e., the interval between the valley and the peak), the system will automatically increase the priority of the energy storage device to ensure that it can obtain power from the wind turbine first to quickly replenish the power. Conversely, when the energy storage capacity of the energy storage device reaches the upper limit (peak) of the second interval, the system will reduce the priority of the energy storage device and reduce the power supply to it, thereby redistributing the power resources to other energy storage devices with higher priority. Such a dynamic adjustment mechanism helps to optimize the allocation of power resources and ensure the flexibility and efficiency of power supply. (a) Initialization: Initialize the priority weight of all energy storage devices. (a) Same value; (b) Real-time monitoring: Monitor the stored capacity of each energy storage device. (c) Priority Adjustment: When Drop to the lower limit of the second interval At that time, improve ;when Reach the upper limit of the second interval At that time, reduce (d) Power allocation: based on priority weights Distribute the output power of wind turbines : in, Indicates the first The output power of a wind turbine to an energy storage device.

[0025] Step 5: Prioritize based on distance factors. Evaluate the physical distance between each power consumption area and the power generation area, as well as the impact of line losses on power transmission. Power consumption areas closer to the power generation area will receive higher priority due to their lower power losses, while those farther away will receive lower priority due to their higher power losses. Prioritizing based on distance factors is implemented using the following algorithm: in It is the first Physical distance between electricity consumption area and power generation area This formula ensures that areas that are closer have higher priority; Step 6: Determine the overall priority and adjust the power transmission. Combine the priority of energy storage equipment and the proportion of distance priority to determine the overall priority. Areas with higher priority will be given priority in obtaining power distribution rights, while areas with lower priority will not be distributed to the public for the time being.

[0026] The overall priority is implemented using the following algorithm: in, Indicates the first The priority of each wind turbine's output power to energy storage devices. Indicates the first The first Prioritize the distance between each wind turbine and the power generation area. Higher values ​​indicate higher priority. In summary, by comprehensively analyzing the climatic conditions of the wind turbine's location, such as wind speed and temperature, the potential power generation capacity of each wind turbine is estimated, and the priority of wind turbines is set accordingly to ensure efficient utilization of wind energy resources. Simultaneously, the energy storage range of the energy storage devices is further defined, including minimum and maximum storage capacity, and the charging limit intervals, namely valley and peak values, are refined to guide the energy storage devices in charging or discharging when grid demand changes. Furthermore, by monitoring the status and storage capacity of the energy storage devices in real time, the system adjusts the discharge rate of the energy storage devices according to the real-time demand of the grid, ensuring that the energy storage devices can respond flexibly. During the power generation process, the system monitors the stored energy in real time. Once the stored energy drops to the lower limit between the valley and peak values, the system automatically increases the priority of the energy storage device to ensure it receives priority power from the wind turbine. Conversely, when the stored energy reaches its peak value, the system automatically decreases the priority of the energy storage device. The system assesses the physical distance between each power consumption area and the power generation area, as well as the impact of line losses on power transmission. Power consumption areas closer to the power generation area will receive higher priority due to their lower power losses, while those farther away will receive lower priority due to their higher power losses. The overall priority is determined by combining the weight of the energy storage device priority and the distance priority. The larger the value, the higher the priority.

[0027] Please refer to Figure 2. An energy storage multi-wind turbine control system, implemented using the aforementioned energy storage multi-wind turbine control method, specifically includes: a wind power generation potential assessment module; and a climate condition analysis unit that analyzes climate conditions such as wind speed, temperature, and humidity at the location of the wind turbine. For example, wind speed is a key factor affecting power generation potential, while temperature may affect the efficiency of the wind turbine.

[0028] Power generation capacity estimation unit: Based on the analysis results of climate conditions, a estimation function is used. To calculate the estimated power generation potential of each wind turbine. This prediction function can be a statistical model based on historical data, taking into account the nonlinear relationship between wind speed and temperature.

[0029] 2. Energy Storage Range Setting Module: Overall Energy Storage Range Definition Unit: Defines the overall energy storage range of the energy storage device, including the minimum storage capacity. and maximum storage capacity This range is set based on the grid demand and the capacity of the energy storage devices.

[0030] Charging Limit Range Setting Unit: Further refines the energy storage range and sets the charging limit range, i.e., the valley value. and peak The valley value is the lower limit of the storage capacity. When the storage capacity is lower than this value, the system will start charging. The peak value is the upper limit of the storage capacity. When the storage capacity reaches this value, the system will reduce charging.

[0031] 3. Energy Storage Status Monitoring Module: Real-time monitoring: Uses sensors and monitoring software to track the stored capacity of each energy storage device in real time. This data is used to assess the status of the energy storage devices and ensure they can respond appropriately to changes in electricity demand.

[0032] 4. Dynamic adjustment of energy storage device priority module: Priority weight initialization unit: When the system starts, the priority weight of all energy storage devices is initialized to the same value.

[0033] Energy storage monitoring unit: Monitors the energy storage capacity of each energy storage device in real time and adjusts the priority weight according to changes in energy storage capacity.

[0034] Priority weight adjustment unit: When the storage capacity of a certain energy storage device drops to the lower limit of the second interval (the interval between the valley and the peak value), the system automatically increases the priority of the energy storage device. Conversely, when the storage capacity of the energy storage device reaches the upper limit of the second interval, the system automatically decreases the priority of the energy storage device.

[0035] 5. Power Allocation Algorithm Module: The power allocation algorithm implementation unit allocates the output power of wind turbines according to priority weights. This algorithm ensures that the output power of wind turbines matches the priority weights of energy storage devices to achieve optimal allocation of power resources.

[0036] Output power adjustment unit: Adjusts the output power of the wind turbine according to the real-time energy storage feedback of the energy storage device in order to maintain grid stability.

[0037] 6. Feedback Adjustment Module: Real-time Feedback Unit: Monitors the energy storage capacity of the energy storage device in real time and feeds the data back to the control system of the wind turbine.

[0038] Output power adjustment unit: Adjusts the output power of the wind turbine according to the real-time feedback of energy storage data in order to maintain the stability and efficiency of the power grid.

[0039] Interaction Explained: Wind Power Potential Assessment Module and Energy Storage Range Setting Module: The power generation potential estimate provided by the wind power potential assessment module directly affects the settings of the energy storage range setting module. For example, if a wind turbine has a high power generation potential estimate, its energy storage range may be set wider to better utilize its power generation capacity.

[0040] The energy storage status monitoring module and the dynamic energy storage device priority adjustment module: The real-time energy storage data provided by the energy storage status monitoring module is the basis for the dynamic energy storage device priority adjustment module to adjust the priority weights. When the energy storage capacity of a certain energy storage device is close to its lowest value, the priority weight adjustment unit will increase its priority to ensure that it can receive power from the wind turbine first.

[0041] The power allocation algorithm module and the dynamic energy storage device priority adjustment module: The power allocation algorithm module allocates the output power of the wind turbine generators according to the priority weights set by the dynamic energy storage device priority adjustment module. This ensures that power resources are preferentially allocated to higher-priority energy storage devices, thereby improving the efficiency of the entire system.

[0042] Feedback regulation module and power allocation algorithm module: The feedback regulation module adjusts the output power of the wind turbine generator based on the output power of the power allocation algorithm module to maintain the stability and efficiency of the power grid. For example, if grid demand increases, the feedback regulation module may increase the output power of the wind turbine generator to meet the demand.

[0043] In summary, by defining the valley and peak values ​​of the energy storage range, the utilization of energy storage resources is optimized, enabling energy storage devices to flexibly respond to changes in grid demand, reducing energy waste and improving energy management efficiency. Dynamically adjusting the priority of energy storage devices and the real-time feedback regulation mechanism further enhance the system's responsiveness, ensuring that the wind power generation system can adapt to wind fluctuations in real time, maintaining grid stability and efficiency. These comprehensive measures enable the wind power generation system not only to efficiently utilize wind energy but also to provide stable power output during grid demand fluctuations, achieving efficient energy management and stable grid operation.

[0044] Finally, it should be noted that the above embodiments are merely examples for clearly illustrating the present invention and are not intended to limit the implementation. Those skilled in the art will recognize that other variations or modifications can be made based on the above description. It is neither necessary nor possible to exhaustively list all possible implementations here. However, obvious variations or modifications derived therefrom are still within the scope of protection of this invention.

Claims

1. A method for controlling a multi-channel energy storage wind turbine, characterized in that... The method includes the following steps: Step 1: Assess wind power generation potential. Analyze the climate conditions of each wind turbine's location to estimate its potential power generation capacity. This estimated value will serve as the basis for prioritizing wind turbines; turbines with higher estimated values ​​will receive higher priority. Step 2: Define energy storage range. Define the energy storage range of energy storage devices, including minimum and maximum storage capacity. These two values ​​define the overall energy storage range of the energy storage devices. Furthermore, this range is further refined by setting a charging limit range, namely valley and peak values, to guide when energy storage devices should charge or discharge. Step 3: Monitor energy storage status. Monitor the status of each energy storage device in real time. These devices supply power to different electricity consumption areas. Since the electricity demand in different areas changes over time, the discharge rate of the energy storage devices will also vary. The system will continuously track the storage capacity of each energy storage device to ensure that they can respond accordingly to changes in electricity demand. Step 4: Dynamically adjust the priority of energy storage devices. Initially, all energy storage devices are set to the same priority. As the energy storage devices discharge, the system monitors the storage capacity of each device in real time. Once the storage capacity of a device drops to the lower limit of its second interval (the interval between the valley and the peak value), the system will automatically increase the priority of that device. Conversely, when the storage capacity of a device reaches the upper limit (peak value) of the second interval, the system will decrease the priority of that device. Step 5: Consider distance factors when setting priorities. Evaluate the physical distance between each power consumption area and the power generation area, as well as the impact of line loss on power transmission. Power consumption areas closer to the power generation area will receive higher priority due to their lower power loss, while those farther away will receive lower priority due to their higher power loss. Step 6: Determine the overall priority and adjust power transmission. Combine the weight of the energy storage device priority and the distance priority to determine the overall priority. Higher priority devices will receive power distribution rights first, while lower priority devices will not receive power distribution temporarily.

2. The energy storage multi-channel wind turbine control method as described in claim 1, characterized in that... The wind power generation potential assessment is calculated using the following formula: in, Indicates the first Estimated power generation potential of a single wind turbine. Indicates climatic conditions. Indicates wind speed. Indicates temperature. This represents the prediction function.

3. The energy storage multi-channel wind turbine control method as described in claim 1, characterized in that... The energy storage range setting is defined by the following formula: in, Indicates the energy storage range. Indicates the minimum storage capacity. Indicates the maximum storage capacity Indicates the valley value of the second interval. This indicates the peak value of the second interval.

4. The energy storage multi-channel wind turbine control method as described in claim 1, characterized in that... The dynamic adjustment of energy storage device priorities is achieved through the following algorithm: (a) Initialization: Initialize the priority weights of all energy storage devices. (a) Same value; (b) Real-time monitoring: Monitor the stored capacity of each energy storage device. (c) Priority Adjustment: When Drop to the lower limit of the second interval At that time, improve ;when Reach the upper limit of the second interval At that time, reduce (d) Power allocation: based on priority weights Distribute the output power of wind turbines : in, Indicates the first The output power of a wind turbine to an energy storage device.

5. The energy storage multi-channel wind turbine control method as described in claim 1, characterized in that... The prioritization based on distance factors is implemented using the following algorithm: in It is the first Physical distance between electricity consumption area and power generation area This formula ensures that areas that are closer together have higher priority.

6. The energy storage multi-channel wind turbine control method as described in claim 1, characterized in that... The overall priority is implemented using the following algorithm: in, Indicates the first The priority of each wind turbine's output power to energy storage devices. Indicates the first The first Prioritize the distance between each wind turbine and the power generation area. The larger the value, the higher the priority.

7. A control system for an energy storage multi-channel wind turbine, implementing any one of claims 1-4, characterized in that... The system includes: a wind power generation potential assessment module, used to analyze the climate conditions of each wind turbine's location to estimate its potential power generation capacity and serve as the basis for prioritizing wind turbines; an energy storage range setting module, used to define the energy storage range of energy storage devices, including minimum and maximum storage capacity, and further refine this range by setting a charging limit range, namely, valley and peak values; and an energy storage status monitoring module, used to monitor the status of each energy storage device in real time, track the storage capacity of each device, and ensure that they can respond accordingly to changes in electricity demand; and dynamically adjust the energy storage device... Priority module: Initially, it sets the priority of all energy storage devices to the same level. As the devices discharge, it monitors the energy storage capacity of each device in real time. Once the energy storage capacity of a device drops to the lower limit of its second interval (the interval between the valley and peak values), the system automatically increases the priority of that device, ensuring it receives priority power from the wind turbine for rapid replenishment. Conversely, when the energy storage capacity of a device reaches the upper limit (peak value) of the second interval, the system decreases the priority of that device, reducing the power supply to it. Power allocation algorithm module: This module allocates power according to priority weights. Distribute the output power of wind turbines And ensure that the output power of the wind turbine matches the priority weight of the energy storage device; Feedback adjustment module: used to adjust the output power of the wind turbine according to the real-time energy storage feedback of the energy storage device in order to maintain grid stability.

8. A multi-channel wind turbine energy storage control system according to claim 5, characterized in that... The energy storage range setting module includes: an overall energy storage range definition unit, used to define the overall energy storage range of the energy storage device, including the minimum energy storage capacity and the maximum energy storage capacity; and a charging limit range setting unit, used to further refine the energy storage range and set the charging limit range, namely the valley value and the peak value.

9. A multi-channel wind turbine energy storage control system according to claim 5, characterized in that... The dynamic adjustment module for energy storage devices includes: a priority weight initialization unit, used to initialize the priority weights of all energy storage devices to the same value when the system starts; an energy storage capacity monitoring unit, used to monitor the energy storage capacity of each energy storage device in real time and adjust the priority weights according to changes in energy storage capacity; and a priority weight adjustment unit, used to adjust the priority weights according to the valley and peak values ​​of energy storage capacity to achieve optimized allocation of power resources.

10. A multi-channel wind turbine energy storage control system according to claim 5, characterized in that... The power allocation algorithm module includes: a power allocation algorithm implementation unit: used to allocate power according to priority weights. Distribute the output power of wind turbines This ensures that the output power of the wind turbine matches the priority weight of the energy storage device; the output power adjustment unit is used to adjust the output power of the wind turbine according to the real-time energy storage feedback of the energy storage device in order to maintain grid stability.

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