A Collaborative Operation Method for Grid-Based Wind Storage Systems Based on Hierarchical Tracking Collaborative Control

Abstract

This invention relates to a method for the coordinated operation of a grid-connected wind and energy storage system based on hierarchical tracking and coordinated control, belonging to the field of wind and energy storage system coordinated operation optimization. The method includes: constructing a dynamic power allocation strategy based on grid load, wind speed, and the state of charge (SOC) of the energy storage system; adjusting the power distribution ratio between wind power output and energy storage system output to maintain an optimal power ratio under different wind power and grid demand conditions; and constructing a grid-connected wind turbine angular frequency error feedback synchronization control strategy to dynamically correct the errors in wind power output and energy storage system output, ensuring real-time synchronization between wind power output and energy storage system output and grid demand. This invention, through precise power allocation and dynamic scheduling strategies, can improve the system's operational stability and economy, while also enhancing its frequency regulation capability.

Description

Technical Field

[0001] This invention belongs to the field of wind-storage system collaborative operation optimization, specifically involving a method for collaborative operation of a grid-connected wind-storage system based on hierarchical tracking collaborative control. Background Technology

[0002] With the rapid development of wind power and energy storage technologies, the combined operation of grid-connected wind power and energy storage systems has become key to solving the problems of power grid volatility and load regulation in modern grids.

[0003] The current challenges and pain points facing grid-connected wind power + energy storage systems are as follows:

[0004] 1. Dispatch challenges arising from the volatility and uncertainty of wind power

[0005] The output power of wind power is greatly affected by changes in wind speed, exhibiting significant volatility and uncertainty. This volatility can adversely impact the stability of the power grid, especially when wind speed changes are drastic, in which case the grid may be unable to effectively cope with load fluctuations from wind power.

[0006] Pain point: Fluctuations in wind power output lead to unstable grid frequency, requiring adjustments to other power sources to balance the power.

[0007] 2. Charge / discharge rate and lifespan issues of energy storage systems

[0008] Energy storage systems (such as batteries) have limited charge and discharge rates; excessively frequent charging and discharging not only affects energy storage efficiency but may also shorten their lifespan. In practical operation, balancing the charging and discharging operations of energy storage while ensuring that the grid's needs are met is a significant challenge.

[0009] Pain point: Frequent charging and discharging of energy storage systems may lead to a decrease in battery life, which in turn affects economic efficiency. Summary of the Invention

[0010] The purpose of this invention is to improve the operational stability and economy of the system through precise power allocation and dynamic scheduling strategies, while enhancing the system's frequency regulation capability, and to provide a method for the coordinated operation of a grid-connected wind and energy storage system based on hierarchical tracking and coordinated control.

[0011] To achieve the above objectives, the technical solution of the present invention is: a method for the coordinated operation of a grid-connected wind and energy storage system based on hierarchical tracking and coordinated control, comprising:

[0012] A dynamic power allocation strategy based on grid load, wind speed and SOC state of energy storage system is constructed. By adjusting the allocation ratio of wind power output and energy storage system output, the system can maintain the optimal ratio of wind power output and energy storage system output under different wind power and grid demand conditions.

[0013] A grid-connected wind turbine angular frequency error feedback synchronization control strategy is constructed. By dynamically correcting the error between the wind power output and the energy storage system output, the wind power output and the energy storage system output are synchronized with the grid demand in real time.

[0014] Furthermore, the dynamic power allocation strategy based on grid load, wind power output, and SOC state of the energy storage system includes constructing a grid-connected wind-storage system with hierarchical tracking and coordinated control, and constructing a recursive dynamic surface control strategy for energy storage. Constructing a grid-connected wind-storage system with hierarchical tracking and coordinated control includes energy storage system modeling, wind turbine system modeling, and hierarchical control structure design.

[0015] Further, the energy storage system is modeled as follows:

[0016] The formula for controlling the output power of an energy storage system is as follows:

[0017]

[0018] in, This is the power control command for the energy storage system, indicating the actual output power that the energy storage system needs to achieve. This is a reference value for controlling the output power of the energy storage system, representing the target output power of the energy storage system. This represents the current actual output power of the energy storage system. is the regulation coefficient of the energy storage system, representing the response sensitivity of the energy storage system to the reference power deviation.

[0019] Further, the wind turbine system is modeled as follows:

[0020] The formula for controlling wind power output is as follows:

[0021]

[0022] in, This is a power control command for wind power, indicating the actual output power that the wind turbine system needs to achieve. This is a reference value for wind power output control, representing the target output power of the wind turbine system; This represents the current actual output power of the wind power system. is the regulation coefficient for wind power, representing the sensitivity of the wind turbine system to deviations from the reference power.

[0023] Furthermore, the hierarchical control structure is divided into high-level control, mid-level control, and low-level control, as detailed below:

[0024] High-level control: Calculate the global power target and determine the total power demand of the power grid;

[0025] The global power control formula is as follows:

[0026]

[0027] This is a total power control command, representing the total power demand of the power grid;

[0028] Mid-level control: Allocating total power demand to the wind turbine system and energy storage system;

[0029] Design a dynamically adjustable power allocation ratio α(t), which is adjusted in real time based on grid load, wind speed, and the SOC state of the energy storage system. The specific formula is as follows:

[0030]

[0031]

[0032] in, , and Let α(t) represent the power control command of the wind power, the power control command of the energy storage system, and the total power control command at the current time t, respectively. α(t) varies with time t, and 0≤α(t)≤1.

[0033] Low-level control: Executes the power output of the wind turbine system and energy storage system to ensure that the actual output matches the control commands;

[0034] Furthermore, the formula for calculating the power allocation ratio α(t) is as follows:

[0035]

[0036] , , These are the weighted coefficients representing the impact of wind speed, grid load demand, and the SOC state of the energy storage system on the allocation coefficient. Let be the wind speed at the current time t. Let t be the current grid load demand. This represents the state of charge of the energy storage system at the current time t.

[0037] Furthermore, a recursive dynamic surface control strategy for energy storage is proposed. A method based on a recursive dynamic surface controller is constructed to adjust the output power of the energy storage system to cope with grid frequency fluctuations and load changes, as detailed below:

[0038] The input to the recursive dynamic surface controller is the current available power of the energy storage system. The reference phase angle input from the energy storage system to the converter and system frequency deviation The output of the recursive dynamic surface controller serves as the reference value for the output power control of the energy storage system. ;

[0039] System frequency deviation Gain After amplification, an adjustment signal is generated. :

[0040]

[0041] It is the control gain, used to adjust the degree of influence of frequency deviation on the output power regulation of the energy storage system;

[0042] Frequency deviation after gain The subsequent adjustment signal is regulated through the first transfer function, which describes the dynamic response of the energy storage system to frequency deviation and is expressed as:

[0043]

[0044] s represents the Laplace operator; It is the time constant of the power response of the energy storage system, which determines the response speed of the energy storage system to frequency deviation; It is the output power of the energy storage system, representing the system's adjustment response to frequency deviation;

[0045] Will The second transfer function is used to handle the charging process of the energy storage system. The second transfer function is expressed as follows:

[0046]

[0047] It is the time constant of the energy storage charging process, which determines the response speed of the energy storage system to power input during charging; It is the energy storage power signal after adjustment during the charging process;

[0048] Will The third transfer function, which combines the responses at high and low frequencies, represents the overall response of the energy storage system to changes in different frequencies, and is expressed as:

[0049]

[0050] It is a high-frequency time constant that determines the energy storage system's ability to respond to rapid frequency changes. It is the low-frequency time constant, which determines the energy storage system's ability to respond to slow frequency changes. It is the final regulating power signal of the energy storage system, which combines the effects of high and low frequencies on power output;

[0051] Final output power control reference value of energy storage system , represented as:

[0052]

[0053] This represents the current available power of the energy storage system, indicating the remaining available power of the energy storage batteries in the system.

[0054] Furthermore, a synchronous control strategy for grid-connected wind turbine angular frequency error feedback is proposed. An error feedback-based control algorithm is used to adjust the virtual angular frequency of the wind turbine. Based on the control error, a nonlinear angular frequency feedback control function is designed to quickly correct the frequency deviation by adjusting the wind power output, ensuring that the wind power and grid frequencies remain synchronized.

[0055] The present invention also provides an electronic device including a processor and a memory, wherein the memory stores a computer program that, when executed by the processor, causes the processor to perform the steps of the method described above.

[0056] The present invention also provides a computer-readable storage medium having stored thereon computer program instructions that can be executed by a processor, wherein when the processor executes the computer program instructions, it can implement the steps of the method described above.

[0057] Compared with the prior art, the present invention has the following beneficial effects:

[0058] 1. Improve system stability

[0059] The combined operation of wind power and energy storage systems significantly enhances the system's ability to cope with external disturbances and fluctuations through precise allocation and coordinated scheduling. Energy storage systems, acting as a buffer against uncertainties in wind power output, can provide support when wind power output is insufficient and absorb excess power when wind power output is excessive, thereby mitigating grid frequency fluctuations.

[0060] Advantages: The volatility of wind power output is smoothed, and system stability is significantly improved. Energy storage systems can respond quickly to instantaneous load changes, reducing grid load fluctuations.

[0061] 2. Improve economy and operational efficiency

[0062] By rationally allocating the power of wind power and energy storage systems and avoiding overcharging and discharging of energy storage devices, not only is the frequent operation of energy storage systems reduced, but the utilization rate of wind power is also improved. Wind power systems can output more power when wind speeds are suitable, while energy storage systems provide regulation when wind power is insufficient, thus improving the overall efficiency and economy of the system.

[0063] Advantages: By reducing the load on energy storage devices, the system extends their lifespan and lowers maintenance and operating costs. Simultaneously, it maximizes the use of clean wind power, improving operational economics.

[0064] 3. Improve frequency modulation capability

[0065] In terms of grid frequency regulation, energy storage systems, acting as regulators for wind power systems, can rapidly provide power support during periods of significant wind power fluctuations, thereby regulating the grid frequency. Through hierarchical tracking and coordinated control, wind power and energy storage systems can work together to adjust power output in real time according to the grid's frequency requirements.

[0066] Advantages: The system provides a fast and flexible frequency regulation response, enhancing the grid's ability to cope with load fluctuations and frequency instability. The coordinated operation of wind power and energy storage systems can stabilize grid frequency and improve the system's frequency regulation capabilities without relying on traditional fossil fuels. Attached Figure Description

[0067] Figure 1 This is a control structure diagram of the grid-type wind storage system of the present invention.

[0068] Figure 2 It is a recursive dynamic surface controller.

[0069] Figure 3 To provide synchronous control of the angular frequency error of the grid-connected wind turbine.

[0070] Figure 4 The results are simulation results for low wind speeds; where (a) is the frequency response, (b) is the wind power output, (c) is the energy storage output power, and (d) is the energy storage SOC. Detailed Implementation

[0071] The technical solution of the present invention will now be described in detail with reference to the accompanying drawings.

[0072] This invention provides a method for the coordinated operation of a grid-connected wind-storage system based on hierarchical tracking and coordinated control, comprising:

[0073] A dynamic power allocation strategy based on grid load, wind speed and SOC state of energy storage system is constructed. By adjusting the allocation ratio of wind power output and energy storage system output, the system can maintain the optimal ratio of wind power output and energy storage system output under different wind power and grid demand conditions.

[0074] A grid-connected wind turbine angular frequency error feedback synchronization control strategy is constructed. By dynamically correcting the error between the wind power output and the energy storage system output, the wind power output and the energy storage system output are synchronized with the grid demand in real time.

[0075] The following is a detailed implementation process of the present invention.

[0076] This example provides a method for the coordinated operation of a grid-connected wind-storage system based on hierarchical tracking and coordinated control, which mainly includes the following three parts:

[0077] 1. Design of a grid-connected wind-storage system with hierarchical tracking and collaborative control (see...) Figure 1 )

[0078] (1) Energy storage system modeling

[0079] The primary task of energy storage systems (such as batteries) is to charge and discharge to balance power fluctuations in the power grid. The relationship between the energy storage power control command and its reference power can be represented by a proportional control model.

[0080] Energy storage power control formula:

[0081]

[0082] in, This is the power control command for the energy storage system, indicating the actual output power that the energy storage system needs to achieve. This is a reference value for controlling the output power of the energy storage system, representing the target output power of the energy storage system. This represents the current actual output power of the energy storage system. is the regulation coefficient of the energy storage system, representing the response sensitivity of the energy storage system to the reference power deviation.

[0083] Power control in energy storage systems is typically adjusted based on the deviation between the target power and the current power. Through proportional control, the system automatically adjusts the energy storage power output to ensure it is close to the reference value.

[0084] (2) Wind turbine system modeling

[0085] The power output of a wind turbine is closely related to factors such as wind speed and the turbine's operating conditions (e.g., blade angle). The relationship between the turbine's power control and its reference value can be described using a proportional control model. Wind turbine power control formula.

[0086]

[0087] in, This is a power control command for wind power, indicating the actual output power that the wind turbine system needs to achieve. This is a reference value for wind power output control, representing the target output power of the wind turbine system; This represents the current actual output power of the wind power system. is the regulation coefficient for wind power, representing the sensitivity of the wind turbine system to deviations from the reference power.

[0088] The power control of the wind turbine adopts a proportional control method similar to that of energy storage systems. The control objective is to ensure that the output power of the wind turbine is as close as possible to the reference value. Yes Real-time tracking.

[0089] (3) Hierarchical control structure

[0090] The goal of hierarchical control is to rationally allocate the power of wind power and energy storage systems to meet the needs of the power grid. We adopt a multi-layered control structure, consisting of high-level control, mid-level control, and low-level control.

[0091] (3.1) High-level control: Global power target

[0092] The goal of high-level control is to determine the total power demand of the system. This layer primarily relies on grid demand and calculates allocation based on the capabilities of energy storage and wind power systems.

[0093] Global power control formula:

[0094]

[0095] This is a total power control command, representing the total power demand of the power grid;

[0096] In high-level control, the system's objective is to ensure that the total power output of the wind power and energy storage systems meets the grid's demand. Therefore, the system will achieve this objective through appropriate power allocation.

[0097] (3.2) Middle-level control

[0098] The goal of this level is to rationally allocate the power output of wind power and energy storage systems based on grid demand, wind power fluctuations, and the charging and discharging capabilities of energy storage. Through control at this level, it can be ensured that:

[0099] A. Stability of the power grid.

[0100] B. The energy storage system will not overcharge or discharge, thus avoiding damage to the equipment.

[0101] C. The power output of the wind power system meets the grid dispatch requirements, while taking into account the uncertainty of wind speed.

[0102] Dynamic adjustment of power allocation ratio:

[0103] This invention designs a dynamically adjustable power allocation ratio α(t), which is adjusted in real time based on system conditions (such as grid load, wind speed, and energy storage SOC). The specific formula is:

[0104]

[0105]

[0106] in, , and Let α(t) represent the power control command of the wind power, the power control command of the energy storage system, and the total power control command at the current time t, respectively. α(t) varies with time t, and 0≤α(t)≤1.

[0107] Allocation coefficient Calculation:

[0108] To achieve more rational power allocation, this invention dynamically adjusts the allocation coefficient based on the following key factors. :

[0109] Grid load demand When the grid load is high, more energy storage systems are needed to support it, and the proportion of power allocated to energy storage should be increased.

[0110] Wind speed changes When the wind speed is high, the output power of the wind turbine is greater, thus increasing the power distribution ratio of wind power.

[0111] State of charge of energy storage The state of the energy storage battery determines its charging and discharging capacity. When the energy storage SOC is low, the energy storage system needs to absorb more power from the grid for charging. At this time, the power output ratio of the energy storage should be reduced.

[0112] Therefore, the allocation coefficient The calculation can be designed as follows:

[0113]

[0114] , , These are the weighted coefficients representing the impact of wind speed, grid load demand, and the SOC state of the energy storage system on the allocation coefficient. The wind speed at the current time t affects the wind power output. The current grid load demand at time t affects the power distribution of the system. The state of charge of the energy storage system at the current time t affects the output power of the energy storage system.

[0115] When wind speed is high, load demand is low, and energy storage SOC is sufficient, the proportion of wind power... It will be larger, and more power will be allocated to the wind turbines.

[0116] When the grid load is high, the wind speed is low, or the energy storage SOC is low, the proportion of energy storage 1−α(t) will increase, and more power will be allocated to the energy storage system.

[0117] (3.3) Low-level control: Specifically executes the power output of the wind turbine and energy storage system to ensure that the actual output matches the control command.

[0118] Hierarchical control:

[0119] High-level control: Calculate the global power target and determine the total power demand.

[0120] Mid-level control: Allocate total power demand reasonably to wind power and energy storage systems.

[0121] Low-level control: Specifically executes the power output of the wind turbine and energy storage system, ensuring that the actual output matches the control commands.

[0122] In the design of a grid-connected wind-storage system with hierarchical tracking and coordinated control, the input for hierarchical tracking and coordinated control is the energy storage power control reference value. Reference value for grid-connected wind power control The output is the energy storage power control command value. Power control command value of grid wind turbine .

[0123] 2. Energy storage recursive dynamic surface control strategy (see...) Figure 2 )

[0124] The input to the recursive dynamic surface controller is the current available power of the energy storage. The reference phase angle of the energy storage input to the converter System frequency deviation The output is the reference value for energy storage power control. .

[0125] This invention proposes a method based on Recursive Dynamic Surface Control (RDC) for regulating the power output of an energy storage system to cope with grid frequency fluctuations and load changes. Through detailed mathematical derivation, this paper demonstrates the control process of power regulation in the energy storage system, combining frequency deviation, energy storage state, charging process, and system response to ensure the stable operation of the energy storage system under grid frequency fluctuations.

[0126] The power regulation process of an energy storage system includes frequency deviation sensing, energy storage power adjustment, and system dynamic response. The control strategy of this invention is based on a recursive dynamic surface controller, which gradually adjusts the power output of the energy storage system to ensure synchronization with the grid frequency.

[0127] 2.1 Input of control signals and gain adjustment

[0128] The first step in power regulation of an energy storage system is handling frequency deviation. The difference between the actual and expected grid frequency (i.e., frequency deviation Δf) directly affects the power output of the energy storage system. Frequency deviation Δf is then processed by gain adjustment. After amplification, an adjustment signal is generated. :

[0129]

[0130] Where: Δf is the frequency deviation of the power grid, representing the difference between the actual frequency of the power grid and the target frequency. It is the control gain, used to adjust the degree to which frequency deviation affects the power regulation of the energy storage system. A larger one... This indicates that the system is more sensitive to frequency deviations and responds faster.

[0131] 2.2 Energy storage power regulation:

[0132] Frequency deviation after gain The subsequent adjustment signal is regulated through the first transfer function. The transfer function describes the dynamic response of the energy storage system to frequency deviation.

[0133]

[0134] s represents the Laplace operator; This is the time constant of the energy storage system's power response. This time constant determines the energy storage system's response speed to frequency deviations. A larger time constant... A higher speed indicates a slower system response, while a higher speed indicates a faster response. It is the energy storage power signal, representing the energy storage system's adjustment response to frequency deviation.

[0135] After the regulation signal is processed by the first transfer function, the power signal of the energy storage system The process will then proceed to the second transfer function, which handles the charging process of the energy storage device. The time constant for the charging process is... The transfer function is:

[0136]

[0137] in: It is the time constant of the energy storage charging process, which determines the response speed of the energy storage battery to power input during charging. A larger... This indicates that the charging process is slow and the energy storage power adjustment response is slow. It is the energy storage power signal after being adjusted during the charging process.

[0138] Energy storage power signal The third transfer function combines the high-frequency and low-frequency responses, representing the overall response of the energy storage system to variations in frequency (including rapid and slow frequency fluctuations). This transfer function is:

[0139]

[0140] in: It is a high-frequency time constant, which determines the energy storage system's ability to respond to rapid frequency changes. It is a low-frequency time constant, which determines the energy storage system's ability to respond to slow frequency changes. It is the final regulating power signal of the energy storage system, which combines the effects of high and low frequencies on power output.

[0141] Final power reference value of energy storage system It is determined by the following three parts:

[0142]

[0143] in: : Current available power of energy storage, indicating the remaining available power of the energy storage battery. The reference phase angle of the energy storage input to the converter is used to ensure that the power output of the energy storage system is phase-matched with the grid frequency. The energy storage power signal, obtained through a recursive dynamic surface controller, represents the energy storage system's response to frequency fluctuations. Ultimately, As a power control reference value for energy storage systems, it is used to adjust the output power of energy storage devices to ensure the stability of grid frequency.

[0144] The power output of the energy storage system is adjusted by a recursive dynamic surface controller (RDC) to cope with grid frequency fluctuations and load changes. By comprehensively considering frequency deviation, available energy storage power, dynamic characteristics of the charging process, and the system's response to different frequency fluctuations, the energy storage system can adjust its power output in real time to support grid frequency stability.

[0145] The mathematical model for energy storage power regulation uses a combination of transfer functions to gradually adjust the power output of the energy storage system. This ensures that the system can quickly and effectively regulate power under grid frequency fluctuations and load changes, providing necessary frequency regulation support for the grid. This control method exhibits high real-time performance and stability, making it suitable for frequency control and energy storage management in modern power grids.

[0146] 3. Synchronous control strategy for angular frequency error feedback of grid-connected wind turbines (see...) Figure 3 )

[0147] To ensure frequency synchronization between wind turbines and the power grid, this invention proposes an error feedback-based control algorithm for adjusting the virtual angular frequency of the wind turbines. Based on control errors, this algorithm designs a nonlinear angular frequency feedback control function, which quickly corrects frequency deviations by adjusting the wind turbine's output power, thereby ensuring frequency synchronization between the wind turbine and the power grid. This invention will derive the mathematical model of the control algorithm in detail, explain the physical meaning of all relevant variables, and demonstrate its application in grid-connected wind turbine power control.

[0148] The input to the grid-connected wind turbine is the output power of the wind turbine after load reduction. The network wind turbine outputs a virtual angular frequency. System angular frequency System frequency deviation Where d% is the fan unloading rate, v is the wind speed, and e is the wind speed. ω The virtual angular frequency deviation of the grid-connected wind turbine represents the difference between the turbine's virtual angular frequency and the grid frequency, and is the main feedback variable of the control system. The control objective is to adjust the turbine's output power through a feedback control mechanism, thereby making e ω Minimize, meaning keep the virtual angular frequency of the wind turbine synchronized with the grid frequency.

[0149]

[0150] To correct the error e ω (t), design a nonlinear control function f based on error feedback. a (e ω This function, denoted by α, λ, adjusts the power output of the fan. The control function takes the following form:

[0151]

[0152] Where α and β are the controller's adjustment parameters. tanh(λ·e ω β·e is the hyperbolic tangent function, used to smooth the control response with small errors and avoid over-adjustment. ω It is a linear term, which enhances the control response under large errors and ensures that the system can quickly restore synchronization.

[0153] hyperbolic tangent term α·tanh(λ·e) ω )

[0154] Physical meaning: The hyperbolic tangent function is a common nonlinear function, which plays a significant role in error... It provides a smooth response when the error is small, and gradually enhances the response as the error increases. This can effectively prevent the system from overreacting to small errors.

[0155] Adjust parameters:

[0156] α: Controls the amplitude of the hyperbolic tangent term, adjusting the controller's response strength when there is a small error.

[0157] λ: Adjusts the system's sensitivity to error; a larger λ will make the system more sensitive to changes in error.

[0158] Linear term β·e ω

[0159] Physical meaning: The linear term is used to enhance the system's response to large errors. When the error e ω When the frequency is large, the linear term provides a stronger control signal, helping the system to quickly correct large frequency deviations.

[0160] Adjust parameters:

[0161] β: Controls the gain of the linear term, determining the adjustment level under large error conditions.

[0162] Fan power control and virtual angular frequency adjustment

[0163] The output signal f of the control system a (e ω The values ​​α, λ will directly affect the power output of the wind turbine, thereby adjusting the turbine's virtual angular frequency. Specifically, the relationship between the wind turbine's power output and the virtual angular frequency can be described by a transfer function:

[0164]

[0165] This formula indicates that by adjusting the control signal f a (e ω As the angular frequency of the wind turbine changes (α, λ), it affects the turbine's virtual angular frequency, causing it to tend to match the grid frequency.

[0166] To ensure the stability of the control system, it is necessary to ensure that the virtual angular frequency of the wind turbine can quickly and smoothly follow changes in the grid frequency. The stability of the control system is usually verified through root locus method, frequency response analysis, or numerical simulation. Theoretically, by reasonably selecting the control parameters α, λ, and β, it is possible to achieve fast response and stability of the system under different frequency fluctuations.

[0167] Through experiments and simulations, parameters α, λ, and β can be adjusted to optimize the system's response speed and stability.

[0168] α: A smaller α can avoid overreacting to small errors, while a larger α can improve the system's ability to respond to small errors.

[0169] λ: A larger λ will enhance the system's sensitivity to changes in error, helping the system to quickly correct frequency deviations when the error is small.

[0170] β: A larger β enhances the system's response speed under large errors, while a smaller β can slow down the system's correction for large errors.

[0171] This invention proposes a nonlinear control algorithm based on error feedback to adjust the virtual angular frequency of a wind turbine, keeping it synchronized with the grid frequency. This is achieved by designing a control function f... a (e ω By combining wind turbine power control with parameters (α, λ), this invention achieves real-time adjustment of the wind turbine and grid frequency. Through the rational selection of adjustment parameters, the control system can provide a fast and stable response under various frequency deviation conditions, ensuring stable system operation.

[0172] This control method simplifies the original complex model while ensuring the feasibility of the system in practical applications. It is suitable for the synchronous control of grid-connected wind turbines and the power grid.

[0173]

[0174] , These are the synchronization compensation coefficient and the adaptive adjustment gain, respectively. For adaptive load shedding power output based on angular frequency, To compensate for the reduced load power gain of the grid-connected wind turbines. The power increment is controlled by the phase angle of the wind turbine. To regulate the frequency power of the grid-connected wind turbine, The frequency sag coefficient of the grid fan.

[0175] It is expressed as follows:

[0176]

[0177] Final grid-connected wind power control reference value It is expressed as follows:

[0178]

[0179] The proposed Angular Frequency Error Feedback Synchronization Control (AFEFS) algorithm achieves synchronization between the wind turbine and the grid frequency by adjusting the virtual angular frequency of the wind turbine. Based on a feedback mechanism, this control algorithm corrects the deviation between the virtual angular frequency and the grid frequency by adjusting the wind turbine power, thereby ensuring synchronization between the wind turbine and the grid. This control method has significant practical implications for wind power generation and grid frequency control.

[0180] Simulation verification

[0181] To evaluate the effectiveness and robustness of the proposed strategy, this invention designs a step load disturbance scenario under low wind speed (6.5 m / s) and conducts a comparative study on hierarchical tracking coordinated control (LTCC) and traditional droop control for a grid-type wind-storage system. The simulation sets the initial State of Charge (SOC) at 50% and applies a step load disturbance of 50 MW amplitude after 5 seconds. To evaluate the effect of frequency regulation control and the SOC maintenance capability of the energy storage system, the maximum frequency deviation (Δfmax) and steady-state frequency deviation (Δfs) are used as performance evaluation indicators.

[0182] from Figure 4 It can be seen that the proposed LTCC control strategy can dynamically adjust the power output ratio of wind power and energy storage according to changes in system frequency, fully leveraging the synergistic frequency regulation advantages of the wind-storage system, thereby improving system stability and economy. Combined with frequency regulation indicators, the LTCC strategy reduces the maximum frequency deviation (Δfmax) by 16.49% and the steady-state frequency deviation (Δfs) by 5.01% compared to droop control. Under low wind speed conditions, wind turbines have insufficient kinetic energy, and traditional droop control can easily lead to frequency regulation at low speeds, potentially causing shutdowns and system instability. Under LTCC control, the minimum speed of the grid-connected DFIG wind turbine is increased by 0.019 pu compared to droop control, and the speed change is more stable. Simultaneously, the fluctuation of the energy storage system's SOC is smaller, indicating that this control strategy effectively reduces the equivalent full cycle number and depth of discharge of energy storage, slows down capacity decay, and improves the system's safety margin and availability. Ultimately, this strategy not only ensures the stable operation of wind turbines and improves energy utilization efficiency but also enhances the reliability and sustainability of wind-storage joint frequency regulation.

[0183] The present invention also provides an electronic device including a processor and a memory, wherein the memory stores a computer program that, when executed by the processor, causes the processor to perform the steps of the method described above.

[0184] The present invention also provides a computer-readable storage medium having stored thereon computer program instructions that can be executed by a processor, wherein when the processor executes the computer program instructions, it can implement the steps of the method described above.

[0185] The above are preferred embodiments of the present invention. Any changes made to the technical solution of the present invention that do not exceed the scope of the technical solution of the present invention shall fall within the protection scope of the present invention.

Claims

1. A method for the coordinated operation of a grid-connected wind-storage system based on hierarchical tracking and coordinated control, characterized in that, include: A dynamic power allocation strategy based on grid load, wind speed and SOC state of energy storage system is constructed. By adjusting the allocation ratio of wind power output and energy storage system output, the system can maintain the optimal ratio of wind power output and energy storage system output under different wind power and grid demand conditions. Dynamic power allocation strategies based on grid load, wind speed and SOC state of energy storage system include building a grid-connected wind-storage system with hierarchical tracking and collaborative control and building a recursive dynamic surface control strategy for energy storage. Constructing a hierarchical tracking and collaborative control grid-connected wind-storage system includes energy storage system modeling, wind turbine system modeling, and hierarchical control structure design; A recursive dynamic surface control strategy for energy storage is proposed. This method, based on a recursive dynamic surface controller, adjusts the output power of the energy storage system to cope with grid frequency fluctuations and load changes, as detailed below: The input to the recursive dynamic surface controller is the current available power of the energy storage system. The reference phase angle input from the energy storage system to the converter and system frequency deviation The output of the recursive dynamic surface controller serves as the reference value for the output power control of the energy storage system. ; System frequency deviation Gain After amplification, an adjustment signal is generated. : It is the control gain, used to adjust the degree of influence of frequency deviation on the output power regulation of the energy storage system; Frequency deviation after gain The subsequent adjustment signal is regulated through the first transfer function, which describes the dynamic response of the energy storage system to frequency deviation and is expressed as: s represents the Laplace operator; It is the time constant of the power response of the energy storage system, which determines the response speed of the energy storage system to frequency deviation; It is the output power of the energy storage system, representing the system's adjustment response to frequency deviation; Will The second transfer function is used to handle the charging process of the energy storage system. The second transfer function is expressed as follows: It is the time constant of the energy storage charging process, which determines the response speed of the energy storage system to power input during charging; It is the energy storage power signal after adjustment during the charging process; Will The third transfer function, which combines the responses at high and low frequencies, represents the overall response of the energy storage system to changes in different frequencies, and is expressed as: It is a high-frequency time constant that determines the energy storage system's ability to respond to rapid frequency changes. It is the low-frequency time constant, which determines the energy storage system's ability to respond to slow frequency changes. It is the final regulating power signal of the energy storage system, which combines the effects of high and low frequencies on power output; Final output power control reference value of energy storage system , represented as: This represents the current available power of the energy storage system, indicating the remaining available power of the energy storage batteries in the system. A grid-connected wind turbine angular frequency error feedback synchronization control strategy is constructed. By dynamically correcting the error between the wind power output and the energy storage system output, the wind power output and the energy storage system output are synchronized with the grid demand in real time.

2. The method for coordinated operation of a grid-connected wind-storage system based on hierarchical tracking and coordinated control according to claim 1, characterized in that, The energy storage system modeling is as follows: The formula for controlling the output power of an energy storage system is as follows: in, This is the power control command for the energy storage system, indicating the actual output power that the energy storage system needs to achieve. This is a reference value for controlling the output power of the energy storage system, representing the target output power of the energy storage system. This represents the current actual output power of the energy storage system. is the regulation coefficient of the energy storage system, representing the response sensitivity of the energy storage system to the reference power deviation.

3. The method for coordinated operation of a grid-connected wind-storage system based on hierarchical tracking and coordinated control according to claim 2, characterized in that, The wind turbine system is modeled as follows: The formula for controlling wind power output is as follows: in, This is a power control command for wind power, indicating the actual output power that the wind turbine system needs to achieve. This is a reference value for wind power output control, representing the target output power of the wind turbine system; This represents the current actual output power of the wind power system. is the regulation coefficient for wind power, representing the sensitivity of the wind turbine system to deviations from the reference power.

4. The method for coordinated operation of a grid-connected wind-storage system based on hierarchical tracking and coordinated control according to claim 3, characterized in that, The hierarchical control structure is divided into high-level control, middle-level control, and low-level control, as detailed below: High-level control: Calculate the global power target and determine the total power demand of the power grid; The global power control formula is as follows: This is a total power control command, representing the total power demand of the power grid; Mid-level control: Allocating total power demand to the wind turbine system and energy storage system; Design a dynamically adjustable power allocation ratio α(t), which is adjusted in real time based on grid load, wind speed, and the SOC state of the energy storage system. The specific formula is as follows: in, , and Let α(t) represent the power control command of the wind power, the power control command of the energy storage system, and the total power control command at the current time t, respectively. α(t) varies with time t, and 0≤α(t)≤1. Low-level control: Executes the power output of the wind turbine system and energy storage system, ensuring that the actual output matches the control commands.

5. The method for coordinated operation of a grid-connected wind-storage system based on hierarchical tracking and coordinated control according to claim 4, characterized in that, The formula for calculating the power allocation ratio α(t) is as follows: , , These are the weighted coefficients representing the impact of wind speed, grid load demand, and the SOC state of the energy storage system on the allocation coefficient. Let be the wind speed at the current time t. Let t be the current grid load demand. This represents the state of charge of the energy storage system at the current time t.

6. The method for coordinated operation of a grid-connected wind-storage system based on hierarchical tracking and coordinated control according to claim 1, characterized in that, A synchronous control strategy for grid-connected wind turbine angular frequency error feedback is proposed. An error feedback-based control algorithm is used to adjust the virtual angular frequency of the wind turbine. Based on the control error, a nonlinear angular frequency feedback control function is designed to quickly correct the frequency deviation by adjusting the wind power output, ensuring that the wind power frequency and the grid frequency remain synchronized.

7. An electronic device, characterized in that, It includes a processor and a memory, wherein the memory stores a computer program that, when executed by the processor, causes the processor to perform the steps of the method as described in any one of claims 1-6.

8. A computer-readable storage medium, characterized in that, It stores computer program instructions that can be executed by a processor, and when the processor executes the computer program instructions, it can implement the steps of the method as described in any one of claims 1-6.

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