Frequency regulation optimization control method considering wind-fire storage cooperation

Abstract

The invention discloses a frequency regulation optimization control method considering wind-fire storage cooperation, and belongs to the technical field of novel power system frequency regulation. Comprising the steps of establishing a wind power frequency modulation model, a thermal power and power grid frequency modulation model and a flywheel energy storage frequency modulation model; designing a frequency first-order low-pass filter, decomposing a frequency signal into a high-frequency signal and a low-frequency signal, and performing flywheel energy storage and wind power response respectively; a thermal power primary frequency modulation signal first-order filter is designed, a primary frequency modulation signal is decomposed into a high-frequency component and a low-frequency component, the high-frequency component is responded by a wind storage system in proportion and serves as compensation of respective frequency modulation instructions, and the low-frequency component is responded by a thermal power generating unit; designing a wind power frequency modulation control strategy and a flywheel energy storage charging and discharging control strategy considering the charge state; different scenes are set, and the frequency modulation effect and the thermal power fluctuation relieving performance are analyzed. Generator output fluctuation can be effectively reduced, frequency modulation pressure is shared for the thermal power generating unit, and safe and stable operation of the system is facilitated.

Description

Technical Field

[0001] The present invention relates to the technical field of novel power system frequency regulation, and in particular to a frequency regulation optimization control method considering the coordination of wind, thermal and storage. Background Art

[0002] As wind power penetration gradually increases, the proportion of traditional synchronous turbines will significantly decrease. Large-scale grid integration of wind farms lacking autonomous frequency regulation capabilities will weaken the power system's ability to cope with frequency fluctuations, negatively impacting grid frequency stability and making grid frequency stability issues increasingly prominent. To enable primary frequency regulation in wind turbines, existing technologies mostly implement this capability by attaching power controllers to the turbines. Currently, wind turbines in wind farms primarily utilize rotor kinetic energy control and power reserve control. Rotor kinetic energy control technology can be implemented while the wind turbine maintains maximum power point tracking (MPPT) operation. It utilizes the released kinetic energy in the rotor to provide the required frequency support for the system. System frequency regulation using rotor kinetic energy is primarily divided into a frequency support phase and a speed recovery phase. After the wind turbine completes the speed kinetic energy release during the frequency support phase, the rotor must undergo speed recovery. However, this speed recovery requires reducing electromagnetic torque to increase the rotor speed, which can result in a power shortfall and easily cause the system frequency to drop again, known as secondary frequency drop.

[0003] In terms of alleviating the secondary frequency drop, some literature adopts the rotor kinetic energy method, such as "Ji Xiaotong, Jiang Kezheng, Yao Yahan, et al. Frequency cooperative support control of wind farms considering the difference in wind turbine operating status [J]. Electric Power Automation Equipment, 2024, 44(03): 98-104.", which proposes a progressive speed recovery strategy to achieve smooth switching between different control stages, but the speed recovery time is relatively long. "Tang Y, Yang P, Yang Y, et al. Fuzzy adaptive frequency support control strategy for wind turbines with improved rotor speed recovery [J]. IEEE Transactions on Sustainable Energy, 2023, 15(2): 1351-1364." proposes a fuzzy adaptive frequency support control strategy for wind turbines with improved rotor speed recovery, which uses rotor speed and frequency deviation to adaptively adjust the proportional gain to avoid the secondary frequency drop caused by excessive deceleration of wind turbines with low rotor speeds, but the algorithm logic is relatively complex. However, no matter how the speed recovery strategy is designed, it can only alleviate the SFD, but cannot completely eliminate it; while the load reduction control of the wind turbine achieves a long period of active reserve by reducing the output, which will not cause a secondary drop in frequency. "Wang Tongsen, Zhang Feng, Ding Lei. Frequency Control Strategy of Overspeed Wind Turbine Considering the Optimal Operating Point [J]. Electric Power Automation Equipment, 2021, 41(06): 22-28." proposed a frequency control strategy for overspeed wind turbine considering the optimal operating point, and solved the optimal operating point under different wind speeds through the frequency regulation energy model, making full use of the reserve capacity of the wind turbine to participate in frequency adjustment. "Peng Haitao, He Shan, Yuan Zhi, et al. Primary Frequency Regulation Strategy of Variable Speed ​​Wind Turbine Based on Improved Coordinated Control of Rotor Speed ​​and Pitch Angle [J]. Electric Power Automation Equipment, 2023, 43(09): 87-94." proposed a primary frequency regulation strategy based on improved coordinated control of rotor speed and pitch angle, which reserves the power margin required for frequency regulation in the full wind speed range and can provide fast and lasting active support when the system frequency fluctuates. While secondary drops do not occur in standby load shedding mode, the load shedding ratio in most literature is maintained at 10% to 20%. Prolonged, high-ratio load shedding can lead to significant wind curtailment. Furthermore, variable pitch load shedding significantly impacts mechanical wear and lifespan of wind turbines. Furthermore, the random nature of wind power affects its frequency regulation, and fluctuations in wind power can further deteriorate grid frequency.

[0004] Energy storage systems have fast response speed and flexible control, making them an effective means of grid frequency regulation. To improve frequency regulation performance, most existing wind farms cooperate with energy storage to participate in primary frequency regulation. Wind-storage combined frequency regulation has become another research hotspot. "Miao L, Wen J, Xie H, et al. Coordinated control strategy of wind turbine generator and energy storage equipment for frequency support [J]. IEEE Transactions on Industry Applications, 2015, 51 (4): 2732-2742." By coordinating the output of wind power and energy storage through fuzzy control, the secondary frequency drop was successfully alleviated, but the method can only provide short-term frequency support. With the development of intelligent algorithms, model predictive control and reinforcement learning have also been widely applied by scholars to wind-storage combined frequency regulation. "Zhu Y, Shi Q, Yao S, et al. Adaptive MPC and power dispersion index based improved hierarchical frequency regulation for wind-storage integrated system [J]. Journal of Energy Storage, 2025, 107: 115006." uses adaptive model predictive control (MPC). The upper controller adopts an adaptive weight coefficient strategy within the MPC framework, allowing for flexible adjustment of the power output of the wind farm and energy storage system, thereby improving the frequency regulation performance. In the lower controller, a new power dispersion indicator is introduced to minimize the pitch angle fluctuation of the wind turbine and optimize the power distribution of the entire wind farm while considering the torque fluctuation. "Xu Bo, Yu Xiangdong, Yang Yixin, et al. Distributed wind-storage collaborative frequency control strategy based on multi-agent system [J]. Power System Protection and Control, 2022, 50(19): 13-24." A distributed wind-storage collaborative frequency control strategy based on a multi-agent system is proposed. When the power grid experiences a frequency disturbance, each agent adjusts the control parameters through a distributed method, controls the corresponding wind-storage equipment to assist the synchronous generator set in participating in inertia response and primary frequency regulation. However, the modeling engineering of MPC and reinforcement learning is relatively difficult and difficult to apply in practice.

[0005] In the above literature, whether wind power or wind energy storage jointly participates in the frequency regulation of the power system, although synchronous units are modeled in the modeling process, the thermal power output constraint is not included in the frequency regulation of the wind-thermal energy storage system. "Chen Biao, Wang Wei, Gao Song, et al. Collaborative optimization of capacity configuration and frequency regulation parameters of thermal power-flywheel energy storage system considering flexible, economical and environmentally friendly operation [J]. Journal of Power Engineering, 2024, 44(03): 376-384" divides the frequency difference into high and low frequency demands, so that the flywheel and lithium battery can coordinate and complement each other during the charging and discharging process, improving the overall frequency regulation performance of the system. Although the thermal energy storage synergy is achieved through the decomposition principle, it does not consider incorporating wind power into the frequency regulation system. "Qu Tong, Su Xiaolin, Yan Xiaoxia, et al. Wind, solar, energy storage and thermal joint frequency modulation strategy based on frequency division principle and regional control [J]. Electrical Measurement and Instrumentation, 2018, 55(20): 122-129+147" proposed a frequency modulation architecture with frequency division. By configuring a multi-time constant low-pass filter unit to separate the high, medium and low frequency components of the frequency deviation, the frequency band with the fastest changing rate is allocated to the energy storage system response, and the slowest frequency band is borne by the thermal power unit, thus realizing the joint frequency modulation of wind, solar, energy storage and thermal power. However, the literature focuses on optimizing the coordination mechanism of primary and secondary frequency modulation. In contrast, the study "Chen Peng, Wang Wei, Yang Jianqing, et al. Wind-fire-storage coordinated frequency regulation control strategy based on multi-scale decomposition [J]. Acta Energiae Solaris Sinica, 2024, 45(03): 428-435" uses wavelet packet decomposition to decompose the grid frequency deviation into three parts: high, medium, and low in the frequency domain based on the response characteristics of wind, fire, and storage. Energy storage, wind power, and thermal power reserve respond to the corresponding components, giving full play to the rapid response capabilities of wind power and energy storage, and the durability of thermal power output. However, the decomposition algorithm and process are relatively cumbersome, and real-time performance cannot be guaranteed. Therefore, a frequency regulation optimization control method that considers the coordination of wind, fire, and storage is needed to solve the above problems. Summary of the Invention

[0006] The purpose of the present invention is to propose a frequency regulation optimization control method considering the coordination of wind, thermal and storage, comprising the following steps:

[0007] Step 1. Establish wind power frequency regulation model, thermal power and grid frequency regulation model, and flywheel energy storage frequency regulation model in Matlab / Simulink;

[0008] Step 2. Design a first-order low-pass frequency filter to decompose the frequency signal into high-frequency and low-frequency signals, which are responded to by the flywheel energy storage and wind power respectively. Design a first-order filter for the thermal power primary frequency modulation signal to decompose the primary frequency modulation signal into high-frequency and low-frequency components. The high-frequency component is proportionally responded by the wind energy storage system as compensation for the respective frequency modulation instructions, and the low-frequency component is responded by the thermal power unit.

[0009] Step 3. Design a frequency modulation control strategy for wind power and a flywheel energy storage charge and discharge control strategy considering the state of charge (SOC);

[0010] Step 4. Set different scenarios and use evaluation indicators to analyze the frequency regulation effect and the performance of mitigating thermal power fluctuations.

[0011] Furthermore, the process of establishing the wind power frequency regulation model in step 1 includes:

[0012] According to aerodynamic theory, calculate the mechanical power captured by the doubly fed wind turbine from the air:

[0013]

[0014] Where: P m is the mechanical power, ρ is the air density, R is the fan radius; ν w is the ambient wind speed, C p (λ,β) is the wind energy utilization coefficient, is the tip speed ratio, β is the pitch angle, ω r is the rotor speed; C1~C6 represent the coefficients of the wind turbine;

[0015] The wind turbine operates in MPPT control mode, and the controller keeps the pitch angle β near 0 degrees without changing it. In this mode, the wind turbine speed is adjusted to ensure that C p Maximum optimal tip speed ratio λ opt :

[0016]

[0017] Where: P MPPT , K opt 、 Respectively represent the maximum output power, MPPT coefficient, and maximum wind energy utilization coefficient;

[0018] During frequency modulation, overspeed control is performed as follows:

[0019]

[0020] Where: P del ,d, and λ del They represent the load-reduced operating power, load-reduced rate, wind energy utilization coefficient in load-reduced mode, and tip speed ratio in load-reduced mode respectively;

[0021] Frequency regulation is performed using the following rotor motion equation:

[0022]

[0023] Where: P e Represents electromagnetic power, H w is the equivalent time constant of the fan;

[0024] The integrated inertia control enables the wind turbine to have inertia response and primary frequency regulation capabilities, and adds an additional power signal P to the active power reference of the wind turbine. add , expressed as:

[0025]

[0026] Where: f is the frequency, Δf is the frequency deviation, K p is the droop control coefficient, K d is the inertial response coefficient, P ref 、P ref,del It is divided into the power setting value of the fan electrical part in MPPT and overspeed load reduction mode; a is the reference value, ensuring that all variables are in the same order of magnitude;

[0027] Simplify the generator part into a first-order inertia link:

[0028]

[0029] Where: T a is the time constant of the inertia link, P e 、P e,del are the output electromagnetic power of the fan in MPPT and load reduction modes respectively.

[0030] Furthermore, the process of establishing the thermal power and grid frequency regulation model in step 1 includes:

[0031] The following steam turbine models are selected for simulated frequency regulation:

[0032]

[0033] Where: G en (s) is the transfer function of the steam turbine model; F LP 、F IP 、F HP is the power coefficient of the low, medium and high pressure cylinders of the turbine; T CO 、T RH 、T CH is the volume time constant of low-pressure steam, reheated steam and high-pressure steam; λ guo is the overshoot coefficient, usually taken as 0.8;

[0034] The speed governor of the thermal power unit is selected as:

[0035]

[0036] Where: T g is the time constant of the speed regulator;

[0037] The generator-load model is selected as:

[0038]

[0039] Where: H is the inertia constant; D is the load damping coefficient.

[0040] Furthermore, the flywheel energy storage frequency regulation model in step 1 is:

[0041]

[0042] Where: T E is the energy storage time constant, and the flywheel energy storage is taken as 0.02.

[0043] Furthermore, the state of charge calculation formula of the flywheel energy storage frequency modulation model is:

[0044]

[0045] Where: SOC0 is the initial value of the state of charge; P F is the real-time output power; E is the system power storage capacity; t is the time.

[0046] Furthermore, the power instructions responded by the thermal power unit and the wind energy storage system in step 2 are:

[0047]

[0048] Where: P G,ref P is the reference value of thermal power input; add is the additional power signal; P L 、P H are the low-frequency component and high-frequency component of the primary frequency modulation signal, P w,ref 、P w,ref,i are the reference values ​​of wind farm and wind turbine input power respectively; t is time; n is the number of wind turbines; P F,ref Input power reference value for battery energy storage; K p is the droop control coefficient, K d is the inertia response coefficient, K is the proportion of wind power in the high-frequency part of thermal power frequency regulation; Δf is the frequency deviation, are the power values ​​of wind farm and energy storage in response to frequency changes, respectively.

[0049] Furthermore, the flywheel energy storage charge and discharge control strategy considering the state of charge (SOC) in step 3 is as follows:

[0050] Δf H When ≤|0.033|Hz, the flywheel energy storage does not participate in the primary frequency modulation;

[0051] Δf H When <-0.033Hz, the actual output power value of flywheel energy storage is:

[0052]

[0053] Δf H When the frequency is greater than 0.033Hz and S≤0.6, the flywheel energy storage is charged according to the maximum input power;

[0054] Δf H When >0.033Hz and S>0.6, the flywheel energy storage output power value is:

[0055]

[0056] Where: K, P, P0, b, r are constants; P m,F is the flywheel mechanical power, P M is the rated power of the energy storage system; SOC max , SOC min Respectively represent the maximum and minimum state of charge values ​​of the energy storage system; P F,ref Input power reference value for battery energy storage; Δf H is the frequency deviation of the energy storage response after decomposition, P d is the flywheel energy storage output power; P dmax is the maximum output power of the flywheel energy storage; P c is the flywheel energy storage input power, P cmax The maximum input power of the flywheel energy storage.

[0057] The beneficial effects of the present invention are:

[0058] 1. The present invention plays a guiding role in maintaining frequency stability in new power systems with a high proportion of wind power penetration. It adopts a method of decomposing thermal power frequency regulation instructions and proportionally distributing high-frequency components as compensation for the reference power of the wind-storage system. This can effectively reduce unit output fluctuations, share the frequency regulation pressure for thermal power units, and facilitate safe and stable operation of the system. The frequency is decomposed into high- and low-frequency parts through a first-order low-pass filter, and the flywheel energy storage and wind power respond respectively, effectively simplifying the complexity of using wavelet packet decomposition.

[0059] 2. The wind-fire-storage coordinated frequency regulation optimization method proposed in the present invention does not require complex modeling and is easy to implement compared to intelligent algorithms such as model predictive control and reinforcement learning.

[0060] 3. The present invention proposes a frequency modulation control method combining low overspeed load reduction of wind power with SIC and energy storage considering SOC, which alleviates the secondary frequency drop that occurs in the rotor kinetic energy method, while avoiding the phenomenon of wind curtailment and mechanical wear under high-proportion load reduction, as well as the shortcomings of energy storage overcharging and discharging affecting the energy storage life. BRIEF DESCRIPTION OF THE DRAWINGS

[0061] Figure 1 This is a flow chart of the frequency regulation optimization control method considering the coordination of wind, thermal and storage in the present invention.

[0062] Figure 2 Frequency regulation optimization control block diagram for wind-thermal-storage collaboration.

[0063] Figure 3 This is the frequency deviation diagram under different control strategies for scenario 1.

[0064] Figure 4 This is the thermal power output diagram under different control strategies in scenario 1.

[0065] Figure 5 This is the frequency deviation diagram under different control strategies in scenario 2.

[0066] Figure 6 This is the thermal power output diagram under different control strategies in scenario 2. DETAILED DESCRIPTION

[0067] The present invention proposes a frequency regulation optimization control method considering the coordination of wind, thermal and storage. The present invention is further described below with reference to the accompanying drawings and specific embodiments.

[0068] Figure 1 This is a flow chart of the frequency regulation optimization control method considering wind, thermal and storage coordination in the present invention. Figure 2 This is a block diagram for optimizing the frequency regulation of wind-heat-storage coordination. The method includes the following steps:

[0069] Step 1. Establish wind power frequency regulation model, thermal power and grid frequency regulation model, and flywheel energy storage frequency regulation model in Matlab / Simulink;

[0070] 1. Establish a wind power frequency regulation model, as follows:

[0071] First, according to aerodynamic theory, the mechanical power captured by the doubly fed wind turbine from the air can be expressed as:

[0072]

[0073] Where: P m is the mechanical power, ρ is the air density, R is the fan radius; ν w is the ambient wind speed, C p (λ,β) is the wind energy utilization coefficient, is the tip speed ratio, β is the pitch angle, ω r is the rotor speed. C1 to C6 represent the coefficients of the wind turbine.

[0074] The wind turbine operates in MPPT control mode, and the controller keeps the pitch angle β near 0 degrees without changing. In this mode, by adjusting the wind turbine speed, there is a unique λ that makes C p Maximum, called the optimal tip speed ratio λ opt, as shown in formula (2).

[0075]

[0076] Where: P MPPT , K opt 、 Respectively represent the maximum output power, MPPT coefficient, and maximum wind energy utilization coefficient

[0077] Overspeed control is to move the fan operating point from the maximum power point to the right and run the rotor in overspeed mode, retaining some power and releasing it when frequency regulation is needed. The specific overspeed control is as follows:

[0078]

[0079] Where: P del ,d, and λ del They respectively represent the load-reduced operating power, load-reduced rate, wind energy utilization coefficient in load-reduced mode, and tip speed ratio in load-reduced mode.

[0080] Wind power participates in frequency regulation by utilizing rotor kinetic energy. The rotor motion equation is expressed as:

[0081]

[0082] Where: P e Represents electromagnetic power, H w is the equivalent time constant of the fan.

[0083] The integrated inertia control enables the wind turbine to have inertial response and primary frequency regulation capabilities. In fact, an additional power signal P is added to the active power reference of the wind turbine. add , expressed as:

[0084]

[0085] Where: f is the frequency, Δf is the frequency deviation (unit: Hz), K p is the droop control coefficient, K d is the inertial response coefficient, P ref 、P ref,del This is the power setting value for the fan electrical system in MPPT and overspeed load shedding modes. a is the baseline value, ensuring that all variables are within the same order of magnitude.

[0086] Since large wind turbines now all have active and reactive power decoupling control, when studying the active power control problem of wind farms, the generator part can be simplified to a first-order inertia link.

[0087]

[0088] Where: T a is the time constant of the inertia link, P e 、P e,del are the output electromagnetic power of the fan in MPPT and load reduction modes respectively.

[0089] It is worth noting that in order to maintain the same order of magnitude as the thermal storage frequency regulation model, the wind power model of this embodiment has an incremental power output of the wind farm, and the output is the result of per-unit processing.

[0090] 2. Establishing thermal power and grid frequency regulation models is as follows:

[0091] The modeling of thermal power units generally uses a reheat steam turbine to simulate the frequency modulation effect. The simplified steam turbine model can be expressed by the following transfer function:

[0092]

[0093] Where: G en (s) is the transfer function of the steam turbine model; F LP 、F IP 、F HP is the power coefficient of the low, medium and high pressure cylinders of the turbine; T CO 、T RH 、T CH is the volume time constant of low-pressure steam, reheated steam and high-pressure steam.

[0094] However, in actual application, since the high-pressure cylinder power will have an obvious overshoot phenomenon in the dynamic process, the turbine model of this embodiment adds an overshoot coefficient λ guo , the transfer function is shown in formula (8).

[0095]

[0096] Where: guo is the overshoot coefficient, usually taken as 0.8.

[0097] The speed governor of a thermal power unit is expressed as:

[0098]

[0099] Where: T g is the speed regulator time constant.

[0100] The generator-load model is expressed as:

[0101]

[0102] Where: H is the inertia constant; D is the load damping coefficient.

[0103] 3. The flywheel energy storage frequency regulation model is as follows:

[0104] The energy storage equivalent model uses the first-order inertia with higher accuracy, and the transfer function is expressed as:

[0105]

[0106] Where: T E is the energy storage time constant. In this embodiment, the flywheel energy storage is set to 0.02.

[0107] The state of charge module of the energy storage mainly monitors the output power of the flywheel energy storage in real time. The state of charge calculation formula is:

[0108]

[0109] Where: SOC0 is the initial value of the state of charge; P F is the real-time output power; E is the system power storage capacity.

[0110] Step 2. Design a first-order low-pass frequency filter to decompose the frequency signal into high-frequency and low-frequency signals, which are responded to by the flywheel energy storage and wind power respectively. Design a first-order filter for the thermal power primary frequency modulation signal to decompose the primary frequency modulation signal into high-frequency and low-frequency components. The high-frequency component is proportionally responded by the wind energy storage system as compensation for the respective frequency modulation instructions, and the low-frequency component is responded by the thermal power unit. The details are as follows:

[0111] Different power sources have different adaptability to frequency difference signals. Wind power generation boasts fast frequency modulation. Furthermore, the low-overspeed load shedding standby mode employed by this embodiment provides long-term frequency support, smoothing medium and low-frequency fluctuations within a certain range. Energy storage, on the other hand, offers fast response and adaptability to high-frequency frequency difference signals. Given these characteristics, this embodiment linearly decomposes the frequency deviation and processes it through a first-order low-pass filter to obtain the flywheel's high-frequency deviation and the low-frequency wind power frequency difference component, fully leveraging the advantages of frequency modulation for both energy sources.

[0112]

[0113] Where: T is the low-pass filter time constant.

[0114] At the same time, this embodiment decomposes the original frequency regulation instructions of the thermal power units, with the wind-storage system responding proportionally to the high-frequency signal and the thermal power units responding to the low-frequency signal, thereby establishing a coordinated control strategy for the wind-fire-storage combined system. This solution can effectively mitigate unit output fluctuations and quickly stabilize the grid frequency.

[0115] Primary frequency regulation instruction P of thermal power unit the for:

[0116] P the =-K g·Δf (14)

[0117] The original thermal power unit primary frequency modulation instruction P is converted into the The high- and low-frequency components are decomposed, with the thermal power unit bearing the low-frequency component and the high-frequency component being transferred to the wind-storage system. The transfer function F(s) of the low-pass filter is:

[0118]

[0119] Where: T is the low-pass filter time constant.

[0120] The relationship between the primary frequency modulation instruction, high frequency component, and low frequency component is:

[0121] P the =P H +P L (16)

[0122] After decomposition, the power instructions that the thermal power unit and wind storage system should respond to are:

[0123]

[0124] Where: P G,ref =P L P is the reference value of thermal power input; w,ref 、P w,ref,i are the reference values ​​of input power of wind farm and wind turbine i respectively; P F,ref is the reference value of battery energy storage input power; K is the proportion of wind power in the designated high-frequency part of thermal power frequency regulation; are the power values ​​of wind farm and energy storage in response to frequency changes, respectively.

[0125] Step 3. Design a frequency modulation control strategy for wind power and a flywheel energy storage charge and discharge control strategy considering the state of charge (SOC). The details are as follows:

[0126] The integrated inertia control (SIC) of wind turbines can increase the lowest frequency point by immediately releasing the kinetic energy stored in the rotating mass. However, SIC may reduce the stable frequency to below the maximum steady-state frequency deviation. This embodiment proposes a closed-loop SIC scheme for wind turbines, which, combined with low overspeed load reduction operations, can increase the lowest frequency point and the stable frequency. At the same time, coordination with thermal storage is fully achieved. The power of a single wind turbine under frequency regulation can be obtained from equations (1 to 6), and the reference power of the entire wind farm can be obtained from equations (17 to 18).

[0127] According to formula (12), the output power of the flywheel energy storage system is integrated over time to obtain the real-time state of charge (SOC) of the energy storage system, which is used as a feedback signal to control the power of the flywheel energy storage system through the Logistic regression function.

[0128] Discharge power:

[0129]

[0130] Charging power:

[0131]

[0132] Where: K, P, P0, b, r are constants; P M is the rated power of the energy storage system; SOC max , SOC min They represent the maximum and minimum state of charge values ​​of the energy storage system respectively.

[0133] The flywheel energy storage control method is virtual droop control:

[0134]

[0135] According to the energy storage participating in the grid frequency regulation, the dead band is set to 0.033Hz to limit the flywheel action to prevent the flywheel system from frequent charging and discharging. Flywheel energy storage system control strategy.

[0136] 1)Δf H ≤|0.033|Hz, flywheel energy storage does not participate in primary frequency regulation.

[0137] 2)Δf H When <-0.033Hz, the actual output power value of flywheel energy storage is:

[0138]

[0139] 3)Δf H When the frequency is greater than 0.033 Hz and S is less than or equal to 0.6, the flywheel energy storage is charged at the maximum input power.

[0140] 4)Δf H When >0.033Hz and S>0.6, the flywheel energy storage output power value is:

[0141]

[0142] Where: K, P, P0, b, r are constants; P m,F is the flywheel mechanical power, P M is the rated power of the energy storage system; SOC max , SOC min Respectively represent the maximum and minimum state of charge values ​​of the energy storage system; PF,ref Input power reference value for battery energy storage; Δf H is the frequency deviation of the energy storage response after decomposition, P d is the flywheel energy storage output power; P dmax is the maximum output power of the flywheel energy storage; P c is the flywheel energy storage input power, P cmax The maximum input power of the flywheel energy storage.

[0143] Step 4. Set up different scenarios and use evaluation indicators to analyze the frequency regulation effect and the performance of mitigating thermal power fluctuations. The details are as follows:

[0144] In design scenario 1, under the same step disturbance, we compare frequency regulation using thermal power alone (Strategy 1), combined frequency regulation using thermal power and energy storage (Strategy 2), combined frequency regulation using wind and thermal power (Strategy 3), and the strategy of this embodiment (Strategy 4). We compare the proposed method with traditional methods in terms of frequency regulation and mitigation of thermal power fluctuations.

[0145] In scenario 1, a step disturbance of ΔP = -0.20 pu is applied at t = 102s to simulate a sudden load increase. The strategy of this embodiment (Strategy 4) is compared with the frequency regulation of thermal power alone (Strategy 1), the combined frequency regulation of thermal power and energy storage (Strategy 2), and the combined frequency regulation of wind and thermal power (Strategy 3). As shown in Table 1, the proposed strategy has the largest frequency minimum point and can effectively reduce the system frequency deviation. Figure 3 Frequency deviation under different control strategies in scenario 1; at the same time, Figure 4 It can be seen that the output growth trend of thermal power units has shown a slowing trend. The frequency regulation of thermal power units can effectively reduce the unit output fluctuation and improve the frequency regulation performance.

[0146] Table 1 Comparison of frequency modulation effects under different control strategies in scenario 1

[0147]

[0148] In design scenario 2, under the same step disturbance, the installed capacity of the wind farm is varied to compare frequency regulation using thermal power alone (Strategy 1), combined frequency regulation using thermal power and energy storage (Strategy 2), combined frequency regulation using wind and thermal power (Strategy 3), and the strategy of this embodiment (Strategy 4). The proposed method is compared with traditional methods in terms of frequency regulation and mitigation of thermal power fluctuations.

[0149] In scenario 2, based on the step disturbance of ΔP = -0.15 pu applied at t = 102 s, the installed capacity of the wind farm is changed from 120 MW to 90 MW, simulating scenarios with different wind power penetration rates. The strategy of this embodiment (strategy 4) is compared with the frequency regulation of thermal power alone (strategy 1), the frequency regulation of thermal power and energy storage (strategy 2), and the frequency regulation of wind and thermal power (strategy 3). According to Table 2 and Figure 5 、 Figure 6It can be seen that the strategy proposed in this embodiment still performs outstandingly in terms of frequency modulation effect and maintaining system stability.

[0150] Table 2 Comparison of frequency modulation effects under different control strategies in scenario 2

[0151]

[0152] In summary, the proposed frequency regulation optimization method for the coordination of wind, thermal and storage can effectively explore the frequency regulation capabilities of different power sources, effectively share the frequency regulation pressure of thermal power, and provide a new idea for the cooperation of multiple forms of power sources in the frequency regulation task of the new power system. Compared with the traditional frequency regulation control method, the present invention has a guiding role in maintaining the frequency stability of the new power system with a high proportion of wind power penetration; the method of decomposing the thermal power frequency regulation instruction and proportionally distributing the high-frequency part as the compensation for the reference power of the wind storage system can effectively reduce the unit output fluctuation and improve the frequency regulation performance. Compared with intelligent algorithms such as model predictive control and reinforcement learning, the present invention does not require complex modeling and is relatively easy to implement. The frequency regulation control method of combining wind power low overspeed load reduction with SIC and energy storage considering SOC proposed by the present invention takes into account the shortcomings of wind farm abandonment and mechanical wear caused by conventional load reduction and the impact of excessive charge and discharge of energy storage on energy storage life.

Claims

1. A frequency regulation optimization control method considering wind, thermal and storage synergy, characterized in that: The following steps are involved: Step 1. Establish wind power frequency regulation model, thermal power and grid frequency regulation model, and flywheel energy storage frequency regulation model in Matlab / Simulink; Step 2. Design a first-order low-pass frequency filter to decompose the frequency signal into high-frequency and low-frequency signals, which are responded to by the flywheel energy storage and wind power respectively. Design a first-order filter for the thermal power primary frequency modulation signal to decompose the primary frequency modulation signal into high-frequency and low-frequency components. The high-frequency component is proportionally responded by the wind energy storage system as compensation for the respective frequency modulation instructions, and the low-frequency component is responded by the thermal power unit. Step 3. Design a frequency modulation control strategy for wind power and a flywheel energy storage charge and discharge control strategy considering the state of charge (SOC); Step 4. Set different scenarios and use evaluation indicators to analyze the frequency regulation effect and the performance of mitigating thermal power fluctuations.

2. The frequency regulation optimization control method considering wind, thermal and storage synergy according to claim 1 is characterized in that: The process of establishing the wind power frequency regulation model in step 1 includes: According to aerodynamic theory, calculate the mechanical power captured by the doubly fed wind turbine from the air: Where: P m is the mechanical power, ρ is the air density, R is the fan radius; ν w is the ambient wind speed, C p (λ,β) is the wind energy utilization coefficient, is the tip speed ratio, β is the pitch angle, ω r is the rotor speed; C1~C6 represent the coefficients of the wind turbine; The wind turbine operates in MPPT control mode, and the controller keeps the pitch angle β near 0 degrees without changing it. In this mode, the wind turbine speed is adjusted to ensure that C p Maximum optimal tip speed ratio λ opt : Where: P MPPT , K opt 、 Respectively represent the maximum output power, MPPT coefficient, and maximum wind energy utilization coefficient; During frequency modulation, overspeed control is performed as follows: Where: P del ,d, and λ del They represent the load-reduced operating power, load-reduced rate, wind energy utilization coefficient in load-reduced mode, and tip speed ratio in load-reduced mode respectively; Frequency regulation is performed using the following rotor motion equation: Where: P e Represents electromagnetic power, H w is the equivalent time constant of the fan; The integrated inertia control enables the wind turbine to have inertia response and primary frequency regulation capabilities, and adds an additional power signal P to the active power reference of the wind turbine. add , expressed as: Where: f is the frequency, Δf is the frequency deviation, K p is the droop control coefficient, K d is the inertial response coefficient, P ref 、P ref,del It is divided into the power setting value of the fan electrical part in MPPT and overspeed load reduction mode; a is the reference value, ensuring that all variables are in the same order of magnitude; Simplify the generator part into a first-order inertia link: Where: T a is the time constant of the inertia link, P e 、P e,del are the output electromagnetic power of the fan in MPPT and load reduction modes respectively.

3. The frequency regulation optimization control method considering wind, thermal and storage synergy according to claim 1 or 2 is characterized in that: The process of establishing the thermal power and grid frequency regulation model in step 1 includes: The following steam turbine models are selected for simulated frequency regulation: Where: G en (s) is the transfer function of the steam turbine model; F LP 、F IP 、F HP is the power coefficient of the low, medium and high pressure cylinders of the turbine; T CO 、T RH 、T CH is the volume time constant of low-pressure steam, reheated steam and high-pressure steam; λ guo is the overshoot coefficient, usually taken as 0.8; The speed regulator of the thermal power unit is selected as: Where: T g is the speed regulator time constant; The generator-load model is selected as: Where: H is the inertia constant; D is the load damping coefficient.

4. The frequency regulation optimization control method considering wind, thermal and storage synergy according to claim 3 is characterized in that: The flywheel energy storage frequency modulation model in step 1 is: Where: T E is the energy storage time constant, and the flywheel energy storage is taken as 0.

02.

5. The frequency regulation optimization control method considering wind, thermal and storage synergy according to claim 4 is characterized in that: The state of charge calculation formula of the flywheel energy storage frequency modulation model is: Where: SOC0 is the initial value of the state of charge; P F is the real-time output power; E is the system power storage capacity; t is the time.

6. The frequency regulation optimization control method considering wind, thermal and storage synergy according to claim 1 is characterized in that: The power instructions responded by the thermal power generation unit and the wind energy storage system in step 2 are: Where: P G,ref P is the reference value of thermal power input; add is the additional power signal; P L 、P H are the low-frequency component and high-frequency component of the primary frequency modulation signal, P w,ref 、P w,ref,i are the reference values ​​of wind farm and wind turbine input power respectively; t is time; n is the number of wind turbines; P F,ref Input power reference value for battery energy storage; K p is the droop control coefficient, K d is the inertia response coefficient, K is the proportion of wind power in the high-frequency part of thermal power frequency regulation; Δf is the frequency deviation, are the power values ​​of wind farm and energy storage in response to frequency changes, respectively.

7. The frequency regulation optimization control method considering wind, thermal and storage synergy according to claim 1 or 6 is characterized in that: The flywheel energy storage charge and discharge control strategy considering the state of charge (SOC) in step 3 is as follows: Δf H When ≤|0.033|Hz, the flywheel energy storage does not participate in the primary frequency modulation; Δf H When <-0.033Hz, the actual output power value of flywheel energy storage is: Δf H When the frequency is greater than 0.033Hz and S≤0.6, the flywheel energy storage is charged according to the maximum input power; Δf H When >0.033Hz and S>0.6, the flywheel energy storage output power value is: Where: K, P, P0, b, r are constants; P m,F is the flywheel mechanical power, P M is the rated power of the energy storage system; SOC max , SOC min Respectively represent the maximum and minimum state of charge values ​​of the energy storage system; P F,ref Input power reference value for battery energy storage; Δf H is the frequency deviation of the energy storage response after decomposition, P d is the flywheel energy storage output power; P dmax is the maximum output power of the flywheel energy storage; P c is the flywheel energy storage input power, P cmax The maximum input power of the flywheel energy storage.

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