考虑抑制二次跌落的风电自适应频率支撑控制策略及其参数整定

doi:10.19595/j.cnki.1000-6753.tces.250393

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摘要

风电随风资源的起伏致使其在不同场景下对系统的频率支撑能力有所差异,而风电的频率支撑能力、控制策略及控制参数的不匹配将严重影响系统频率的动态响应。为提升风电参与频率支撑时的稳定性与持续性,本文提出一种考虑转速平滑恢复的风机频率支撑控制策略,使风机在系统频率到达最低点之后自适应减小有功输出使其进入转速恢复状态,同时根据转速恢复情况自适应减小频率支撑控制参数,抑制了转速恢复对系统频率的不利影响。再依据风机参与频率支撑期间的运行点偏移求得不同转速下风机的最小动能损耗,进而求出风机的最大频率支撑能量;然后推导出了计及同步机与风电参与频率支撑的系统频率动态响应模型的时域表达式,统一了不同阻尼比下的频率极值点计算式;随后,基于系统频率安全约束与风机频率支撑能量约束,建立了分别以风机频率支撑量和风机偏移量最小为目标的优化模型,实现了故障场景下各风电场控制参数的整定。最后通过IEEE 30节点系统和实际电网的仿真算例验证了所提方法的有效性。

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关键词 ：风电场, 频率支撑控制, 参数整定, 转速恢复, 二次跌落

Abstract：

Wind power exhibits varying frequency support capabilities for power systems under different wind speed scenarios. The kinetic energy available for frequency support from wind power, along with the alignment of the control strategy and its parameters, significantly impacts the system frequency dynamic. For wind turbines utilizing rotor energy control, the effectiveness of the power feedback loop in responding to changes in system frequency is influenced by the magnitude of the virtual inertia and droop control parameters. If these control parameters are set too low, wind turbines will have a minimal impact on supporting system frequency. Conversely, if parameters are set too high, wind turbines may trigger speed protection due to a rapid decrease in rotational speed during the primary frequency regulation period, ultimately leading to a secondary drop in system frequency. To enhance the stability and sustainability of wind power participation in frequency support, this paper proposed a control strategy and parameter configuration method that emphasizes smooth speed recovery for wind turbines.
Firstly, after the system frequency reaches its nadir, wind turbines adaptively reduce their active output to enter a speed recovery state. Concurrently, frequency support control parameters are adjusted based on the state of speed recovery to mitigate any adverse effects on the system frequency. By analyzing the deviation from the initial operating point during the frequency support period of wind turbines, the minimum kinetic energy loss at different speeds is calculated, determining the maximum frequency support energy available. Next, the time-domain expression for the system frequency response model is derived, incorporating the contributions of synchronous generators and wind power in frequency support, and unifying the calculation formula for frequency extreme points across varying damping ratios. Following this, optimization models are established based on frequency security constraints and wind turbine frequency support energy constraints. These models aim to minimize both the frequency support from wind turbines and the deviations from initial operating points, thereby facilitating the configuration of control parameters for each wind farm during fault scenarios. Finally, the effectiveness of the proposed method is validated through simulations involving the IEEE 30-bus system and an actual power grid.
From the simulation analysis, the following conclusions can be drawn: (1) The all-damping SFR model proposed in this paper exhibits minimal calculation errors for the maximum frequency deviation in both over-damping and under-damping conditions, with the frequency dynamics following disturbances aligning closely with actual engineering outcomes. (2) The control strategy presented herein disables MPPT control during the initial phase of frequency support, allowing wind farms to provide sufficient assistance to the system frequency. Once the system frequency reaches its nadir, the output from wind farms is adaptively reduced, enabling wind turbines to transition into a speed recovery state. As turbine speeds enter the recovery phase, the frequency support control parameters are gradually decreased, preventing abrupt power changes and significant secondary drops. (3) The parameter optimization model takes into account the available kinetic energy of wind turbines and the rate of change of frequency. The first stage of the optimization model prioritizes frequency support from wind turbines as the objective function, while the second stage aims to minimize deviations from the initial positions of the turbines. This approach mitigates the impact of operating point deviations for each wind farm, thereby enhancing overall system frequency performance.

Key words： Wind farm frequency support control parameter configuration speed recovery secondary drop

PACS:

TM712

通讯作者: 文云峰男,1986年生,教授,博士生导师,研究方向为低惯量电力系统规划、运行与控制。E-mail：yunfeng.868l@163.com

作者简介: 张超男,1994年生,博士研究生,研究方向为新能源主动支撑能力需求评估。E-mail：chaozhang94@126.com

引用本文:

张超, 文云峰, 黎婧娴, 廖帮昆, 孙铭锐. 考虑抑制二次跌落的风电自适应频率支撑控制策略及其参数整定[J]. 电工技术学报, 0, (): 20250393-20250393. Zhang Chao, Wen Yunfeng, Li Jingxian, Liao Bangkun, Sun Mingrui. An adaptive frequency support control strategy and parameter configuration method of wind power considering the mitigation secondary drop. Transactions of China Electrotechnical Society, 0, (): 20250393-20250393.

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