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1. 清华大学电机工程与应用电子技术系,北京市 100084
2. 电力系统及发电设备控制和仿真国家重点实验室,清华大学,北京市 100084
3. 云南电网有限责任公司电力调度控制中心,云南省昆明市 650011
Received:03 August 2019,
Revised:2019-12-12,
Published Online:26 February 2020,
Published:10 April 2020
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李青兰,吴琛,陈磊等.抑制频率振荡的电力系统稳定器参数优化[J].电力系统自动化,2020,44(7):93-99.
LI Qinglan,WU Chen,CHEN Lei,et al.Parameter Optimization of Power System Stabilizer for Suppressing Frequency Oscillation[J].Automation of Electric Power Systems,2020,44(7):93-99.
李青兰,吴琛,陈磊等.抑制频率振荡的电力系统稳定器参数优化[J].电力系统自动化,2020,44(7):93-99. DOI: 10.7500/AEPS20190803005.
LI Qinglan,WU Chen,CHEN Lei,et al.Parameter Optimization of Power System Stabilizer for Suppressing Frequency Oscillation[J].Automation of Electric Power Systems,2020,44(7):93-99. DOI: 10.7500/AEPS20190803005.
超低频频率振荡是有功频率控制过程的小扰动稳定问题。由于负荷电压调节效应使得无功电压控制和有功频率控制产生耦合,传统用于抑制低频振荡的电力系统稳定器(PSS)可用于抑制频率振荡。提出了在多机系统中选择抑制频率振荡的PSS的方法,该方法综合了PSS对低频振荡和频率振荡的影响大小。构建了抑制频率振荡的PSS参数优化模型,该模型仍然以低频振荡模式阻尼比作为优化目标,但加入频率振荡对应频段发电机励磁系统相位要求作为约束,保证机组励磁系统为频率振荡提供足够的正阻尼。采用粒子群优化算法对模型进行求解得到PSS最优参数。仿真结果验证了所提方法的有效性。
Ultra-low frequency oscillation is a small disturbance stability problem in the active frequency control process. Power system stabilizer (PSS)
which is traditionally used to suppress low frequency oscillations
can also be used to suppress frequency oscillations due to load voltage regulation effects that cause the coupling of reactive voltage control and active frequency control. A method for selecting the PSS which can suppress frequency oscillations in a multi-machine system is proposed. This method combines the effects of PSS on low-frequency oscillation and frequency oscillation. A PSS parameter optimization model considering frequency oscillation suppression is constructed. The model still uses the damping ratio of the low-frequency oscillation mode as the optimization target
but adds the phase requirement of the generator excitation system in the corresponding band of the frequency oscillation as a constraint to ensure that the unit excitation system provides sufficient positive damping for the frequency oscillation. The particle swarm optimization algorithm is used to solve the model to obtain PSS optimization parameters. The effectiveness of the proposed method is verified by the simulation results.
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