Self-Adaptive Secondary Frequency Regulation Strategy Based on Distributed Model Predictive Control

doi:10.16183/j.cnki.jsjtu.2023.352

Abstract

Abstract:

To address the issues of reduced adaptability of secondary frequency regulation caused by changes in power system parameters, a self-adaptive secondary frequency regulation strategy based on distributed model predictive control (DMPC) is proposed. First, a model of a multi-area interconnected power system is built. Based on the frequency response trajectory, a parameter identification model for each area of the system is established. Then, the recursive least square method is used to solve the parameter identification model and update the parameters of each area online. Additionally, with the objective to minimize the area control error (ACE), DMPC is adopted to optimize the power of generators for secondary frequency regulation. Finally, a case study is conducted to demonstrate the effectiveness of the proposed strategy.

Key words: distributed model predictive control (DMPC), secondary frequency regulation, parameter identification, area control error (ACE), optimized decision-making

CLC Number:

TM715

CAO Yongji, ZHANG Jiangfeng, WANG Tianyu, ZHENG Keke, WU Qiuwei. Self-Adaptive Secondary Frequency Regulation Strategy Based on Distributed Model Predictive Control[J]. Journal of Shanghai Jiao Tong University, 2025, 59(3): 333-341.

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方法	频率最大偏差/Hz	频率偏差均方根/Hz	ACE最大偏差(p.u.)	ACE均方根(p.u.)
方法1	-0.1319	0.0424	-0.0887	0.0273
方法2	-0.0919	0.0279	-0.0626	0.0198
方法3	0.0580	0.0168	-0.0423	0.0115
所提方法	0.0580	0.0168	-0.0423	0.0115

方法	频率最大偏差/Hz	频率偏差均方根/Hz	ACE最大偏差(p.u.)	ACE均方根(p.u.)
方法1	-0.1319	0.0441	-0.0887	0.0284
方法2	-0.1043	0.0303	-0.0716	0.0215
方法3	-0.0882	0.0233	-0.0651	0.0160
所提方法	-0.0713	0.0192	-0.0524	0.0132