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

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.