Open AccessDistributed event‐triggered robust automatic generation control for networked power system with wind turbines
Author(s) -
Huo Zhihong
Publication year - 2021
Publication title -
iet renewable power generation
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.005
H-Index - 76
eISSN - 1752-1424
pISSN - 1752-1416
DOI - 10.1049/rpg2.12036
Subject(s) - networked control system , control theory (sociology) , electric power system , computer science , wind power , linear matrix inequality , control engineering , control system , distributed control system , scheme (mathematics) , stability (learning theory) , power control , robust control , distributed power , power (physics) , control (management) , engineering , mathematical optimization , mathematics , mathematical analysis , physics , quantum mechanics , artificial intelligence , machine learning , electrical engineering
This paper proposes an event‐triggered distributed networked control scheme and its robust stability analysis strategy for the automatic generation control of multi‐area interconnected power system with wind turbines. First, for the large‐scale distributed networked control systems, considering the networked control systems with parameters uncertainty, effective transmission bandwidth, and time‐varying networked‐induced delays, a new distributed networked control systems model is proposed. Then, by constructing Lyapunov–Krasovskii functional method, the sufficient conditions for asymptotical stability of the system are obtained, a design method of event‐triggered distributed networked control law based on linear matrix inequality is proposed. In order to verify the effectiveness of the proposed scheme, a multi‐area power system with wind turbines is considered, and the system performance under different load disturbances is simulated. The simulation results show that the scheme has reliable robust performance for multi‐area distributed networked power system and improves the anti‐interference ability of the power system.