Open AccessStability analysis and control optimisation based on particle swarm algorithm of modular multilevel matrix converter in fractional frequency transmission system
Author(s) -
Meng Yongqing,
Li Sijia,
Zou Yichao,
Li Kaikai,
Wang Xiuli,
Wang Xifan
Publication year - 2020
Publication title -
iet generation, transmission and distribution
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.92
H-Index - 110
eISSN - 1751-8695
pISSN - 1751-8687
DOI - 10.1049/iet-gtd.2019.1620
Subject(s) - particle swarm optimization , control theory (sociology) , modular design , decoupling (probability) , matlab , transmission system , computer science , controller (irrigation) , stability (learning theory) , electric power system , algorithm , transmission (telecommunications) , control engineering , engineering , power (physics) , control (management) , telecommunications , artificial intelligence , machine learning , operating system , agronomy , physics , quantum mechanics , biology
Modular multilevel matrix converter (M3C) is a competitive option in the fractional frequency transmission system (FFTS) application. Focusing on stability and power quality issues, this study firstly proposes a new mathematical model and control strategy. Different from the previous research, this control scheme is based on the frequency decoupling model of double dq coordinate transformation and the control of the sub‐converter, which implements the frequency decoupling control and solves the frequency leakage problem. Subsequently, a complete state‐space model and small‐signal model of M3C are built for analysing small disturbance stability. On this basis, the optimisation of M3C in FFTS is studied, and an optimisation method based on particle swarm algorithm is proposed. This method can directly design the adaptive objective function according to the optimisation requirements of system control performance to simultaneously optimise all controller parameters of the system. After optimisation, the stability and dynamic performance of the system have been significantly improved. Finally, the effectiveness of the proposed control and optimisation is verified by the simulation results in MATLAB/ Simulink.