Circulating current control of modular multilevel converter by wild spider foraging optimization based fractional order proportional integral derivative controller

被引:3
|
作者
Balamurugan, S. [1 ]
Nageswari, S. [1 ]
机构
[1] Alagappa Chettiar Govt Coll Engn & Technol, Dept Elect & Elect Engn, Karaikkudi, Tamil Nadu, India
关键词
Modular multilevel converter; wild spider foraging optimization; circulating current; total harmonic distortion; VOLTAGE BALANCING ALGORITHM; FOPID CONTROLLERS; SUPPRESSION; SYSTEMS; PSO;
D O I
10.3233/JIFS-210528
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Modular Multilevel Converter (MMC) plays a vital role in high voltage industries because of its high rating power conversion. Due to its usage in high voltage rating power conversion and switched capacitor usage in MMC structure, there arises a problem of unbalanced capacitor voltage, which causes circulating current and disturbance in output current regulation. To manage these problematic parameters, a FOPID (Fractional Order Proportional Integral Derivative) controller has been utilized, due to its dynamic tracking and fast response. Secondly, the gain values of FOPID are not efficient, and they are optimized for each control group at all times of MMC working conditions. To provide a dynamic gain value by considering the dynamic change of error tracking parameters, Wild Spider Foraging Optimization (WSFO) algorithm has been developed based on the foraging behaviour of wild spider searching food (gain values) in view of changing the error of tracking parameters. The proposed algorithm has been evaluated in MATLAB Simulink by modeling the MMC structure with FOPID controller. The parameters of FOPID are optimized by bio-inspired algorithms like WSFO, Artificial Bee Colony (ABC) and Particle Swarm Optimization (PSO). The outcomes of the proposed WSFO-FOPID provide minimum circulating current and effectively balance the capacitor voltage in MMC. When the effectiveness of the results has been verified with the existing ABC and PSO optimization approaches, the proposed algorithm outperforms.
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页码:4127 / 4147
页数:21
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