Design and Study on Sliding Mode Extremum Seeking Control of the Chaos Embedded Particle Swarm Optimization for Maximum Power Point Tracking in Wind Power Systems

Jui-Ho Chen, Her-Terng Yau and Weir Hung
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Jui-Ho Chen: Department of Electrical Engineering, National Chin-Yi University of Technology, Taichung 41170, Taiwan
Her-Terng Yau: Department of Electrical Engineering, National Chin-Yi University of Technology, Taichung 41170, Taiwan
Weir Hung: Department of Electrical Engineering, National Chin-Yi University of Technology, Taichung 41170, Taiwan

Energies, 2014, vol. 7, issue 3, 1-15

Abstract: This paper proposes a sliding mode extremum seeking control (SMESC) of chaos embedded particle swarm optimization (CEPSO) Algorithm, applied to the design of maximum power point tracking in wind power systems. Its features are that the control parameters in SMESC are optimized by CEPSO, making it unnecessary to change the output power of different wind turbines, the designed in-repetition rate is reduced, and the system control efficiency is increased. The wind power system control is designed by simulation, in comparison with the traditional wind power control method, and the simulated dynamic response obtained by the SMESC algorithm proposed in this paper is better than the traditional hill-climbing search (HCS) and extremum seeking control (ESC) algorithms in the transient or steady states, validating the advantages and practicability of the method proposed in this paper.

Keywords: extremum seeking control (ESC); sliding mode extremum seeking control (SMESC); maximum power point tracking (MPPT); particle swarm optimization (PSO); chaos; wind power (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2014
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (4)

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