Open AccessMaximum power extraction from a switched reluctance generator based wind power generating system using optimization techniques
Author(s) -
Mapa Swagata,
Gurumoorthy Bhuvaneswari
Publication year - 2022
Publication title -
engineering reports
Language(s) - English
Resource type - Journals
ISSN - 2577-8196
DOI - 10.1002/eng2.12457
Subject(s) - particle swarm optimization , switched reluctance motor , power (physics) , control theory (sociology) , wind power , computer science , generator (circuit theory) , matlab , maximum power principle , control engineering , engineering , algorithm , control (management) , rotor (electric) , mechanical engineering , artificial intelligence , electrical engineering , physics , quantum mechanics , operating system
This article advocates the use of two different optimization techniques, namely, gravitational search algorithm (GSA) and particle swarm optimization (PSO), to obtain suitable combinations of firing angles for the asymmetric half bridge converter (AHBC) to ensure optimum power extraction from a switched reluctance generator (SRG) based wind power generating system, at any given wind speed. As optimum power generation from an SRG turns out to be a multi‐dimensional search problem due to the nonlinear magnetic behavior of the machine, optimization techniques can be aptly employed for obtaining suitable values of control parameters. The techniques considered in this work, GSA and PSO, do not require any information about the geometrical features of the machine. Both techniques are implemented with an outer power control loop to propel the machine to perform optimally at variable wind speeds. Simulated results obtained by modeling these techniques in MATLAB environment are validated with the experimental results from a laboratory prototype consisting of a 1 hp, 2000 rpm, 8/6 SRM, and an AHBC. The results presented bring out the relative merits and demerits of the optimization techniques, thus highlighting their suitability for actual field implementation.