Open AccessDifferential evolution method‐based output power optimisation of switched reluctance generator for wind turbine applications
Author(s) -
Yahia Hedi,
Liouane Noureddine,
Dhifaoui Rachid
Publication year - 2014
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/iet-rpg.2013.0179
Subject(s) - switched reluctance motor , wind power , generator (circuit theory) , control theory (sociology) , turbine , computer science , automotive engineering , power (physics) , control engineering , electrical engineering , engineering , physics , aerospace engineering , rotor (electric) , control (management) , quantum mechanics , artificial intelligence
The use of wind energy for electric power generation provides a clean and renewable source. Therefore there is an increasing interest in developing and exploiting natural energy generation system. Switched reluctance generators (SRGs) have the potential to be a robust and highly efficient electrical conversion system for variable‐speed wind applications. This study presents a new approach for optimising performance of a SRG intended for variable‐speed direct drive wind turbine applications. DC bus voltage level and phase voltage switching angles have been identified as control variables affecting power generation. Owing to highly non‐linear characteristics of SRG, iterative simulation of the generator model on the range of control variables can be used for finding output power profile. Since it is a multidimensional search space, the number of iterations is very big. Differential evolution (DE) strategy has been introduced to find optimal firing angles and DC bus voltage level under multiple operating conditions. Optimisation of the control variables is performed using a machine model based on the measured characteristics. Selected operating points are experimentally tested using a 4 kW 1500 rpm SRG prototype. DE algorithm is a viable alternative for generating optimal control in multidimensional optimisation of SRG wind energy generation.