Optimization of a small passive wind turbine generator with multiobjective genetic algorithms

Abstract

In this paper Multiobjective Genetic Algorithms (MOGAs) are used for the design of a small wind turbine generator (WTG) coupled to a DC bus through a diode bridge. The originality of the considered system resides in the suppression of the Maximum Power Point Tracker (MPPT). The poor efficiency of the corresponding passive structure is considerably improved by optimizing the generator characteristics associated with the wind turbine in relation to the wind cycle. The optimized configurations are capable of matching very closely the behavior of active wind turbine systems which operate at optimal wind powers by using a MPPT control device.

Thermal modeling of permanent magnet motor with finite element method

“…Thermal radiation is a transfer mode can influence in the case of motors studied, in this paper investigate only heat transfer by conduction and convection [4]- [5].…”

Optimization of power and its variability with an artificial immune network algorithm

“…Boukhezzar et al [4] designed a non-linear controller for optimizing the power of the DFIG (Doubly Fed Induction Generator). Abdelli et al [5] applied a multi-objective genetic algorithm to optimize the efficiency of a small-scale turbine. Muljadi et al [6] addressed operating a variable-speed wind turbine with pitch control to maximize power while minimizing the loads.…”

Diagnosis & fault detection in wind energy conversion system

“…There are two classes: analytical and numerical models [5]. The modeling steps and different models of the WT are detailed in [6].…”

“…WT used for electricity generation should produce a maximum power by making the best use of available energy in the wind. For this reason, many control laws, for mechanical and electrical parts, have been developed to maximize this energy conversion [5]. A fault tolerant control approach, in multi-model, was developed in [9].…”