Optimized Hybrid Fuel Cell-Wind Power System with Economic Power Control

Abstract

This project introduces an intelligent extraction of optimum power and its dispatch by using Ant colony algorithm (ACO) from a grid tied hybrid generation system comprising of a permanent magnet synchronous generator based fuel cell, wind turbine. For fuel cell, maximum power point tracking control is implemented using ACO logic under varying solar irradiance. Power extracted from wind turbine is designed as an ACO function of the dc link voltage error, its rate of change and error in the direct axis current of the inverter. This reduces high frequency oscillations in the wind extracted power. Such an extraction is considered as a novelty of this paper. A failure mode and effect analysis is done for power converters and possible mitigation schemes are suggested for different faults. A,1:1 delta wye-grounded transformer is used at the inverter output to eliminate the triplet harmonics. Further, dynamic performances of both ACO proportional-derivative and integral (PD+I) controller and classical proportional integral (ACO) controller, to control the inverter currents, are compared. The proposed method results in an enhanced power dispatch and improvement in distortions and oscillations in the converter currents. This also reduces the probability of failures in the converter switches and other passive components.