Design and analysis of stand alone Hybrid renewable energy systems Using multi objective evolutionary Algorithms

Abstract

Global depletion in fossil fuels necessitates countries to reduce their newlinereliance on non-renewable energy sources. Extensive utilization of the boundless newlinepotential of Renewable Energy (RE) sources helps to meet the world s soaring newlineenergy demands. However, the intermittent nature of renewable energy sources newlineis the primary impediment to their widespread adoption. Regular use of energy newlinestorage devices and conventional generators enhances the reliability and the newlinequality of the power produced by RE systems. Distributed generation, on the newlineother hand, can notably widen the reliability by exploiting two or more RE newlinesources. newlineWith the increasing hazard to the environment and progressions in newlinerenewable energy technologies, Hybrid Renewable Energy Systems (HRES) can newlinemeet the energy demand. The addition of battery banks to the hybrid systems newlineincreases its dependability. However, blending two or more distinct resources newlinesurges the complexity of hybrid systems. Alarming environmental concerns newlinemake renewable energy systems design and functionality more challenging to newlineminimize the cost and the environmental burdens without shattering the energy newlinedemand. Also, minimization of cost and environmental issues is usually newlineconflicting in nature. Employing multi-objective optimization methods reduces newlinethe complexity of such problems to discover the optimal solution. newlineWith the availability of satisfactory profusion of software for the newlinedesign and analysis of Renewable Energy System (RES), this research utilizes newlinethe versatile potential of improved Hybrid Optimization using Genetic newlineAlgorithm (iHOGA) software to solve complex multi-objective optimization newlineproblems. newline