Optimization of Power System Problem with Renewable Energy Sources Using Enhanced Differential Evolution Algorithm

Abstract

Electricity demand in most homes is supplied using conventional electric power resources such as coal, and other fossil fuels. With the passage of time, these resources are depleting and producing a large amount of greenhouse gases which is harmful for the ozone layer and eventually leading to global warming. In order to reduce these emissions and provide clean energy, renewable energy resources come into action. After all, due to the increasing costs as well as the harmful emissions, renewable resources offer the best means of replacing them. Solar and wind are the most commonly used renewable resources and are also easily available. Solar and wind energy resources are important sources for providing renewable and clean energy. In general, depending on any one resource as such is not recommended as each has its own drawbacks and thus forming a hybrid renewable energy system helps in integrating various energy sources to form a single system. In this paper, a sizing optimization that involves optimizing the number of solar panels, battery units and the number of micro turbines is done using optimization algorithms. A small region in Palestine was selected for carrying out the experimentation. The Objective function minimizes the cost of energy (COE) and also satisfies the energy demand for the whole year round. Enhanced Differential Evolution Algorithm is being implemented to meet the requirements. Results obtained from enhanced DE is compared with other optimization algorithms to prove its effectiveness.