OPTIMIZATION OF A GRID INDEPENDENT HYBRID RENEWABLE ENERGY SYSTEM

Abstract

One of the most promising applications of renewable energy technology is the installation of hybrid energy systems in remote areas, where the cost of grid extension is prohibitive and the price for fuel increases drastically with the remoteness of the location. The implementation of 1-lybrid Renewable Energy System (HRFS) can significantly reduce the total lifecycle cost and provide a more reliable supply of electricity. IIRES describes a stand-alone energy system, which combines renewable energy sources with batteries for chemical storage. Although, with the increased complexity in comparison with the single energy systems, optimum design of hybrid system becomes complicated. In order to efficiently and economically utilize the renewable energy resources, one optimal sizing method is necessary. In this project, an optimization model is developed to determine the best size of a stand-alone hybrid renewable energy system (HRES) for electrification to a remote area. The model is defined based on three decision variables related to the system components, namely, total area occupied by the set of PV panels (a continuous variable), total swept area by the rotating turbines' blades (a continuous variable) and the number of batteries (an integer variable). In order to find the optimal values of the variables, particle swarm optimization (PSO) is proposed. PSO, which is an efficient population-based heuristic technique, can be a good candidate. Particles of PSO probe the search space to minimize the life cycle cost (L.CC), ensuring at the same time certain level of system reliability.