Size optimization for hybrid (photovoltaic-wind) energy system using heuristic optimization algoritm

With the increasing energy demand in recent years, the trend towards renewable energy sources has increased. Therefore, researches on renewable energy sources are increasing with this interest. Since the applicability of wind turbines and photovoltaic panels (such as installation and energy supply potential) for micro scale energy production is easier than the others, renewable energy sources used by these systems have been considered as the main area of interest in the study. This type of power generation systems can be used alone or used together because of intermittent or discontinuous wind and solar energy. The hybrid energy system consists of two or more power generation systems, storage units and control elements. Determining the size of the hybrid energy system is a problem that needs to be solved by considering different criteria. Many techniques such as analytical methods, dynamic programming and heuristic algorithms are used for size optimization of these systems. This thesis proposes that the size of the hybrid photovoltaic/wind power generation system is determined with the help of Artificial Bee Colony algorithm, an heuristic optimization algorithm. Pınarhisar Vocational and Technical Anatolian High School (PMTAL) was chosen as the study area. In this context, wind speed and solar radiation data of the region were obtained from TUMAS database of General Directorate of Meteorology. With these data, size optimization was developed in object oriented programming language to minimize the total cost of hybrid photovoltaic/wind energy system which can meet the power demand of PMTAL. The reliability analysis of the system that will meet the power demand was made by the power supply loss probability (LPSP) method. In this method, LPSP values are determined as 0%, 0.2%, 1% and 3% and the system is provided with sufficient power to meet the load demand. According to the determined LPSP values, the total annual cost of hybrid photovoltaic/wind energy system is minimized and optimum wind turbine, solar panel and battery number is determined by Artificial Bee Colony optimization algorithm. In addition, size optimization of single energy systems consisting only of photovoltaic panels and wind turbines was calculated by the same method and the results were compared with the hybrid system. As a result, in this study, the decision making process has been accelerated to determine the size of the renewable energy source with the Artificial Bee Colony optimization algorithm and with the improvement of the decision quality, an effective and correct solution has been reached.