Sizing Optimization of Hybrid Photovoltaic-Wind-Battery System towards Zero Energy Building using Genetic Algorithm

Abstract

A new topic of Zero Energy Building (ZEB) is getting famous in research areabecause of its goal of reaching zero carbon emission and low building cost. Renewableenergy system is one of the ideas to achieve the objective of ZEB. Genetic Algorithm (GA)is widely used in many research areas due to its capability to escape from a local minimalto obtain a better solution. In our study, GA is chosen in sizing optimization of thenumber of photovoltaic, wind turbine and battery of a hybrid photovoltaic-wind-batterysystem. The aim is to minimize the total annual cost (TAC) of the hybrid energy systemtowards the low cost concept of ZEB. Two GA parameters, which are generation numberand population size, have been analysed and optimized in order to meet the minimumTAC. The results show that the GA is efficient in minimizing cost function of a hybridphotovoltaic-wind-battery system with its robustness property