Size optimization of a stand-alone solar-wind-battery hybrid system for net zero energy buildings: A case study

Abstract

In this research, a solar-wind-battery hybrid system (PV/WT/BS) is proposed to supply the electricity demand of a stand-alone net zero energy building. for estimating the output power of the hybrid system, wind speed and solar irradiance are measured throughout a year and their uncertainties are estimated by applying the Monte Carlo algorithm. The wind speed Wiebull distribution is estimated, and the solar irradiance distribution is obtained using a novel approach based on the sky cloudiness parameter. Moreover, to simulate the performance of the hybrid system components according to the actual conditions, their availability is calculated using failure and repair rates. The optimal size of the proposed hybrid system is calculated considering, for the first time, the reliability and system costs. The system's size is optimized through the consideration of key decision variables, including photovoltaic panel area, rated power, wind turbine tower height, and battery capacity. Two distinct optimization methods are employed: a single-objective approach utilizing Genetic Algorithm, where the total system cost is minimized with reliability as a constraint, and a double-objective approach using NSGA-II, considering both initial cost and reliability as objectives. The optimal system size is determined through an efficient decision-making process. A practical case study is conducted, monitoring wind speed, solar irradiance, and electricity demand of a residential building at 15-minute intervals over a year. The results reveal the efficacy of the optimization methods, with the single-objective approach yielding a total system cost of €75,495 and reliability of 95.19%, while the double-objective optimization achieves a cost of €73,460 and a reliability of 91.88%.