Multiobjective Optimization of a Hybrid Wind/Solar Battery Energy System in the Arctic

Abstract

This paper presents an optimal design of a hybrid wind turbine/PV/battery energy system for a household application using a multiobjective optimization approach, namely, particle swarm optimization (PSO). The ultimately optimal component selection of the hybrid renewable energy system (HRES) is suggested by comprehensively investigating the effects of various factors on the cost-reliability relation, such as the mounting orientation, temperature on the PV modules, wind turbine hub height, different types of batteries, and different load profiles. The optimization results show the feasibility of HRES for a single-family household demand in the arctic region of Tromsø, Norway. As we will discuss in the results, an HRES operating in such a region can achieve great energy-autonomous levels at a reasonable cost partially thanks to the cold climate. The mounting structure and temperature effects on the PV modules and the battery type can significantly change the system performance in terms of cost and reliability, while a higher wind turbine hub offers little improvement. The result suggests an optimal HRES consisting of a wind turbine with a swept area of 21 m2 and a hub height of 12 m, a PV system of 12 m2 with 2-axis tracking, and a battery bank of 3 kWh. This system will achieve 98.2% in self-reliance. Assuming that the system lifetime is 20 years, the annual cost is about 900 USD. Even though this study focuses on an HRES for a single-family application in the arctic, such an approach can be extended for other applications and in other geographical areas.