Solar energy utilization patterns for different district typologies using multi-objective optimization: A comparative study in China

Abstract

Abstract Currently, solar energy technologies are in the stage of intensive development. With booming solar industry, there is a challenge to seek for appropriate solar energy solutions for different district typologies. This paper presents a comparative study on solar energy utilization patterns for different types of districts located in Kunming, China. Four district typologies are investigated: residential district (RD), official district (OD), commercial district (CD) and industrial district (ID). For each district, the objective is to identify such solar energy utilization patterns that result in an optimal design and operation of solar energy system. The optimum system is defined and obtained through minimizing life cycle CO 2 emissions and costs as well as maximizing exergy efficiency. To that end, a multi-objective optimization approach based on Genetic Algorithm is proposed. The results of the case study suggest that solar energy is to represent 3.7%, 5.9%, 7.9% and 21.4% of annual energy consumption for RD, OD, CD and ID, respectively. For each district, the portfolio of solar energy technologies is different. Solar power systems factually contribute to the energy supply of ID only. The final work aims at investigating the effects of different solar energy parameters on the solar utilization patterns for these districts.