Abstract

For a photovoltaic (PV) project, there are multiple stages during its life cycle, including investment, construction, and operation. To promote the sustainability of PV projects, it is essential to use appropriate methods to handle the key decision-making issues at different life-cycle stages. Site selection is an important step in the investment phase, which has a significant effect on the potential electricity generation and the socio-economic and environmental benefits. In this context, various factors need to be considered to select a suitable location for a sustainable PV project, for example, solar resources, transportation condition, geology, and influences of PV project on the local environment and society, etc. Therefore, site selection of PV power stations could be seen as a multiple-criteria decision-making (MCDM) process. A number of MCDM methods have been used for site selection; however, many of them do not consider the judgments’ vagueness, and suppose experts are rational, which are not consistent with the reality. In this chapter, an integrated location selection model for PV power stations is constructed. It utilizes rough sets and prospect theory (PT) improving the limitations of technique for order performance by similarity to ideal solution (TOPSIS) method. Rough sets can handle the imprecise and vague information flexibly, without no preset assumptions; PT could effectively manipulate the bounded rationality. In the end, this hybrid framework is applied to a real case to demonstrate its effectiveness and feasibility.

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