Strategic Analysis of Solar Energy Pricing Process with Hesitant Fuzzy Cognitive Map

Abstract

Sun is the leading renewable energy source for satisfying energy demand. Solar energy systems, which have direct and indirect energy generation technologies, require high initial costs and low operation costs. The right determination of solar energy price has an important role on efficient solar energy investment decisions. In this study, the critical factors for the solar energy price are defined and the causal relationships among them are represented with a Hesitant Fuzzy Cognitive Map (HFCM) model. The causal relations among the factors and the initial state values of the factors are defined with the linguistic evaluations of the experts by using Hesitant Fuzzy Linguistic Term Sets (HFLTSs). The linguistic expressions are converted into Trapezoid Fuzzy Membership Functions (TFMFs). The obtained HFCM model is used for simulating various scenarios, and the equilibrium state values of the factors are obtained. The results indicate that the factors affecting solar energy systems have an important effect in determining the solar energy price. The solar energy price adapts to the general energy price market in the long term.