Abstract
Solar energy is an important and reliable source of energy. Better understanding the concepts and relationships of the factors that affect solar energy generation capacity can enhance the usage of solar energy. This understanding can lead investors and governors in their solar power investments. However, solar power generation process is complicated, and the relations among the factors are vague and hesitant. In this paper, a hesitant fuzzy cognitive map for solar energy generation is developed and used for modeling and analyzing the ambiguous relations. The concepts and the relationships among them are defined by using experts’ opinions. Different scenarios are formed and evaluated with the proposed model.
Highlights
Growing population and industrialization has been increasing the energy demand throughout the world [1]
Obtained trapezoidal membership functions are defuzzified to crisp values that are accepted the weights of the causal relationships and defined as weight matrix (W) and it is operated in the Hesitant Fuzzy Cognitive Maps (HFCMs) until to converge to an equilibrium point (Fig. 6)
We focused on two main titles that are “Solar Energy” and “Hesitant Fuzzy Cognitive Maps.”
Summary
Growing population and industrialization has been increasing the energy demand throughout the world [1]. There is a consensus among scholars that conventional energy sources, fossil fuels, have catastrophic damage on the environment by increasing CO2 emission. The investors and governors can be conducted toward solar power investments [10] These factors around the new solar energy generation are dynamic and complex, and the relationships among factors are ambiguous. The aim of the study is to assess the hesitant and causal relationship among the concepts around the capacity of new generated solar energy by using Hesitant Fuzzy Cognitive Maps (HFCMs).
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