Abstract
Renewable energy sources (solar, wind, tidal, etc.), which are unlimited and have a fair distribution in the world, are an alternative to the depleting fossil fuels (coil, petroleum, natural gas, etc.). It is necessary to identify the right technologies and methods to make more effective use of renewable energy sources including uncertainty and irregularity in resource creation. In this study, dynamic environmental factors affecting the production of solar and wind energy are defined and the relations among them are linguistically expressed by the experts. These linguistic relationships among factors and their initial states are assessed by new developed hesitant linguistic cognitive map method that is an extension of hesitant fuzzy sets and fuzzy cognitive map. Relational development between factors was observed by simulating the model according to the initial condition of the factors. Thus, the model helps investors and governments to direct their solar and wind energy investment decisions.
Highlights
The energy obtained from infinite natural sources such as wind power, hydropower, solar energy, geothermal energy, biomass, tidal power and wave power are called renewable energy
After these core knowledge and definitions, the hesitant fuzzy cognitive maps (HFCMs) operation flow process (Fig. 4) can be summarized as following steps: Step 1 HFCM consists of concepts and weighted edges among concepts that can be defined by experts with their linguistic expressions
Simulation results show that the affecting and being affected of the transmitter and global concepts take a long time because of their long path lengths within concepts
Summary
The energy obtained from infinite natural sources such as wind power, hydropower, solar energy, geothermal energy, biomass, tidal power and wave power are called renewable energy. Among the renewable energy sources, solar power has the highest increase capacity. In 2014, solar power generation capacity increased by 14.1% compared with 2013 [1]. Hesitant fuzzy cognitive maps are used for modeling solar energy generation capacity. This study examines the dynamic behavior of factors whose behavior is unclear during the installation phase of renewable energy systems. In this way, the relationships between the factors are determined linguistically by expert opinions and the behavior of the factors and the general system can be observed. “Modeling renewable energy usage based on HFCMs”, the proposed hesitant fuzzy renewable energy cognitive map with different scenarios is given.
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