Modeling Turkey's solar energy potential under different conditions

Fossil-based energy sources are presented as primary energy supply in response to rising energy demand with increased population and industrialization. Carbon dioxide and harmful gases that are emitted to the environment in the energy conversion process of fossil energy sources accumulate in the atmosphere and cause the greenhouse effect. The greenhouse gases that cause global warming and climate changes reveal environmental, social and economic promises on a global scale. The world is turning to environmentally friendly renewable energy sources (hydro, wind, sun, geothermal, tidal, biomass) to eliminate the problems of fossil-based energy sources. The sun, which is the main source of the energies on earth (except tidal, nuclear, geothermal), is the most important renewable energy source. Solar energy systems require high-tech infrastructure and equipment, while simple and high-tech methods are used to obtain heat and electricity from the sun. The high initial investment cost is the main disadvantage of solar energy systems and also prevents price competition with other energy systems. The competition conditions in the energy sector make it necessary for the solar energy systems to make the right decisions in the installation process. The correct identification and assessment of environmental, social, economic and technical conditions are required to make the right decisions. Experts that contribute to our work takes place in the energy sector, and academic and causal relationships between identified factors were evaluated taking into consideration Turkey and global conditions. In this study, Turkey's solar energy potential is modeled in different conditions to help decision makers in decision making processes. Factors affecting the production of renewable energies are defined, and the effects of wind and solar energy production are modeled with the Hesitant Cognitive Map. Many factors influence the energy sector, and these factors contain uncertainty in a dynamic feature, it is appropriate to develop modeling and calculations by fuzzy logic. Literature and expert opinions determined factors affecting the production and use of solar energy, and fuzzy cognitive maps modeled causal relationships between these factors. Models operated with different initial state scenarios are evaluated on the steady-state values and process movements of the factors. As the initial study results show the significant effects of economic factors in the generation of solar energy, the study of the factors affecting the solar energy price has been defined as a new study title. Similarly, factors affecting the price of solar energy were determined by literature and expert opinions, and causal relationships between factors were evaluated linguistically based on the knowledge and experience of the experts. These studies provide information to decision-makers about the factors and the interactions of factors with each other in the solar energy plant installation and pricing decision-making process. In the last study of the thesis, the economic analysis of the solar power plant was examined using life cycle cost and leveled cost of electricity methods. Pythagorean fuzzy clusters are referenced to incorporate the uncertainties contained in methods based on temporal effects into calculations. The values obtained from Pythagorean based LCC and LCOE calculations give information about the validity of the installation of solar energy systems and compare the solar energy system with other energy systems.