A weighted fuzzy clustering-based facility location model for renewable energy systems

As the population density rises, the importance of renewable energy sources ever more apparent. One of the most important factors in this situation the rapid excuted of fossil fuels and damage to environment. Renewable energy is defined as sustainable resources through natural processes that undergo continual replenishment. Furthermore, CO2 emissions according to fossil fuels is released at much lower levels, its negative impact on the enviroment is also low. In additon to proposing a new model for the facility location, is mentioned renewable energy systems to attract attention to increasing energy requirements. Solar, wind, water, geothermal and biomass are defined as renewable energy resources. Our study, the preference for biogas as a renewable energy sources is that conditions of our country are favorable for agricultural and livestock activities. Our aim is supplied from renewable energy facilities. Assessing the most suitable locations for renewable energy facilities to achieve the targetd yield, is one of the important issues to be examined. In the thesis study, it was examined to determine the most suitable areas for biogas facility location because of are favorable for Konya province where agricultural and livestock activities are intensive in our country. In the facility location problem solving was used method Revised Weighted Fuzzy C-Means. In our review of the literature, there is no study in which this method is used for the biogas facility location. In the initial stage of the methodology, data analysis was performed. In the second stage of methodology, new data for futere years were xx obtained using forecasting methods. Subsequently, the forecasting performance was evaluated, the data set that minimizes the margin of error is obtained. In facility location was used to the data obtained by the forecasting method and the most suitable locations were determined by predicting future conditions. Biogas facility location was examined from an integrated perspective, considering population, cattle and sheep numbers. In the third stage of methodology, a novel model proposal was developed fort he facility location problems, these three different variables are combined into a single final value. Our study's innovative aspects stem from this model proposed for the first time in our study and the first application of the Revised Weighted Fuzzy C-Means method in biogas facility location. The strength of the study are that the proposed approaches are applicable in today's conditions and considering future scenarios in the facility location process. The approach proposed for the first time in this study will be applicable in many regions and areas and is expected will contribute to future studies.