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Top1. Introduction
The rapid growth of the world's population and the new dimensions of industrialization are rapidly increasing the need for energy. For this reason, the developed and developing countries which could not solve the energy problem, tried to develop new energy resources and new technologies for energy needs. As in all developing countries, our country must have sufficient energy to reach the level of developed countries. Nowadays, the need for energy and the negative effects of fossil fuels on the environment, as well as the tendency of fossil fuels to run out, have led researchers to research renewable energies. Biofuels can be produced from agricultural biomass and include bioethanol, biodiesel, bioethanol, biogas (methane and carbon dioxide mixture), and bio-oil components (Demirbaş, 2009). Turkey has a significant bioenergy potential because of its high number of animals and large farmland area. Therefore, an increase in the number of biogas facilities might contribute to the region's energy challenges. The environmental characteristics and the location problems of a biogas facility are important features to ensure maximum profitability (Derse, 2018).
To solve the facility location problems several methods from the center of gravity to clustering have been purposed. The center of gravity (COG) is a mathematical method used to locate the distribution center in such a way as to minimize the distribution costs. The p-median problem is the location problem of p number of facilities to minimize the total transportation cost (Sule, 2001). One of the methods used in the solution of the facility location problem is clustering. The clustering method, with its simplest definition, is the grouping of data with similar characteristics. The overall objective is to ensure homogeneity within the cluster, and heterogeneity among clusters. While the data in the clusters are very close to each other, the distance between the two different clusters is very large. The clustering method in facility location problems is related to the current positions and similarities of individuals in space. Individuals who are near to each other are gathered in the same cluster.
This study has three important contributions. The first contribution is that fuzzy clustering-based hybrid methods are first applied to the location of renewable energy systems. No study has been found in the literature yet. The second important contribution is that the Revised Weighted Fuzzy C-Means and Center-of-Gravity hybrid method developed for the solution of the multi-facility Weber problem. This new method adaptation to the facility location of biogas plants are proposed for the first time in this study. The third important contribution is that Revised Weighted Fuzzy C-Means and Nelder-Mead hybrid method developed by Küçükdeniz and Esnaf (2018), which is the core of the proposed method, was also first used for biogas plant location problem.
Facility location and modelling of biogas, one of the renewable energy sources, is an increasingly important issue. With the establishment of a biogas facility in a suitable location, attention is drawn to the savings in transportation costs and sustainability. Determination of location selection is important for facilities as it greatly affects fixed and variable costs. The aim of the study both the cost will be reduced and the efficiency and profit to be obtained from the biogas facilities will be maximized. Determining the optimum location of biogas facilities benefits many social, environmental, geographical, legal and economic areas. The proposed model was applied for the first time in renewable energy sources. The developed hybrid method is one of rare studies in the literature for biogas facilities. With the proposed model, both optimum location of renewable energy sources are provided and it provides an environmental contribution with the decrease in transportation costs.