Optimum determination of number, capacity and location of bioenergy power plant/s by using geographic information system: A case study in Bismil

Bismil district of Diyarbakir is a region where agricultural activities are very common. About 60% of the terrain is irrigable. Cotton and corn are mostly grown in these irrigable lands. In this study, a mixed integer linear programming (MILP) model and a metaheuristic algorithm which optimize the numbers, locations and capacities of the CCHP (tri-generation=combined cooling, heating and power) facility(ies) that produces energy from cotton and corn residues were developed and solved. Both technics try to maximize the net present value of the potential investment by comparing the trade-offs between the agricultural residues/endproduct transportation costs, facility(ies) and pipeline installation costs. All points (supply, candidate power plant, heat demand, electricity distribution) were determined in Geographic Information System. However, size of the problem was reduced to test the viability of the proposed MILP model. After proving viability of the MILP model, a metaheuristic algorithm (Simulated Annealing) was employed for a real-world problem in Bismil. As annual revenue, electricity, the heating/cooling energy and the fertilizer (biochar) sale; as for annual expenses, transportation of raw materials and heating/cooling energy, losses during heat and electricity transportation, operational maintenance costs of facilities and pipelines were considered. Initial investment cost includes facility, pipeline and electricity transmission installation costs. The model proposed 1 facility with an installed power of about 29 MW. Cooling energy demand of 41 settlements, both cooling and heat energy demand of 9 settlements were met. The net present value of the investment is almost 260 million euro and the repayment period is 1,3 years.