Optimization Of Location Of Generating Stations Using Genetic Algorithm

With the increase of power demand new generating stations are needed. So generation expansion planning is required to meet increased load demand, and transmission planning is required to transmit power to the load centers in efficient and economical manner. In generation expansion planning cost of land is very important. Normally land cost near load centers is high, while transmission line cost away from load centers is high. Generation expansion planning model in this thesis consider capital costs of land, power plant, and transmission lines. Cost of operation of all existing and new power plants and cost of transmission line losses is also considered. Genetic algorithm in MATLAB is used as main optimization tool and linear programming is used for power system operation optimization of the whole system proposed by genetic algorithm. The proposed expansion plane consider both generation and transmission expansion and is mixed integer non linear programming MINLP. The proposed model is applied to Garver test system and IEEE30bus test system on40x40cells map with different land costs. It resulted in the selection of optimized location, power plant types at these locations, transmission lines between existing and new buses, and power output optimization of all plants.