Optimization of a typical biomass fueled power plant using Genetic algorithm and binary particle swarm optimization

Over thousands tons of animal manures are produced in Iran. The major animal manures producers are located in central regions. Animal manures collection is an autochthonous and important renewable energy sources that in most cases are released in nature by ranchers. In this paper, a typical animal manure producer region is considered and optimal location and size of a typical biomass fueled power plant is determined. Genetic algorithm (GA) is used as the major approach of determination and effectively this approach will make possible to determine the optimal location, biomass supply area and power plant size that offer the best profitability for investor. Binary particle swarm optimization algorithm is also used as the second approach of optimization and eventually results obtained from both algorithm are compared. In this work we use profitability index (PI) as the fitness function of Genetic algorithm and the point with the maximum PI is selected.