A Method for Particle Swarm Optimization and its Application in Location of Biomass Power Plants

Abstract

This work introduces a binary particle swarm optimization based approach to locate the optimal location for biomass-based power plants. The proposed algorithm also offers the supply area for the biomass plant. The optimal location can be addressed as a nonlinear optimization problem. The profitability index is the fitness function for the binary optimization algorithm. It is defined as the ratio between the net present value and the initial investment.

The constraints for simulations are: the biomass power plant must be inside the supply area; the electric power generated by the plant is limited to 10 MW. Computer simulations have been performed using 15 particles in the swarm and 50 iterations. Simulation results show that the proposed approach provides high-quality solutions (the profitability index is about 1.8) with reduced computation time (about 170 times lower than that required for exhaustive search).

Keywords:

• Biomass
• Distributed power generation
• Binary particle swarm optimization
• Profitability index
• Optimal location