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Profitability comparison between gas turbines and gas engine in biomass-based power plants using binary particle swarm optimization

Abstract:

This paper employs a binary discrete version of the classical Particle Swarm Optimization to compare the maximum net present value achieved by a gas turbines biomass plant and a gas engine biomass plant. The proposed algorithm determines the optimal location for biomass turbines plant and biomass gas engine plant in order to choose the most profitable between them. Forest residues are converted into biogas . The fitness function for the binary optimization algorithm is the net present value. The problem constraints are: the generation system must be located inside the supply area, and its maximum electric power is 5 MW. Computer simulations have been performed using 20 particles in the swarm and 50 iterations for each kind of power plant. Simulation results indicate that Particle Swarm Optimization is a useful tool to choose successful among different types of biomass plant technologies. In addition, the comparison is made with reduced computation time (more than 800 times lower than that required for exhaustive search). © Springer-Verlag Berlin Heidelberg 2007.