Comparison of metaheuristic techniques to determine optimal placement of biomass power plants

摘要: This paper deals with the application and comparison of several metaheuristic techniques to optimize placement supply area biomass-fueled power plants. Both, trajectory population-based methods are applied for our goal. In particular, two well-known method, such as Simulated Annealing (SA) Tabu Search (TS), commonly used methods, Genetic Algorithms (GA) Particle Swarm Optimization (PSO) hereby considered. addition, a new binary PSO algorithm has been proposed, which incorporates an inertia weight factor, like classical continuous approach. The fitness function metaheuristics is profitability index, defined ratio between net present value initial investment. this work, forest residues considered biomass source, problem constraints are: generation system must be located inside area, its maximum electric 5 MW. comparative results obtained by all discussed. Random walk also assessed we deal with.