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A method for fuzzy logic optimization and its application in placement of biomass power plants

Abstract:

This chapter addresses biomass fuelled generation of electricity in the specific aspect of finding the best location and the supply area of the electric generation plant for gas turbine, taking into account the variables involved in the problem, such as the local distribution of biomass resources, transportation costs, distance to existing electric lines, etc. For this technology, not only optimal location and supply area of the biomass plant, but also net present value and generated electric power are determined by an own metaheuristic based on fuzzy logic. This metaheuristic can be categorized as a trajectory optimization method. The search process of trajectory metaheuristics starts from an initial solution and iteratively try to replace the current solution by a better or more promising solution, in an appropriate manner defined as neighbourhood. The method works in a discrete search space coding each solution as a binary string. This methodology defines two types of neighborhood based on Hamming distance. First order neighbors are considered those solutions whose Hamming distance equals to one. Likewise, second-order neighbors are considered those solutions whose Hamming distance equals to two. The fuzzy system provides the solution at each iteration depending on the fitness of some neighbors of first and second order. This methodology has been compared with other classical trayectory methods, such as Tabu search and Simulated Annealing.