Combined genetic algorithm/simulated annealing/fuzzy set approach to short-term generation scheduling with take-or-pay fuel contract

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Abstract
This paper first develops a new formulation for short-term generation scheduling with take-or-pay fuel contract. In the formulation, a fuzzy set approach is developed to assist the solution process to find schedules which meet as closely as possible the take-or-pay fuel consumption. The formulation is then extended to also cover the economic dispatch problem when the fuel consumption is higher than the agreed amount in the take-or-pay contract. The extended formulation is combined with the genetic algorithms and simulated-annealing optimization methods for the establishment of new algorithms for the present problem. The new algorithms are demonstrated through a test example, in which the generation loadings of 13 generators in a practical power system are scheduled in a 24-hour schedule horizon.

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