COMBINED GENETIC ALGORITHM SIMULATED ANNEALING FUZZY SET APPROACH TO SHORT-TERM GENERATION SCHEDULING WITH TAKE-OR-PAY FUEL CONTRACT

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 sche dules which meet as closely as possible the take-or-pay fuel consumpti on. The formulation is then extended to cover also the economic dispat ch 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 f or the establishment of new algorithms for the present problem. The ne w algorithms are demonstrated through a test example, in which the gen eration loadings of 13 generators in a practical power system are sche duled in a 24-hour schedule horizon.