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

Author

Wong, Kit Po ; Wong, Suzannah Yin Wa

Author_Institution

Dept. of Electr. & Electron. Eng., Western Australia Univ., Nedlands, WA, Australia

Volume

11

Issue

1

fYear

1996

fDate

2/1/1996 12:00:00 AM

Firstpage

128

Lastpage

136

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

Keywords

economics; electric power generation; fuzzy set theory; genetic algorithms; load dispatching; scheduling; simulated annealing; 24-hour schedule horizon; economic dispatch; fuzzy set; genetic algorithm; optimization; power system; short-term generation scheduling; simulated annealing; take-or-pay fuel contract; Contracts; Fuel economy; Fuzzy sets; Genetic algorithms; Optimization methods; Power generation; Power generation economics; Power system simulation; Scheduling algorithm; Simulated annealing;

fLanguage

English

Journal_Title

Power Systems, IEEE Transactions on

Publisher

ieee

ISSN

0885-8950

Type

jour

DOI

10.1109/59.485994

Filename

485994