Diploid genetic algorithm to solve optimal scheduling problem for hydropower in liberalised electricity market

Author

He, Li ; Chen, Dong

Author_Institution

Dept. of Electr. & Electron. Eng., Hubei Univ. of Technol., Wuhan, China

Volume

1

fYear

2010

fDate

1-3 Aug. 2010

Abstract

This paper proposed an improved diploid genetic algorithm (DGA) to solve the nonlinear optimization problem for hydropower producer to obtain realistic and feasible bid in electricity market. The influence of mutation operator on population diversity in DGA was analyzed by introducing an average schema similar rate as the measure criteria. It showed that DGA had a better performance than HGA in terms of preserving the diversity. A case study was served for demonstrating the reasonability and feasibility of the developed method.

Keywords

genetic algorithms; hydroelectric power; power generation scheduling; power markets; DGA; average schema similar rate; diploid genetic algorithm; hydropower; liberalised electricity market; mutation operator; nonlinear optimization problem; optimal scheduling problem; population diversity; Electricity supply industry; Equations; Hydroelectric power generation; Mathematical model; Optimal scheduling; Water resources; DGA; NLP; hydropower; mutation operator;

fLanguage

English

Publisher

ieee

Conference_Titel

Electronics and Information Engineering (ICEIE), 2010 International Conference On

Conference_Location

Kyoto

Print_ISBN

978-1-4244-7679-4

Electronic_ISBN

978-1-4244-7681-7

Type

conf

DOI

10.1109/ICEIE.2010.5559679

Filename

5559679