Title :
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
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;
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
DOI :
10.1109/ICEIE.2010.5559679
