DocumentCode :
2273809
Title :
Unit commitment in microgrids by improved genetic algorithm
Author :
Liang, H.Z. ; Gooi, H.B.
Author_Institution :
Sch. of Electr. & Electron. Eng., Nanyang Technol. Univ., Singapore, Singapore
fYear :
2010
fDate :
27-29 Oct. 2010
Firstpage :
842
Lastpage :
847
Abstract :
A microgrid consists of various types of smart distributed generators, renewable generators, storage devices and controllable load, which not only must meet their local needs but also are under the hierarchical control of management system. Due to this combination of conventional and renewable sources, the unit commitment becomes more crucial and more complicated in the management of a microgrid. In this paper, an improved genetic algorithm based method is proposed for unit commitment in a microgrid. The genetic algorithm is improved by adopting the simulated annealing technique to accelerate the convergence. The objective is to minimize microgrid´s operational cost when it is isolated and maximize its revenue when it is connected to upstream networks.
Keywords :
distributed power generation; genetic algorithms; power generation dispatch; power generation scheduling; simulated annealing; controllable load; genetic algorithm; hierarchical control; microgrid operational cost; microgrid unit commitment; renewable generator; simulated annealing technique; smart distributed generator; storage devices; Acceleration; Batteries; Electricity; Gallium; Generators; Genetic algorithms; Optimization; genetic algorithm; microgrid; renewable source; unit commitment;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
IPEC, 2010 Conference Proceedings
Conference_Location :
Singapore
ISSN :
1947-1262
Print_ISBN :
978-1-4244-7399-1
Type :
conf
DOI :
10.1109/IPECON.2010.5697083
Filename :
5697083
Link To Document :
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