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