DocumentCode :
3258862
Title :
Short term generation scheduling of a Microgrid
Author :
Logenthiran, T. ; Srinivasan, Dipti
Author_Institution :
Dept. of Electr. & Comput. Eng., Nat. Univ. of Singapore, Singapore, Singapore
fYear :
2009
fDate :
23-26 Jan. 2009
Firstpage :
1
Lastpage :
6
Abstract :
Microgrids are low voltage intelligent distribution networks comprising various distributed generators, storage devices and controllable loads which can be operated as interconnected or as islanded system. The optimal generation scheduling is one of the important functions for the Microgrid operation. This paper describes a three-step efficient method for the optimal generation scheduling of a Microgrid in island operation. The first step of the method is to set up an initial feasible solution for thermal unit commitment and the next step is to solve the thermal unit commitment problem. The final step is to optimize the renewable-thermal dispatch based on thermal unit commitment results. Solving the thermal unit commitment problem has more opportunity to minimize the operating cost. Therefore, few algorithms such as Lagrangian relaxation, genetic algorithm and a hybrid algorithm of Lagrangian relaxation and genetic algorithm have been used to find the least operating cost. Microgrid which is considered in the case study, consists of a PV system, a wind plant, 10 thermal units and a battery bank.
Keywords :
genetic algorithms; power generation scheduling; power grids; power system simulation; Lagrangian relaxation; genetic algorithm; low voltage intelligent distribution networks; microgrid; optimal generation scheduling; renewable-thermal dispatch; short term generation scheduling; thermal unit commitment; three-step efficient method; Costs; Distributed power generation; Genetic algorithms; Intelligent networks; Job shop scheduling; Lagrangian functions; Low voltage; Power generation; Power generation economics; Processor scheduling; Distributed Energy Resource; Genetic Algorithm; Lagrangian Relaxation; Microgrid; Optimal Generation Scheduling;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
TENCON 2009 - 2009 IEEE Region 10 Conference
Conference_Location :
Singapore
Print_ISBN :
978-1-4244-4546-2
Electronic_ISBN :
978-1-4244-4547-9
Type :
conf
DOI :
10.1109/TENCON.2009.5396184
Filename :
5396184
Link To Document :
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