DocumentCode
84638
Title
A Hierarchical Framework for Generation Scheduling of Microgrids
Author
Xiong Wu ; Xiuli Wang ; Chong Qu
Author_Institution
Sch. of Electr. Eng., Xi´an Jiaotong Univ., Xi´an, China
Volume
29
Issue
6
fYear
2014
fDate
Dec. 2014
Firstpage
2448
Lastpage
2457
Abstract
The uncertainty and intermittency of renewable energy sources pose a challenge to generation scheduling of microgrids. This paper presents a hierarchical framework to handle the uncertainty and realize an economic generation schedule of microgrids. The lower level combines a battery energy-storage system (BESS) with renewable energy sources, targeting maximal utilization of renewable power and minimal deviation from the schedule, to provide an optimal generation plan in the day-ahead market. The upper level minimizes the total cost of the microgrid by the genetic algorithm (GA) to yield an economic generation plan of dispatchable distributed generators (DGs) based on the lower level. Two stages of such hierarchical scheduling before and in the day gradually reduce the uncertainty, and lead the overall schedule to evolve toward a stable and economic one. The method is tested on a 14-bus microgrid system. The simulation indicates that the wind turbine and photovoltaic are gradually stabilized by BESS Besides, the operation is scheduled economically, and cheap DGs are always arranged in priority.
Keywords
battery management systems; distributed power generation; genetic algorithms; power generation economics; power generation planning; power generation scheduling; wind turbines; 14-bus microgrid system; BESS; battery energy-storage system; day-ahead market; dispatchable distributed generators; economic generation schedule; generation scheduling; genetic algorithm; hierarchical framework; hierarchical scheduling; microgrids; optimal generation plan; photovoltaic; renewable energy sources; renewable power; wind turbine; Energy storage; Microgrids; Optimization; Photovoltaic systems; Renewable energy sources; Schedules; Framework; distributed generator genetic algorithm; generation schedule; microgrids;
fLanguage
English
Journal_Title
Power Delivery, IEEE Transactions on
Publisher
ieee
ISSN
0885-8977
Type
jour
DOI
10.1109/TPWRD.2014.2360064
Filename
6909031
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