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A genetic algorithm-based hybrid optimization approach for microgrid energy management
Li HP(李鹤鹏); Zang CZ(臧传治); Zeng P(曾鹏); Yu HB(于海斌); Li ZW(李忠文)
Department工业控制网络与系统研究室
Conference Name2015 IEEE International Conference on Cyber Technology in Automation, Control, and Intelligent Systems (CYBER)
Conference DateJune 8-12, 2015
Conference PlaceShenyang, China
Source Publication2015 IEEE International Conference on Cyber Technology in Automation, Control, and Intelligent Systems (CYBER)
PublisherIEEE
Publication PlacePiscataway, NJ, USA
2015
Pages1474-1478
Indexed ByEI ; CPCI(ISTP)
EI Accession number20161402187632
WOS IDWOS:000380502300269
Contribution Rank1
ISSN2379-7711
ISBN978-1-4799-8730-6
KeywordMicrogrids Energy Management System Mixed Integer Nonlinear Programming Genetic Algorithm Optimization
AbstractThis paper proposes a novel Meta-heuristic based hybrid optimization method for Microgrid energy management system. First, microgrid energy management problem is modeled as a mixed integer nonlinear programming with the consideration of quadratic fuel cost of distributed generators and their startup/shut-down states. In order to obtain a favorable solution, a hybrid solution procedure combined quadratic programming and genetic algorithm is proposed to solve the problem. Then, the proposed method is verified via numerical simulation. Through the comparison of optimization result with IBM ILOG CPLEX Optimizer, simulation shows that the proposed algorithm has the advantage of finding better scheduling solution which leads to less operating cost.
Language英语
Citation statistics
Document Type会议论文
Identifierhttp://ir.sia.cn/handle/173321/17390
Collection工业控制网络与系统研究室
Corresponding AuthorLi HP(李鹤鹏)
Affiliation1.Lab. of Networked Control Systems, Shenyang Institute of Automation, Chinese Academy of Sciences, Shenyang, China
2.University of Chinese Academy of Sciences, Beijing, China
Recommended Citation
GB/T 7714
Li HP,Zang CZ,Zeng P,et al. A genetic algorithm-based hybrid optimization approach for microgrid energy management[C]. Piscataway, NJ, USA:IEEE,2015:1474-1478.
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