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A survey of distributed optimization
Yang, Tao1; Yi, Xinlei2; Wu, Junfeng3; Yuan, Ye4,5; Wu, Di6; Meng, Ziyang7,8; Hong, Yiguang9; Wang, Hong10; Lin, Zongli11; Johansson, Karl H.2
AbstractIn distributed optimization of multi-agent systems, agents cooperate to minimize a global function which is a sum of local objective functions. Motivated by applications including power systems, sensor networks, smart buildings, and smart manufacturing, various distributed optimization algorithms have been developed. In these algorithms, each agent performs local computation based on its own information and information received from its neighboring agents through the underlying communication network, so that the optimization problem can be solved in a distributed manner. This survey paper aims to offer a detailed overview of existing distributed optimization algorithms and their applications in power systems. More specifically, we first review discrete-time and continuous-time distributed optimization algorithms for undirected graphs. We then discuss how to extend these algorithms in various directions to handle more realistic scenarios. Finally, we focus on the application of distributed optimization in the optimal coordination of distributed energy resources. (C) 2019 Elsevier Ltd. All rights reserved.
KeywordDistributed optimization Coordination of distributed energy resources
Funding ProjectU.S. Department of Energy[DE-AC05-00OR22725] ; Department of Energy
WOS Research AreaAutomation & Control Systems
WOS SubjectAutomation & Control Systems
WOS IDWOS:000474680200022
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Document Type期刊论文
Corresponding AuthorYuan, Ye
Affiliation1.Univ North Texas, Dept Elect Engn, Denton, TX 76203 USA
2.KTH Royal Inst Technol, Sch Elect Engn & Comp Sci, Div Decis & Control Syst, S-10044 Stockholm, Sweden
3.Zhejiang Univ, Coll Control Sci & Engn, Hangzhou 310027, Zhejiang, Peoples R China
4.Huazhong Univ Sci & Technol, Sch Artificial Intelligence & Automat, Wuhan 430074, Hubei, Peoples R China
5.Huazhong Univ Sci & Technol, State Key Lab Digital Mfg Equipment & Technol, Wuhan 430074, Hubei, Peoples R China
6.Pacific Northwest Natl Lab, Richland, WA 99352 USA
7.Tsinghua Univ, Dept Precis Instrument, Beijing 100084, Peoples R China
8.Tsinghua Univ, State Key Lab Precis Measurement Technol & Instru, Beijing 100084, Peoples R China
9.Chinese Acad Sci, Inst Syst Sci, Key Lab Syst & Control, Beijing 100190, Peoples R China
10.Oak Ridge Natl Lab, Oak Ridge, TN 37932 USA
11.Univ Virginia, Charles L Brown Dept Elect & Comp Engn, Charlottesville, VA 22904 USA
Recommended Citation
GB/T 7714
Yang, Tao,Yi, Xinlei,Wu, Junfeng,et al. A survey of distributed optimization[J]. ANNUAL REVIEWS IN CONTROL,2019,47:278-305.
APA Yang, Tao.,Yi, Xinlei.,Wu, Junfeng.,Yuan, Ye.,Wu, Di.,...&Johansson, Karl H..(2019).A survey of distributed optimization.ANNUAL REVIEWS IN CONTROL,47,278-305.
MLA Yang, Tao,et al."A survey of distributed optimization".ANNUAL REVIEWS IN CONTROL 47(2019):278-305.
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