LAPSE:2018.0516
Published Article
LAPSE:2018.0516
A Fully Distributed Approach for Economic Dispatch Problem of Smart Grid
September 21, 2018
The cooperative, reliable and responsive characteristics make smart grid more popular than traditional power grid. However, with the extensive employment of smart grid concepts, the traditional centralized control methods expose a lot of shortcomings, such as communication congestion, computing complexity in central management systems, and so on. The distributed control method with flexible characteristics can meet the timeliness and effectiveness of information management in smart grid and ensure the information collection timely and the power dispatch economically. This article presents a decentralized approach based on multi agent system (MAS) for solving data collection and economic dispatch problem of smart grid. First, considering the generators and loads are distributed on many nodes in the space, a flooding-based consensus algorithm is proposed to achieve generator and load information for each agent. Then, a suitable distributed algorithm called λ-consensus is used for solving the economic dispatch problem, eventually, all generators can automatically minimize the total cost in a collective sense. Simulation results in standard test cases are presented to demonstrate the effectiveness of the proposed control strategy.
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Keywords
consensus algorithm, distributed control, economic dispatch problem, optimal resource management, Sensor data collection
Subject
Suggested Citation
Li B, Wang Y, Li J, Cao S. A Fully Distributed Approach for Economic Dispatch Problem of Smart Grid. (2018). LAPSE:2018.0516
Author Affiliations
Li B: School of Automation Engineering, Northeast Electric Power University, Jilin 132012, China
Wang Y: School of Automation Engineering, Northeast Electric Power University, Jilin 132012, China
Li J: School of Automation Engineering, Northeast Electric Power University, Jilin 132012, China
Cao S: School of Automation Engineering, Northeast Electric Power University, Jilin 132012, China
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Wang Y: School of Automation Engineering, Northeast Electric Power University, Jilin 132012, China
Li J: School of Automation Engineering, Northeast Electric Power University, Jilin 132012, China
Cao S: School of Automation Engineering, Northeast Electric Power University, Jilin 132012, China
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Journal Name
Energies
Volume
11
Issue
8
Article Number
E1993
Year
2018
Publication Date
2018-08-01
Published Version
ISSN
1996-1073
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Original Submission
Other Meta
PII: en11081993, Publication Type: Journal Article
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Published Article
LAPSE:2018.0516
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External Link
doi:10.3390/en11081993
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[v1] (Original Submission)
Sep 21, 2018
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Sep 21, 2018
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https://psecommunity.org/LAPSE:2018.0516
Original Submitter
Calvin Tsay
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