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Distributed Event-Triggered Scheme for Economic Dispatch in Smart Grids

  • Chaojie Li
  • , Xinghuo Yu
  • , Wenwu Yu
  • , Tingwen Huang
  • , Zhi-Wei Liu

Research output: Journal Publications and Reviews › RGC 21 - Publication in refereed journal › peer-review

Abstract

To reduce information exchange requirements in smart grids, an event-triggered communication-based distributed optimization is proposed for economic dispatch. In this work, the θ-logarithmic barrier-based method is employed to reformulate the economic dispatch problem, and the consensus-based approach is considered for developing fully distributed technology-enabled algorithms. Specifically, a novel distributed algorithm utilizes the minimum connected dominating set (CDS), which efficiently allocates the task of balancing supply and demand for the entire power network at the beginning of economic dispatch. Further, an event-triggered communication-based method for the incremental cost of each generator is able to reach a consensus, coinciding with the global optimality of the objective function. In addition, a fast gradient-based distributed optimization method is also designed to accelerate the convergence rate of the event-triggered distributed optimization. Simulations based on the IEEE 57-bus test system demonstrate the effectiveness and good performance of proposed algorithms. © 2005-2012 IEEE.
Original languageEnglish
Pages (from-to)1775-1785
JournalIEEE Transactions on Industrial Informatics
Volume12
Issue number5
DOIs
Publication statusPublished - 1 Oct 2016
Externally publishedYes

Bibliographical note

Publication details (e.g. title, author(s), publication statuses and dates) are captured on an “AS IS” and “AS AVAILABLE” basis at the time of record harvesting from the data source. Suggestions for further amendments or supplementary information can be sent to [email protected].

Funding

This work was supported in part by the Australian Research Council (ARC) Discovery Scheme under Grant 140100544, in part by the National Natural Science Foundation of China under Grant 61322302 and Grant 61304152, in part by the Six Talent Peaks of Jiangsu Province of China under Grant 2014-DZXX-004, and in part by National Priority Research Project (NPRP) from the Qatar National Research Fund (a member of Qatar Foundation) under Grant NPRP 4-1162-1-181. Paper no. TII-15-0522.

Research Keywords

  • Distributed optimization
  • economic dispatch
  • event-triggered
  • fast gradient
  • minimum connected dominating set (CDS)

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