Skip to main navigation Skip to search Skip to main content

A Finite-Time Distributed Optimization Algorithm for Economic Dispatch in Smart Grids

  • Shuai Mao
  • , Ziwei Dong
  • , Paul Schultz
  • , Yang Tang*
  • , Ke Meng
  • , Zhao Yang Dong
  • , Feng Qian
  • *Corresponding author for this work

Research output: Journal Publications and ReviewsRGC 21 - Publication in refereed journalpeer-review

Abstract

The economic dispatch problem (EDP) is one of the fundamental and important problems in power systems. The objective of EDP is to determine the output generation of generators to minimize the total generation cost under various constraints. In this article, a finite-time consensus-based distributed optimization algorithm is proposed to solve EDP. It is only required that each device in the communication network has access to its own local generation cost function, designed virtual local demand and its neighbors' local optimization variables. The proposed finite-time algorithm can solve EDP, if the gain parameters in the algorithm satisfy some conditions under undirected and connected time-varying graphs. Moreover, the bounded or linear increasing assumption on the gradient and subgradient of objecive functions is relaxed in this algorithm. Examples under several cases are provided to verify the effectiveness of the proposed distributed optimization algorithm. © 2019 IEEE.
Original languageEnglish
Pages (from-to)2068-2079
JournalIEEE Transactions on Systems, Man, and Cybernetics: Systems
Volume51
Issue number4
Online published19 Aug 2019
DOIs
Publication statusPublished - Apr 2021
Externally publishedYes

Research Keywords

  • Consensus
  • distributed optimization algorithm
  • economic dispatch
  • finite time
  • smart grids

Policy Impact

  • Cited in Policy Documents

Fingerprint

Dive into the research topics of 'A Finite-Time Distributed Optimization Algorithm for Economic Dispatch in Smart Grids'. Together they form a unique fingerprint.

Cite this