A fully distributed asynchronous approach for multi-area coordinated network-constrained unit commitment

Yamin Wang, Lei Wu, Jie Li

Research output: Contribution to journalArticlepeer-review

10 Scopus citations

Abstract

This paper discusses a consensus-based alternating direction method of multipliers (ADMM) approach to solve the multi-area coordinated network-constrained unit commitment (NCUC) problem in a distributed manner. Due to political and technical difficulties, it is neither practical nor feasible to solve the multi-area coordination problem in a centralized fashion, which requires full access to all the data of individual areas. In comparison, in the proposed fully distributed approach, local NCUC problems of individual areas can be solved independently, and only limited information is exchanged among adjacent areas to facilitate the multi-area coordination. Furthermore, since traditional ADMM can guarantee convergence only for convex problems, this paper discusses several strategies to mitigate oscillations, enhance convergence performance, and derive good-enough feasible solutions, including: (1) a tie-line power-flow-based area coordination strategy is designed to reduce the number of global consensus variables; (2) different penalty parameters ρ are assigned to individual consensus variables and are updated via certain rules during the iterative procedure, which reduces the impact of the initial values of ρ on the convergence performance; (3) heuristic rules are adopted to fix certain unit commitment variables to avoid oscillations during the iterative procedure; and (4) an asynchronous distributed strategy is studied, which solves NCUC subproblems of small areas multiple times and exchanges information with adjacent areas more frequently within one complete run of slower NCUC subproblems of large areas. Numerical cases illustrate the effectiveness of the proposed asynchronous fully distributed NCUC approach, and we investigate key factors that would affect its convergence performance.

Original languageEnglish (US)
Pages (from-to)419-452
Number of pages34
JournalOptimization and Engineering
Volume19
Issue number2
DOIs
StatePublished - Jun 1 2018
Externally publishedYes

All Science Journal Classification (ASJC) codes

  • Software
  • Civil and Structural Engineering
  • Aerospace Engineering
  • Mechanical Engineering
  • Control and Optimization
  • Electrical and Electronic Engineering

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