Multi-period OPF with energy storages and renewable sources: A parallel moment approach

Chao Duan, Lin Jiang, Wanliang Fang, Jun Liu

Research output: Chapter in Book/Report/Conference proceedingConference contribution

5 Scopus citations

Abstract

Multi-period optimal power flow (OPF) is a basic tool to achieve optimal operation of a power system with energy storages devices and renewable sources. A novel convex relaxation based decomposeition algorithm is proposed in this paper to solve the full AC multi-period OPF with energy storages and renewable sources. Based on alternating direction method of multipliers (ADMM), the original time-correlated non-convex optimization problem is decomposed into two subproblems. The first subproblem is non-convex and separable among different time slots. Moment relaxation can be constructed and solved for each time slot in parallel. The second subproblem is a convex quadratic program (QP) and separable among different buses, which can be solved in parallel by standard interior point (IPM) solver. Case study on a benchmark system demonstrates the effectiveness of the proposed algorithm.

Original languageEnglish (US)
Title of host publication2016 IEEE Power and Energy Society General Meeting, PESGM 2016
PublisherIEEE Computer Society
ISBN (Electronic)9781509041688
DOIs
StatePublished - Nov 10 2016
Event2016 IEEE Power and Energy Society General Meeting, PESGM 2016 - Boston, United States
Duration: Jul 17 2016Jul 21 2016

Publication series

NameIEEE Power and Energy Society General Meeting
Volume2016-November
ISSN (Print)1944-9925
ISSN (Electronic)1944-9933

Conference

Conference2016 IEEE Power and Energy Society General Meeting, PESGM 2016
CountryUnited States
CityBoston
Period7/17/167/21/16

Keywords

  • Alternating direction method of multipliers
  • Correlative sparsity
  • Energy Storage
  • Moment relaxation
  • Optimal power flow
  • Polynomial optimization
  • Renewable Energy

ASJC Scopus subject areas

  • Energy Engineering and Power Technology
  • Nuclear Energy and Engineering
  • Renewable Energy, Sustainability and the Environment
  • Electrical and Electronic Engineering

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