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Multi-Period Stochastic Economic Dispatch of Microgrid Considering Renewable Energy Uncertainty Using Parallel Algorithm

  • Bo Feng
  • , Hongyu Yang
  • , Qingrun Yang
  • , Tao Ding
  • , Haixiang Zang
  • State Grid Lianyungang Electric Power Supply Company
  • Xi'an Jiaotong University
  • Hohai University

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

3 Scopus citations

Abstract

In recent years, microgirds (MGs) have gained sustained attractions among the researches. The economic dispatch is one of the most important topics of the MGs. For the fast real-time dispatch, the number of time periods may become larger and the computational complexity will rapidly increase. To handle this issue, a parallel algorithm for the multi-period economic dispatch of the MGs is proposed in this paper, which can decompose the original problem into several small-scale sub-problems that can be efficiently solved in parallel. Moreover, the model is designed in a stochastic scheme to handle the uncertainty of renewable energy sources (RES) output. Case studies verify the effectiveness of the proposed parallel algorithm.

Original languageEnglish
Title of host publication2019 IEEE PES Innovative Smart Grid Technologies Asia, ISGT 2019
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages3185-3189
Number of pages5
ISBN (Electronic)9781728135205
DOIs
StatePublished - May 2019
Event2019 IEEE PES Innovative Smart Grid Technologies Asia, ISGT 2019 - Chengdu, China
Duration: 21 May 201924 May 2019

Publication series

Name2019 IEEE PES Innovative Smart Grid Technologies Asia, ISGT 2019

Conference

Conference2019 IEEE PES Innovative Smart Grid Technologies Asia, ISGT 2019
Country/TerritoryChina
CityChengdu
Period21/05/1924/05/19

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 7 - Affordable and Clean Energy
    SDG 7 Affordable and Clean Energy

Keywords

  • Economic dispatch
  • microgrid
  • parallel algorithm
  • stochastic method

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