Distributed Energy Optimization in MAS-based Microgrids using Asynchronous ADMM

Md Habib Ullah, Jae Do Park

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

11 Scopus citations

Abstract

This paper proposes a scalable distributed energy management system for multi-agent system (MAS)-based microgrids under communication delay. In the proposed approach, the centralized convex optimization problem of a microgrid with distributed energy resources is decomposed into sub-problems solved iteratively by the respective agents in a distributive manner using privacy-preserving asynchronous alternating direction method of multipliers (ADMM) algorithm. In this algorithm, each agent accumulates the sub-system updates from local controllers and only shares partial information with the adjacent agents while minimizing the aggregated operational cost of the microgrid in a cooperative mode. The numerical result shows that the algorithm can reach the convergence very fast under various conditions. The optimality of this algorithm was analyzed briefly and its effectiveness was compared with the synchronous ADMM algorithm.

Original languageEnglish (US)
Title of host publication2019 IEEE Power and Energy Society Innovative Smart Grid Technologies Conference, ISGT 2019
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781538682326
DOIs
StatePublished - Feb 2019
Event2019 IEEE Power and Energy Society Innovative Smart Grid Technologies Conference, ISGT 2019 - Washington, United States
Duration: Feb 18 2019Feb 21 2019

Publication series

Name2019 IEEE Power and Energy Society Innovative Smart Grid Technologies Conference, ISGT 2019

Conference

Conference2019 IEEE Power and Energy Society Innovative Smart Grid Technologies Conference, ISGT 2019
Country/TerritoryUnited States
CityWashington
Period2/18/192/21/19

All Science Journal Classification (ASJC) codes

  • Artificial Intelligence
  • Hardware and Architecture
  • Energy Engineering and Power Technology
  • Electrical and Electronic Engineering
  • Control and Optimization
  • Strategy and Management

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