Microgrid Distributed Frequency Control over Time-Varying Communication Networks

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

Abstract

In this paper, we study AC microgrid dynamics under a completely decentralized primary control, and a secondary frequency control the implementation of which is distributed over a communication network with communication links that are time-varying and can be (i) bidirectional, or (ii) unidirectional. For a certain class of controllers, the closed-loop system dynamics solve a certain multi-agent optimization problem by performing two steps: (i) gradient-descent, and (ii) distributed averaging. The proposed framework allows to explore many of the existing distributed algorithms developed for solving general multi-agent optimization problems over time-varying communication networks. In particular, we use the subgradient-push algorithm to design a distributed frequency controller, and we present the convergence analysis for the closed-loop system. We also dwell on this framework and propose a distributed frequency controller that does not require agents (power generators) to know their out-degree, which is a necessary assumption for the convergence of the subgradient-push algorithm.

Original languageEnglish (US)
Title of host publication2018 IEEE Conference on Decision and Control, CDC 2018
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages5722-5727
Number of pages6
ISBN (Electronic)9781538613955
DOIs
StatePublished - Jul 2 2018
Event57th IEEE Conference on Decision and Control, CDC 2018 - Miami, United States
Duration: Dec 17 2018Dec 19 2018

Publication series

NameProceedings of the IEEE Conference on Decision and Control
Volume2018-December
ISSN (Print)0743-1546
ISSN (Electronic)2576-2370

Conference

Conference57th IEEE Conference on Decision and Control, CDC 2018
Country/TerritoryUnited States
CityMiami
Period12/17/1812/19/18

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Modeling and Simulation
  • Control and Optimization

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