Distributed Consensus Control of Thermostatically Controlled Loads for Fast Ancillary Services

Yu Wang, Yan Xu, Zhao Xu, Junhua Zhao, Jing Qiu, Ke Meng, Yu Zheng

Research output: Chapter in book / Conference proceedingConference article published in proceeding or bookAcademic researchpeer-review


In this paper, thermostatically controlled loads (TCLs) to the provision of fast ancillary services are investigated. In a residential community, a population of TCLs in smart buildings is able to respond to fast regulation signals in a distributed way via sparse communication infrastructure. A two-layer distributed consensus protocol (TLDCP) is proposed with the optimal control gain design based on the linear quadratic regulator method. In the proposed TLDCP, the communication graph is divided into two-layer considering both the local interaction of TCLs in each building and interconnection among buildings. This method will achieve fast, dynamic and distributed power regulation with fair power and comfort sharing among all participate TCLs. With different supervisory control (e.g. fluctuation mitigation and frequency regulation), the TLDCP controlled TCLs can provide various grid ancillary services. The case studies validate the effectiveness of the proposed method.

Original languageEnglish
Title of host publicationProceedings of the 31st Chinese Control and Decision Conference, CCDC 2019
PublisherInstitute of Electrical and Electronics Engineers Inc.
Number of pages6
ISBN (Electronic)9781728101057
Publication statusPublished - Jun 2019
Event31st Chinese Control and Decision Conference, CCDC 2019 - Nanchang, China
Duration: 3 Jun 20195 Jun 2019

Publication series

NameProceedings of the 31st Chinese Control and Decision Conference, CCDC 2019


Conference31st Chinese Control and Decision Conference, CCDC 2019


  • demand response
  • Distributed consensus control
  • grid ancillary services
  • thermostatically controlled loads

ASJC Scopus subject areas

  • Decision Sciences(all)
  • Control and Systems Engineering
  • Control and Optimization

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