A novel distributed control framework for thermostatically controlled loads cluster

Abstract Renewable energy is developing rapidly, and its intermittency and uncertainty pose a serious challenge to the grid’s regulation capability. Demand response, as a crucial means of integrating flexible load-side resources, has become a key technology in alleviating grid pressure. This paper f...

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Main Authors: Yiyan Zheng, Zhenwei Yu, Li Ding
Format: Article
Language:English
Published: Springer 2025-06-01
Series:Discover Artificial Intelligence
Subjects:
Online Access:https://doi.org/10.1007/s44163-025-00368-9
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author Yiyan Zheng
Zhenwei Yu
Li Ding
author_facet Yiyan Zheng
Zhenwei Yu
Li Ding
author_sort Yiyan Zheng
collection DOAJ
description Abstract Renewable energy is developing rapidly, and its intermittency and uncertainty pose a serious challenge to the grid’s regulation capability. Demand response, as a crucial means of integrating flexible load-side resources, has become a key technology in alleviating grid pressure. This paper focuses on thermostatically controlled loads and proposes a novel distributed control framework. The framework decouples the load control loop by dividing the control process into a short distributed coordination phase and a long local tracking phase. This approach significantly reduces communication requirements of the load nodes. Through mathematical derivations, numerical simulations, and hardware-in-the-loop experiments, the theoretical feasibility and practical effectiveness of the proposed framework are validated.
format Article
id doaj-art-48f85a2ed55749d89b0485f2d8f3ffa0
institution Kabale University
issn 2731-0809
language English
publishDate 2025-06-01
publisher Springer
record_format Article
series Discover Artificial Intelligence
spelling doaj-art-48f85a2ed55749d89b0485f2d8f3ffa02025-08-20T03:47:16ZengSpringerDiscover Artificial Intelligence2731-08092025-06-015111810.1007/s44163-025-00368-9A novel distributed control framework for thermostatically controlled loads clusterYiyan Zheng0Zhenwei Yu1Li Ding2School of Electrical Engineering and Automation, Wuhan UniversitySchool of Electrical Engineering and Automation, Wuhan UniversitySchool of Electrical Engineering and Automation, Wuhan UniversityAbstract Renewable energy is developing rapidly, and its intermittency and uncertainty pose a serious challenge to the grid’s regulation capability. Demand response, as a crucial means of integrating flexible load-side resources, has become a key technology in alleviating grid pressure. This paper focuses on thermostatically controlled loads and proposes a novel distributed control framework. The framework decouples the load control loop by dividing the control process into a short distributed coordination phase and a long local tracking phase. This approach significantly reduces communication requirements of the load nodes. Through mathematical derivations, numerical simulations, and hardware-in-the-loop experiments, the theoretical feasibility and practical effectiveness of the proposed framework are validated.https://doi.org/10.1007/s44163-025-00368-9Thermostatically controlled loadsDistributed controlComfort level sharingPrescribed-time consensus
spellingShingle Yiyan Zheng
Zhenwei Yu
Li Ding
A novel distributed control framework for thermostatically controlled loads cluster
Discover Artificial Intelligence
Thermostatically controlled loads
Distributed control
Comfort level sharing
Prescribed-time consensus
title A novel distributed control framework for thermostatically controlled loads cluster
title_full A novel distributed control framework for thermostatically controlled loads cluster
title_fullStr A novel distributed control framework for thermostatically controlled loads cluster
title_full_unstemmed A novel distributed control framework for thermostatically controlled loads cluster
title_short A novel distributed control framework for thermostatically controlled loads cluster
title_sort novel distributed control framework for thermostatically controlled loads cluster
topic Thermostatically controlled loads
Distributed control
Comfort level sharing
Prescribed-time consensus
url https://doi.org/10.1007/s44163-025-00368-9
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