Fixed-Time Hierarchical Distributed Control for Flexible Thermostatically Controlled Loads

Mi, Zilong, Kong, Zhengmin, Huang, Tao, Shi, Peng, Yu, Zhenwei, and Ding, Li (2024) Fixed-Time Hierarchical Distributed Control for Flexible Thermostatically Controlled Loads. IEEE Systems Journal, 18 (2). pp. 1344-1355.

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Abstract

With the growing integration of unpredictable renewable energy sources into the grid, achieving power balance has become an increasingly crucial challenge. To address this challenge, demand response has emerged as a promising solution. This article proposes a new demand-side flexible thermostatically controlled loads response strategy framework. Our method employs a hierarchical control framework that covers three layers of control, which consist of the optimization layer, coordination layer, and local control layer. The optimization layer employs a dynamic average consensus algorithm for economic optimization scheduling to maximize the sum of the aggregators' welfare functions. In the coordination layer, power is distributed fairly based on the comfort state, generating reference signals for the local control layer. The local control layer tracks these reference signals and employs integral sliding mode control to suppress the influence of unknown disturbances. The control objectives of the entire framework can be achieved in a fixed time, and the parameters in the framework are heterogeneous. Furthermore, the relationships between controller parameters and tracking performance are derived, and the upper bounds of settling time are estimated. Finally, we demonstrate the validity of our theoretical results through numerical simulations.

Item ID: 85845
Item Type: Article (Research - C1)
ISSN: 1937-9234
Copyright Information: © 2024 IEEE.
Date Deposited: 17 Jun 2025 01:21
FoR Codes: 40 ENGINEERING > 4010 Engineering practice and education > 401006 Systems engineering @ 100%
SEO Codes: 17 ENERGY > 1703 Energy storage, distribution and supply > 170399 Energy storage, distribution and supply not elsewhere classified @ 100%
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