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Demand response control for the installed inverter air conditioners based on hierarchical model predictive control.

Number: 0490

Author(s) : WANG C., WANG B., ZHAO Z.

Summary

The supply-demand imbalance of electricity is burdened by the penetration of Renewable Energy Sources. Air conditioners (ACs) in residential buildings have great potential for demand response (DR) due to their load flexibility and a high share of peak electricity consumption. Model predictive control (MPC) is suitable for unlocking the flexibility of residential buildings to realize DR by responding to electricity prices. However, operating MPC requires high computing power, making it difficult to be applied in installed ACs. A hierarchical MPC (HMPC) is proposed to realize DR for ACs in residential buildings, and it can utilize cloud-based infrastructure or the Internet of Things, thereby avoiding limitations imposed by local computing power. To investigate the performance of HMPC, a testbed is built in Matlab/Simulink and Simscape environments. The simulation results show that HMPC outperforms the hierarchical controller with a rule-based upper controller in shifting and shaving peak power.

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Pages: 9

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Details

  • Original title: Demand response control for the installed inverter air conditioners based on hierarchical model predictive control.
  • Record ID : 30031860
  • Languages: English
  • Subject: Technology
  • Source: Proceedings of the 26th IIR International Congress of Refrigeration: Paris , France, August 21-25, 2023.
  • Publication date: 2023/08/21
  • DOI: http://dx.doi.org/10.18462/iir.icr.2023.0490

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