Field test and evaluation of model predictive control in a grid-interactive thermal energy storage integrated heat pump system.

Number: 3530

Author(s) : QIAO Y., LIU X., DONG J., SHI L., WANG L., CUI B., QU M.

Summary

The grid-interactive heat pump (HP) system is designed to participate in demand response programs, thereby contributing to grid stability. Considering this, thermal energy storage (TES) incorporated with the grid-interactive HP has gained increasing attention due to its capacity for load shifting, energy cost reduction, and improved system flexibility. Efficient management of the TES charge and discharge processes, which is crucial for minimizing total energy costs, requires consideration of various factors such as electricity costs, weather data, and building cooling loads. Therefore, an intelligent control becomes essential for optimizing TES utilization in grid-interactive buildings. In this study, a dynamic model for controlling the TES integrated HP system was developed based on experimental data. A model predictive control (MPC) based on the dynamic programming method was then developed to optimize the performance of the HP-TES system, ensuring both reduced electrical costs and sustained human comfort. This optimal control was evaluated by comparing with a rule-based control (RBC) through field tests in a real building. The results demonstrate that the proposed optimal control strategy exhibits intelligent system operation management by selecting different operation modes under various circumstances. Compared with RBC, it can achieve a 21% decrease in energy consumption in the field test. This paper provides insights for smart control for the grid-interactive HP system.

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Pages: 9 p.

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Details

  • Original title: Field test and evaluation of model predictive control in a grid-interactive thermal energy storage integrated heat pump system.
  • Record ID : 30032919
  • Languages: English
  • Subject: Technology
  • Source: 2024 Purdue Conferences. 8th International High Performance Buildings Conference at Purdue.
  • Publication date: 2024/07/15

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