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Optimal control and energy efficiency evaluation of district ice storage system

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  • Cao, Hui
  • Lin, Jiajing
  • Li, Nan

Abstract

Accurate cooling load forecasting and optimal control strategy for the energy management of district ice storage system (DISS) are two key factors in improving performance and achieving energy cost savings. This work constructs Similar Days (SD) Algorithm to screen and reduce the dimension of the training samples. The SD-based Support Vector Regression (SVR) model shows superiority in hourly forecasting accuracy compared with single models. Further, the Moth-Flame Optimization (MFO) is introduced for hyperparameters optimization, which improves the accuracy and greatly reduces the daily cumulative error, enabling to implement optimal control during the cooling period and to charge ice storage tank (IST) to appropriate amount after midnight.

Suggested Citation

  • Cao, Hui & Lin, Jiajing & Li, Nan, 2023. "Optimal control and energy efficiency evaluation of district ice storage system," Energy, Elsevier, vol. 276(C).
    • Handle: RePEc:eee:energy:v:276:y:2023:i:c:s0360544223009921
    DOI: 10.1016/j.energy.2023.127598
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