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Day-ahead schedule optimization of household appliances for demand flexibility: Case study on PV/T powered buildings

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  • Wang, Chuyao
  • Ji, Jie
  • Yang, Hongxing

Abstract

Employing the demand flexibility strategy in PV powered buildings can effectively balance solar energy supply and building energy demand, thereby increasing the self-consumption ratio of PV electricity. Despite this, its solar energy utilization is still low due to the limit of the PV efficiency. On the other hand, PV/T modules not only generate electricity but also produce domestic hot water, thus providing higher solar efficiency. In this study, the demand flexibility of various shiftable appliances in a PV/T powered building was investigated. An optimization-based demand flexibility strategy was proposed to reduce electricity cost and maximum grid power. The case study showed that the proposed strategy could reduce the electricity cost by 23 % and smooth grid power fluctuation. Moreover, compared with the PV powered building, the PV/T powered building could reduce the electricity cost by 10 % and significantly improve utility grid friendliness. Furthermore, the forecast error of boundary conditions negatively affected the electricity cost and grid power fluctuations. The sensitivity analysis revealed that the ambient temperature and solar irradiation on the PV/T modules had a greater impact on the optimization objective. Overall, this work aims to provide guidance for planning the flexibility operation of PV/T powered buildings.

Suggested Citation

  • Wang, Chuyao & Ji, Jie & Yang, Hongxing, 2024. "Day-ahead schedule optimization of household appliances for demand flexibility: Case study on PV/T powered buildings," Energy, Elsevier, vol. 289(C).
    • Handle: RePEc:eee:energy:v:289:y:2024:i:c:s0360544223034369
    DOI: 10.1016/j.energy.2023.130042
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    Cited by:

    1. Wang, Chuyao & Ji, Jie & Song, Zhiying & Ke, Wei, 2024. "Performance analysis and capacity configuration of building energy system integrated with PV/T technology under different operation strategies," Energy, Elsevier, vol. 293(C).

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