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Energy consumption analysis of residential swimming pools for peak load shaving

Author

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  • Song, Chunhe
  • Jing, Wei
  • Zeng, Peng
  • Yu, Haibin
  • Rosenberg, Catherine

Abstract

Peak load shaving is a very important issue, however, most of peak load shaving methods either require extra investments or reduce the comfort of the consumers. This paper analyzes the impact of circulating pumps of residential swimming pools on the peak load, and shows that shifting the active time of circulating pumps of residential swimming pools could shave the peak load without requiring extra investments or reducing the comfort of the consumers. First, based on an extensive dataset containing hourly energy consumption readings of 1005 residents during March 2011 and October 2012 in South Ontario, this paper analyzes the features of the energy consumptions of residents with and without swimming pools. Second, this paper proposes a novel non-intrusive appliance load monitoring method to estimate the energy consumption of circulating pumps of residential swimming pools. The advantages of the proposed method are that, compared with other non-intrusive appliance load monitoring methods, it does not require high sampling rate data or prior information of the appliance, therefore the cost of implementation is reduced and users’ privacy is protected. Finally, this paper shows that, the average hourly energy consumption of CPRSP is 0.7429 kW h. During the peak hour, circulating pumps of residential swimming pools contributes 20.11% energy consumption of residents with swimming pools, as well as 8.79% peak load of all neighborhoods. When considering minimizing the peak load, by postponing circulating pumps of residential swimming pools for 8 h rather than turn them off, the peak load can be shaved by 4.64%. When considering minimizing the cost of circulating pumps of residential swimming pools, the peak load can be shaved by 3.15% by postponing circulating pumps of residential swimming pools for 6 h, meanwhile the peak hour is postponed from 18:00 to 19:00.

Suggested Citation

  • Song, Chunhe & Jing, Wei & Zeng, Peng & Yu, Haibin & Rosenberg, Catherine, 2018. "Energy consumption analysis of residential swimming pools for peak load shaving," Applied Energy, Elsevier, vol. 220(C), pages 176-191.
  • Handle: RePEc:eee:appene:v:220:y:2018:i:c:p:176-191
    DOI: 10.1016/j.apenergy.2018.03.094
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    7. Olszewski, Pawel & Arafeh, Jamal, 2018. "Parametric analysis of pumping station with parallel-configured centrifugal pumps towards self-learning applications," Applied Energy, Elsevier, vol. 231(C), pages 1146-1158.
    8. Yiran Wang & Shuowei Jin & Ming Cheng, 2023. "A Convolution–Non-Convolution Parallel Deep Network for Electricity Theft Detection," Sustainability, MDPI, vol. 15(13), pages 1-22, June.

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