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A simple peak shifting DSM (demand-side management) strategy for residential water heaters

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  • Atikol, Uğur

Abstract

In many developing countries due to lack of infrastructure the utilities experience difficulties in monitoring their customers' demand or time of use of electricity and hence it is very difficult to apply DSM (demand-side management) programs for peak shifting. In several of these countries the residential EWHs (electric water heaters) are usually responsible for the evening peak. The general attitude of people is to turn them on just before they need hot water and statistics have shown that this takes place in the evening hours constituting the evening peak. The present work reviews the experimental findings about the static and dynamic cooling behavior of hot water in storage tanks and discusses the possible timer programs to avoid the peak hours. It is deduced from the experiments that even when the hot water is kept standing in a tank for 12 h after the initial withdrawal of 64.2 L, it would be possible to have warm water at temperatures above 40 °C in the top 15% of the tank to utilize. If the DSM programs are carefully designed it would be possible to set the timers to operate the EWHs for once or twice a day to meet the daily demand of households.

Suggested Citation

  • Atikol, Uğur, 2013. "A simple peak shifting DSM (demand-side management) strategy for residential water heaters," Energy, Elsevier, vol. 62(C), pages 435-440.
    • Handle: RePEc:eee:energy:v:62:y:2013:i:c:p:435-440
    DOI: 10.1016/j.energy.2013.09.052
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    Cited by:

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    3. Azzopardi, Brian & Gabriel-Buenaventura, Alejandro, 2014. "Feasibility assessment for high penetration of distributed photovoltaics based on net demand planning," Energy, Elsevier, vol. 76(C), pages 233-240.
    4. Linas Gelažanskas & Kelum A. A. Gamage, 2016. "Distributed Energy Storage Using Residential Hot Water Heaters," Energies, MDPI, vol. 9(3), pages 1-13, February.
    5. Ahammed, Md. Tanvir & Khan, Imran, 2022. "Ensuring power quality and demand-side management through IoT-based smart meters in a developing country," Energy, Elsevier, vol. 250(C).
    6. Kotur, Dimitrije & Đurišić, Željko, 2017. "Optimal spatial and temporal demand side management in a power system comprising renewable energy sources," Renewable Energy, Elsevier, vol. 108(C), pages 533-547.
    7. Jack, M.W. & Suomalainen, K. & Dew, J.J.W. & Eyers, D., 2018. "A minimal simulation of the electricity demand of a domestic hot water cylinder for smart control," Applied Energy, Elsevier, vol. 211(C), pages 104-112.
    8. Armstrong, P. & Ager, D. & Thompson, I. & McCulloch, M., 2014. "Improving the energy storage capability of hot water tanks through wall material specification," Energy, Elsevier, vol. 78(C), pages 128-140.
    9. Farzamkia, Saleh & Ranjbar, Hossein & Hatami, Alireza & Iman-Eini, Hossein, 2016. "A novel PSO (Particle Swarm Optimization)-based approach for optimal schedule of refrigerators using experimental models," Energy, Elsevier, vol. 107(C), pages 707-715.
    10. Jalali, Mohammad Majid & Kazemi, Ahad, 2015. "Demand side management in a smart grid with multiple electricity suppliers," Energy, Elsevier, vol. 81(C), pages 766-776.
    11. Matthias Eydner & Lu Wan & Tobias Henzler & Konstantinos Stergiaropoulos, 2022. "Real-Time Grid Signal-Based Energy Flexibility of Heating Generation: A Methodology for Optimal Scheduling of Stratified Storage Tanks," Energies, MDPI, vol. 15(5), pages 1-31, February.
    12. Atikol, U. & Aldabbagh, L.B.Y., 2015. "The impact of two-stage discharging on the exergoeconomic performance of a storage-type domestic water-heater," Energy, Elsevier, vol. 83(C), pages 379-386.

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