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Demand side management of an urban water supply using wholesale electricity price

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  • Kernan, R.
  • Liu, X.
  • McLoone, S.
  • Fox, B.

Abstract

Municipal water supply consumes large quantities of electrical energy to move water from catchment areas to service reservoirs near centres of population. Pumping does not necessarily occur round the clock, but rather when necessary to uphold constraints relating to reservoir levels and system pressure. There is a degree of flexibility in the timing of pumping that makes it an excellent candidate for Demand Side Management, meaning that it can provide opportunities for improving power system operation and reducing electricity costs for the water utility. The extent of this flexibility depends on a number of factors. This study examines the optimisation of two water supply systems - the ‘Van Zyl’ benchmark system and a representation of the supply for the city of Belfast, Northern Ireland. The potential to employ intelligent operation of pumps to help bolster uptake of variable wind generation is assessed, as is quantification of the potential savings for a water utility. The results show significant potential savings for the water utility as well as a substantial increase in the utilisation of wind power.

Suggested Citation

  • Kernan, R. & Liu, X. & McLoone, S. & Fox, B., 2017. "Demand side management of an urban water supply using wholesale electricity price," Applied Energy, Elsevier, vol. 189(C), pages 395-402.
    • Handle: RePEc:eee:appene:v:189:y:2017:i:c:p:395-402
    DOI: 10.1016/j.apenergy.2016.12.082
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    References listed on IDEAS

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    Cited by:

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    3. Reis, Ana L. & Lopes, Marta A.R. & Andrade-Campos, A. & Henggeler Antunes, Carlos, 2023. "A review of operational control strategies in water supply systems for energy and cost efficiency," Renewable and Sustainable Energy Reviews, Elsevier, vol. 175(C).
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    5. Majid, A. & van Zyl, J.E. & Hall, J.W., 2022. "The influence of temporal variability and reservoir management on demand-response in the water sector," Applied Energy, Elsevier, vol. 305(C).
    6. Zeng, X.T. & Zhang, J.L. & Yu, L. & Zhu, J.X. & Li, Z. & Tang, L., 2019. "A sustainable water-food-energy plan to confront climatic and socioeconomic changes using simulation-optimization approach," Applied Energy, Elsevier, vol. 236(C), pages 743-759.
    7. Filipe, Jorge & Bessa, Ricardo J. & Reis, Marisa & Alves, Rita & Póvoa, Pedro, 2019. "Data-driven predictive energy optimization in a wastewater pumping station," Applied Energy, Elsevier, vol. 252(C), pages 1-1.
    8. Moreno-Leiva, Simón & Haas, Jannik & Nowak, Wolfgang & Kracht, Willy & Eltrop, Ludger & Breyer, Christian, 2021. "Integration of seawater pumped storage and desalination in multi-energy systems planning: The case of copper as a key material for the energy transition," Applied Energy, Elsevier, vol. 299(C).
    9. Seier, Maximilian & Schebek, Liselotte, 2017. "Model-based investigation of residual load smoothing through dynamic electricity purchase: The case of wastewater treatment plants in Germany," Applied Energy, Elsevier, vol. 205(C), pages 210-224.
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