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Integrating wind power using intelligent electric water heating

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  • Fitzgerald, Niall
  • Foley, Aoife M.
  • McKeogh, Eamon

Abstract

Dwindling fossil fuel resources and pressures to reduce greenhouse gas emissions will result in a more diverse range of generation portfolios for future electricity systems. Irrespective of the portfolio mix the overarching requirement for all electricity suppliers and system operators is to instantaneously meet demand, to operate to standards and reduce greenhouse gas emissions. Therefore all electricity market participants will ultimately need to use a variety of tools to balance the power system. Thus the role of demand side management with energy storage will be paramount to integrate future diverse generation portfolios. Electric water heating has been studied previously, particularly at the domestic level to provide load control, peak shave and to benefit end-users financially with lower bills, particularly in vertically integrated monopolies. In this paper a number of continuous direct load control demand response based electric water heating algorithms are modelled to test the effectiveness of wholesale electricity market signals to study the system benefits. The results are compared and contrasted to determine which control algorithm showed the best potential for energy savings, system marginal price savings and wind integration.

Suggested Citation

  • Fitzgerald, Niall & Foley, Aoife M. & McKeogh, Eamon, 2012. "Integrating wind power using intelligent electric water heating," Energy, Elsevier, vol. 48(1), pages 135-143.
    • Handle: RePEc:eee:energy:v:48:y:2012:i:1:p:135-143
    DOI: 10.1016/j.energy.2012.03.014
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    Cited by:

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    2. Tiago Cardoso Pereira & Rui Amaral Lopes & João Martins, 2019. "Exploring the Energy Flexibility of Electric Water Heaters," Energies, MDPI, vol. 13(1), pages 1-11, December.
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    7. Bartłomiej Ciapała & Jakub Jurasz & Alexander Kies, 2019. "The Potential of Wind Power-Supported Geothermal District Heating Systems—Model Results for a Location in Warsaw (Poland)," Energies, MDPI, vol. 12(19), pages 1-15, September.
    8. Baeten, Brecht & Confrey, Thomas & Pecceu, Sébastien & Rogiers, Frederik & Helsen, Lieve, 2016. "A validated model for mixing and buoyancy in stratified hot water storage tanks for use in building energy simulations," Applied Energy, Elsevier, vol. 172(C), pages 217-229.
    9. Linas Gelažanskas & Kelum A. A. Gamage, 2016. "Distributed Energy Storage Using Residential Hot Water Heaters," Energies, MDPI, vol. 9(3), pages 1-13, February.
    10. Foley, A.M. & Leahy, P.G. & Li, K. & McKeogh, E.J. & Morrison, A.P., 2015. "A long-term analysis of pumped hydro storage to firm wind power," Applied Energy, Elsevier, vol. 137(C), pages 638-648.
    11. Balta-Ozkan, Nazmiye & Davidson, Rosemary & Bicket, Martha & Whitmarsh, Lorraine, 2013. "The development of smart homes market in the UK," Energy, Elsevier, vol. 60(C), pages 361-372.
    12. Rinaldi, Arthur & Yilmaz, Selin & Patel, Martin K. & Parra, David, 2022. "What adds more flexibility? An energy system analysis of storage, demand-side response, heating electrification, and distribution reinforcement," Renewable and Sustainable Energy Reviews, Elsevier, vol. 167(C).
    13. George Xydis, 2015. "Wind Energy Integration through District Heating. A Wind Resource Based Approach," Resources, MDPI, vol. 4(1), pages 1-18, March.
    14. Kirchem, Dana & Lynch, Muireann Á & Casey, Eoin & Bertsch, Valentin, 2019. "Demand response within the energy-for-water-nexus: A review," Papers WP637, Economic and Social Research Institute (ESRI).
    15. Martin Almenta, M. & Morrow, D.J. & Best, R.J. & Fox, B. & Foley, A.M., 2016. "Domestic fridge-freezer load aggregation to support ancillary services," Renewable Energy, Elsevier, vol. 87(P2), pages 954-964.
    16. Gou, Xing & Chen, Qun & Hu, Kang & Ma, Huan & Chen, Lei & Wang, Xiao-Hai & Qi, Jun & Xu, Fei & Min, Yong, 2018. "Optimal planning of capacities and distribution of electric heater and heat storage for reduction of wind power curtailment in power systems," Energy, Elsevier, vol. 160(C), pages 763-773.
    17. Hedegaard, Karsten & Balyk, Olexandr, 2013. "Energy system investment model incorporating heat pumps with thermal storage in buildings and buffer tanks," Energy, Elsevier, vol. 63(C), pages 356-365.
    18. Allik, Alo & Märss, Maido & Uiga, Jaanus & Annuk, Andres, 2016. "Optimization of the inverter size for grid-connected residential wind energy systems with peak shaving," Renewable Energy, Elsevier, vol. 99(C), pages 1116-1125.
    19. Foley, A.M. & Ó Gallachóir, B.P. & McKeogh, E.J. & Milborrow, D. & Leahy, P.G., 2013. "Addressing the technical and market challenges to high wind power integration in Ireland," Renewable and Sustainable Energy Reviews, Elsevier, vol. 19(C), pages 692-703.
    20. Yang, Zhile & Li, Kang & Foley, Aoife, 2015. "Computational scheduling methods for integrating plug-in electric vehicles with power systems: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 51(C), pages 396-416.

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