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Demand–Response Control of Electric Storage Water Heaters Based on Dynamic Electricity Pricing and Comfort Optimization

Author

Listed:
  • Ángel Á. Pardiñas

    (Energy Division, Galicia Institute of Technology, 15003 A Coruña, Spain)

  • Pablo Durán Gómez

    (Energy Division, Galicia Institute of Technology, 15003 A Coruña, Spain)

  • Fernando Echevarría Camarero

    (Energy Division, Galicia Institute of Technology, 15003 A Coruña, Spain)

  • Pablo Carrasco Ortega

    (Energy Division, Galicia Institute of Technology, 15003 A Coruña, Spain)

Abstract

Electric Storage Water Heaters (ESWH) are a widespread solution to supply domestic hot water (DHW) to dwellings and other applications. The working principle of these units makes them a great resource for peak shaving, which is particularly important due to the level of penetration renewable energies are achieving and their intermittent nature. Renewable energy deployment in the electricity market translates into large electricity price fluctuations throughout the day for individual users. The purpose of this study was to find a demand–response strategy for the activation of the heating element based on a multiobjective minimization of electricity cost and user discomfort, assuming a known DHW consumption profile. An experimentally validated numerical model was used to perform an evaluation of the potential savings with the demand–response optimized strategy compared to a thermostat-based approach. Results showed that cost savings of approximately 12% can be achieved on a yearly basis, while even improving user thermal comfort. Moreover, increasing the ESWH volume would allow (i) more aggressive demand–response strategies in terms of cost savings, and (ii) higher level of uncertainty in the DHW consumption profile, without detriment to discomfort.

Suggested Citation

  • Ángel Á. Pardiñas & Pablo Durán Gómez & Fernando Echevarría Camarero & Pablo Carrasco Ortega, 2023. "Demand–Response Control of Electric Storage Water Heaters Based on Dynamic Electricity Pricing and Comfort Optimization," Energies, MDPI, vol. 16(10), pages 1-25, May.
    • Handle: RePEc:gam:jeners:v:16:y:2023:i:10:p:4104-:d:1147544
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    References listed on IDEAS

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    1. Clift, Dean Holland & Stanley, Cameron & Hasan, Kazi N. & Rosengarten, Gary, 2023. "Assessment of advanced demand response value streams for water heaters in renewable-rich electricity markets," Energy, Elsevier, vol. 267(C).
    2. Bo Lin & Shuhui Li & Yang Xiao, 2017. "Optimal and Learning-Based Demand Response Mechanism for Electric Water Heater System," Energies, MDPI, vol. 10(11), pages 1-17, October.
    3. Armstrong, Peter M. & Uapipatanakul, Meg & Thompson, Ian & Ager, Duane & McCulloch, Malcolm, 2014. "Thermal and sanitary performance of domestic hot water cylinders: Conflicting requirements," Applied Energy, Elsevier, vol. 131(C), pages 171-179.
    4. Lago, Jesus & De Ridder, Fjo & Mazairac, Wiet & De Schutter, Bart, 2019. "A 1-dimensional continuous and smooth model for thermally stratified storage tanks including mixing and buoyancy," Applied Energy, Elsevier, vol. 248(C), pages 640-655.
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