Skip to main content

Advertisement

SpringerLink
Log in

Impacts of domestic electric water heater parameters on demand response

A Simulative Analysis of Physical and Control Parameter Impacts

  • Special Issue Paper
  • Published:
Computer Science - Research and Development

Abstract

This paper analyzes the impact of the high dimensional parameter space of domestic electric water heaters (DEWH) for demand response (DR). To quantify the consumer comfort a novel metric is introduced considering a stochastic distribution of different water draw events. Incorporating three control algorithms from literature, it is shown that all considered parameters of a DEWH except the heat conductivity have a significant impact on consumer satisfaction. The effect on DR is mainly influenced by the temperature range and the planning horizon, but also by the heat conductivity and the volume. In contrast, the rated power of the heating element and the nominal temperature have no significant impact on the effect on DR. The impacts are analyzed by varying these parameters in a simulation of 1000 DEWHs considering three different controllers: a common thermostat, an exchange price dependent nominal temperature changing mechanism and an energy scheduling algorithm proposed by Du and Lu.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9
Fig. 10
Fig. 11
Fig. 12
Fig. 13
Fig. 14
Fig. 15
Fig. 16
Fig. 17

Similar content being viewed by others

References

  1. Lechner H et al (1998) Analysis of energy efficiency of domestic electric storage water heaters. study for the directorate general for energy (DG XVII) of the Commission of the European Communities, Contract No. SAVE-4.1031/E/95-013, Final Report. Tech. rep

  2. Stadler I (2006) Demand response: nichtelektrische Speicher für Elektrizitätsversorgungssysteme mit hohem Anteil erneuerbarer Energien. Habilitation. dissertation.de, Berlin

  3. Nehrir M, Jia R, Pierre D, Hammerstrom D (2007) Power management of aggregate electric water heater loads by voltage control. IEEE Power Eng Soc Gen Meet 1–6

  4. Paull L, Li H, Chang L (2010) A novel domestic electric water heater model for a multi-objective demand side management program. Electr Power Syst Res 80(12):1446–1451

    Article  Google Scholar 

  5. Shaad M, Momeni A, Diduch CP, Kaye M, Chang L (2012) Parameter identification of thermal models for domestic electric water heaters in a direct load control program. IEEE, pp 1–5

  6. Fernández-Seara J, Uhía FJ, Sieres J (2007) Experimental analysis of a domestic electric hot water storage tank. Part II: dynamic mode of operation. Appl Therm Eng 27(1):137–144

    Article  Google Scholar 

  7. Kondoh J, Aki H, Yamaguchi H, Murata A, Ishii I (2005) Future consumed power estimation of time deferrable loads for frequency regulation. In: 18th international conference and exhibition on electricity distribution (CIRED 2005). IET, Turin, Italy, pp 1–4. doi:10.1049/cp:20051215

  8. Kondoh J, Lu N, Hammerstrom DJ (2011) An evaluation of the water heater load potential for providing regulation service. IEEE Trans Power Syst 26(3):1309–1316

    Article  Google Scholar 

  9. Department for Environment, Food and Rural Affairs (Defra): Measurement of Domestic Hot Water Consumption in Dwellings. Tech. rep., Department for Environment, Food and Rural Affairs (Defra) (2008). https://www.gov.uk/government/uploads/system/uploads/attachment_data/file/48188/3147-measure-domestic-hot-water-consump.pdf

  10. Mufaris A, Baba J (2015) Coordinated consumer load control by use of heat pump water heaters for voltage rise mitigation in future distribution system. In: 2015 seventh annual IEEE green technologies conference. IEEE, New Orleans, pp 176–182. doi:10.1109/GREENTECH.2015.14

  11. Lane I, Beute N (1996) A model of the domestic hot water load. IEEE Trans Power Syst 11(4):1850–1855

    Article  Google Scholar 

  12. Jordan U, Vajen K. Realistic domestic hot-water profiles in different time scales (v. 2.0). Project Report for IEA-SHC Task 26 (2001). http://sel.me.wisc.edu/trnsys/trnlib/iea-shc-task26/iea-shc-task26-load-profiles-description-jordan.pdf

  13. Siano P (2014) Demand response and smart grids–a survey. Renew Sustain Energy Rev 30:461–478

    Article  Google Scholar 

  14. Conchado A, Linares P (2012) Handbook of networks in power systems I, chap. The economic impact of demand-response programs on power systems. A survey of the state of the art. Springer, Berlin, pp 281–301

  15. Vardakas JS, Zorba N, Verikoukis CV (2015) A survey on demand response programs in smart grids: pricing methods and optimization algorithms. IEEE Commun Surv Tutor 17(1):152–178

    Article  Google Scholar 

  16. Venzke M, Turau V (2016) Simulative evaluation of demand response approaches for waterbeds. In: Proceedings of the 2016 IEEE international energy conference (ENERGYCON)

  17. Lu N, Katipamula, S (2005) Control strategies of thermostatically controlled appliances in a competitive electricity market. In: IEEE power engineering society general meeting, vol 1. IEEE, pp 202–207. doi:10.1109/PES.2005.1489101

  18. Lu N, Chow J, Desrochers A (2004) Pumped-storage hydro-turbine bidding strategies in a competitive electricity market. IEEE Trans Power Syst 19(2):834–841

    Article  Google Scholar 

  19. Du P, Lu N (2011) Appliance commitment for household load scheduling. IEEE Trans Smart Grid 2(2):411–419

    Article  Google Scholar 

  20. Mohsenian-Rad AH, Leon-Garcia A (2010) Optimal residential load control with price prediction in real-time electricity pricing environments. IEEE Trans Smart Grid 1(2):120–133

    Article  Google Scholar 

  21. Tsui KM, Chan SC (2012) Demand response optimization for smart home scheduling under real-time pricing. IEEE Trans Smart Grid 3(4):1812–1821

    Article  Google Scholar 

  22. Qian LP, Zhang YJA, Huang J, Wu Y (2013) Demand response management via real-time electricity price control in smart grids. IEEE J Sel Areas Commun 31(7):1268–1280

    Article  Google Scholar 

  23. SaniTec Produkthandel GmbH: Fach-Information Warmwassergeräte (2014). http://sanitec.de/fileadmin/user_upload/SaniTec/Kataloge/SaniTec_Folder_2014.pdf

Download references

Author information

Authors and Affiliations

  1. Telematics, Hamburg University of Technology, Hamburg, Germany

    Tobias Lübkert, Marcus Venzke & Volker Turau

Authors
  1. Tobias Lübkert
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Marcus Venzke
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Volker Turau
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Tobias Lübkert.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Lübkert, T., Venzke, M. & Turau, V. Impacts of domestic electric water heater parameters on demand response. Comput Sci Res Dev 32, 49–64 (2017). https://doi.org/10.1007/s00450-016-0321-8

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00450-016-0321-8

Keywords

Search

Navigation