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Demand Side Management for the European Supergrid: Occupancy variances of European single-person households

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  • Torriti, Jacopo

Abstract

The prospect of a European Supergrid calls for research on aggregate electricity peak demand and Europe-wide Demand Side Management. No attempt has been made as yet to represent a time-related demand curve of residential electricity consumption at the European level. This article assesses how active occupancy levels of single-person households vary in single-person household in 15 European countries. It makes use of occupancy time-series data from the Harmonised European Time Use Survey database to build European occupancy curves; identify peak occupancy periods; construct time-related electricity demand curves for TV and video watching activities and assess occupancy variances of single-person households.

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  • Torriti, Jacopo, 2012. "Demand Side Management for the European Supergrid: Occupancy variances of European single-person households," Energy Policy, Elsevier, vol. 44(C), pages 199-206.
    • Handle: RePEc:eee:enepol:v:44:y:2012:i:c:p:199-206
    DOI: 10.1016/j.enpol.2012.01.039
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    Cited by:

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    2. Anees, Amir & Chen, Yi-Ping Phoebe, 2016. "True real time pricing and combined power scheduling of electric appliances in residential energy management system," Applied Energy, Elsevier, vol. 165(C), pages 592-600.
    3. Torriti, Jacopo, 2013. "The significance of occupancy steadiness in residential consumer response to Time-of-Use pricing: Evidence from a stochastic adjustment model," Utilities Policy, Elsevier, vol. 27(C), pages 49-56.
    4. Jacopo Torriti, 2022. "Household electricity demand, the intrinsic flexibility index and UK wholesale electricity market prices," Environmental Economics and Policy Studies, Springer;Society for Environmental Economics and Policy Studies - SEEPS, vol. 24(1), pages 7-27, January.
    5. Jacopo Torriti & Philipp Grunewald, 2014. "Demand Side Response: Patterns in Europe and Future Policy Perspectives under Capacity Mechanisms," Economics of Energy & Environmental Policy, International Association for Energy Economics, vol. 0(Number 1).
    6. López-Rodríguez, M.A. & Santiago, I. & Trillo-Montero, D. & Torriti, J. & Moreno-Munoz, A., 2013. "Analysis and modeling of active occupancy of the residential sector in Spain: An indicator of residential electricity consumption," Energy Policy, Elsevier, vol. 62(C), pages 742-751.
    7. Apajalahti, Eeva-Lotta & Lovio, Raimo & Heiskanen, Eva, 2015. "From demand side management (DSM) to energy efficiency services: A Finnish case study," Energy Policy, Elsevier, vol. 81(C), pages 76-85.
    8. Jacopo Torriti, 2017. "The Risk of Residential Peak Electricity Demand: A Comparison of Five European Countries," Energies, MDPI, vol. 10(3), pages 1-14, March.
    9. Torriti, Jacopo, 2012. "Price-based demand side management: Assessing the impacts of time-of-use tariffs on residential electricity demand and peak shifting in Northern Italy," Energy, Elsevier, vol. 44(1), pages 576-583.
    10. Anderson, Ben & Torriti, Jacopo, 2018. "Explaining shifts in UK electricity demand using time use data from 1974 to 2014," Energy Policy, Elsevier, vol. 123(C), pages 544-557.
    11. Gils, Hans Christian, 2014. "Assessment of the theoretical demand response potential in Europe," Energy, Elsevier, vol. 67(C), pages 1-18.
    12. Broberg, Thomas & Persson, Lars, 2016. "Is our everyday comfort for sale? Preferences for demand management on the electricity market," Energy Economics, Elsevier, vol. 54(C), pages 24-32.
    13. Xiufeng Liu & Yanyan Yang & Rongling Li & Per Sieverts Nielsen, 2019. "A Stochastic Model for Residential User Activity Simulation," Energies, MDPI, vol. 12(17), pages 1-17, August.
    14. Igor Kotenko & Igor Saenko & Oleg Lauta & Aleksander Kribel, 2020. "An Approach to Detecting Cyber Attacks against Smart Power Grids Based on the Analysis of Network Traffic Self-Similarity," Energies, MDPI, vol. 13(19), pages 1-24, September.
    15. Schleich, Joachim & Faure, Corinne & Klobasa, Marian, 2017. "Persistence of the effects of providing feedback alongside smart metering devices on household electricity demand," Energy Policy, Elsevier, vol. 107(C), pages 225-233.
    16. Palacios-Garcia, E.J. & Moreno-Munoz, A. & Santiago, I. & Flores-Arias, J.M. & Bellido-Outeirino, F.J. & Moreno-Garcia, I.M., 2018. "A stochastic modelling and simulation approach to heating and cooling electricity consumption in the residential sector," Energy, Elsevier, vol. 144(C), pages 1080-1091.
    17. Torriti, Jacopo, 2020. "Temporal aggregation: Time use methodologies applied to residential electricity demand," Utilities Policy, Elsevier, vol. 64(C).
    18. Santiago, I. & López-Rodríguez, M.A. & Gil-de-Castro, A. & Moreno-Munoz, A. & Luna-Rodríguez, J.J., 2013. "Energy consumption of audiovisual devices in the residential sector: Economic impact of harmonic losses," Energy, Elsevier, vol. 60(C), pages 292-301.
    19. Zarazua de Rubens, Gerardo & Noel, Lance, 2019. "The non-technical barriers to large scale electricity networks: Analysing the case for the US and EU supergrids," Energy Policy, Elsevier, vol. 135(C).
    20. Schleich, Joachim & Klobasa, Marian & Gölz, Sebastian & Brunner, Marc, 2013. "Effects of feedback on residential electricity demand—Findings from a field trial in Austria," Energy Policy, Elsevier, vol. 61(C), pages 1097-1106.
    21. Satoshi Nakano & Ayu Washizu, 2020. "On the Acceptability of Electricity Demand Side Management by Time of Day," Energies, MDPI, vol. 13(14), pages 1-21, July.
    22. Gils, Hans Christian, 2016. "Economic potential for future demand response in Germany – Modeling approach and case study," Applied Energy, Elsevier, vol. 162(C), pages 401-415.

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