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Analysing socioeconomic diversity and scaling effects on residential electricity load profiles in the context of low carbon technology uptake

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  • McKenna, R.
  • Hofmann, L.
  • Merkel, E.
  • Fichtner, W.
  • Strachan, N.

Abstract

Adequately accounting for interactions between Low Carbon Technologies (LCTs) at the building level and the overarching energy system means capturing the granularity associated with decentralised heat and power supply in residential buildings. The approach presented here adds novelty in terms of a realistic socioeconomic differentiation by employing dwelling/household archetypes (DHAs) and neighbourhood clusters at the Output Area (OA) level. These archetypes are combined with a mixed integer linear program (MILP) to generate optimum (minimum cost) technology configurations and operation schedules. Even in the baseline case, without any LCT penetration, a substantial deviation from the standard load profile (SLP) is encountered, suggesting that for some neighbourhoods this profile is not appropriate. With the application of LCTs, including heat pumps, micro-CHP and photovoltaic (PV), this effect is much stronger, including more negative residual load, more variability, and higher ramps with increased LCT penetration, and crucially different between neighbourhood clusters. The main policy implication of the study is the importance of understanding electrical load profiles at the neighbourhood level, because of the consequences they have for investment in the overarching energy system, including transmission and distribution infrastructure, and centralised generation plant. Further work should focus on attaining a superior socioeconomic differentiation between households.

Suggested Citation

  • McKenna, R. & Hofmann, L. & Merkel, E. & Fichtner, W. & Strachan, N., 2016. "Analysing socioeconomic diversity and scaling effects on residential electricity load profiles in the context of low carbon technology uptake," Energy Policy, Elsevier, vol. 97(C), pages 13-26.
    • Handle: RePEc:eee:enepol:v:97:y:2016:i:c:p:13-26
    DOI: 10.1016/j.enpol.2016.06.042
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    References listed on IDEAS

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    Cited by:

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    2. Ryu, Jun-Yeol & Kim, Dae-Wook & Kim, Man-Keun, 2021. "Household differentiation and residential electricity demand in Korea," Energy Economics, Elsevier, vol. 95(C).
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    6. Weinand, J.M. & McKenna, R. & Fichtner, W., 2019. "Developing a municipality typology for modelling decentralised energy systems," Utilities Policy, Elsevier, vol. 57(C), pages 75-96.
    7. Andersen, Kristoffer Steen & Wiese, Catharina & Petrovic, Stefan & McKenna, Russell, 2020. "Exploring the role of households’ hurdle rates and demand elasticities in meeting Danish energy-savings target," Energy Policy, Elsevier, vol. 146(C).
    8. Thøgersen, John, 2017. "Housing-related lifestyle and energy saving: A multi-level approach," Energy Policy, Elsevier, vol. 102(C), pages 73-87.
    9. Beaufils, Timothé & Pineau, Pierre-Olivier, 2019. "Assessing the impact of residential load profile changes on electricity distribution utility revenues under alternative rate structures," Utilities Policy, Elsevier, vol. 61(C).
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