TY - JOUR
T1 - Analysing socioeconomic diversity and scaling effects on residential electricity load profiles in the context of low carbon technology uptake
AU - McKenna, R.
AU - Hofmann, L.
AU - Merkel, E.
AU - Fichtner, W.
AU - Strachan, N.
N1 - Acknowledgements
This research was primarily supported under the Fellowship programme of the EPSRC funded Whole Systems Energy Modelling Consortium (WholeSEM) – Grant Reference: EP/K039326/1. The authors also wish to acknowledge the financial support of the BMBF for the project “Wettbewerb Energieeffiziente Stadt” (03SF0415B) and the EU for the project CIVIS (www.civisproject.eu). The first author would also like to thank the members of the Energy Systems Modelling research theme at the UCL Energy Institute for numerous valuable discussions in the context of the above Fellowship. The authors are also grateful for the helpful comments of two anonymous reviewers on an earlier version of this manuscript.
PY - 2016/10
Y1 - 2016/10
N2 - 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.
AB - 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.
KW - Buildings
KW - Distribution network
KW - Households
KW - Load profiles
KW - Low carbon technologies
KW - Socioeconomic factors
UR - http://www.scopus.com/inward/record.url?scp=84978379758&partnerID=8YFLogxK
U2 - 10.1016/j.enpol.2016.06.042
DO - 10.1016/j.enpol.2016.06.042
M3 - Article
AN - SCOPUS:84978379758
VL - 97
SP - 13
EP - 26
JO - Energy Policy
JF - Energy Policy
SN - 0301-4215
ER -