Analysing socioeconomic diversity and scaling effects on residential electricity load profiles in the context of low carbon technology uptake. (October 2016)

• Record Type: Journal Article
• Authors: McKenna, R.; Hofmann, L.; Merkel, E.; Fichtner, W.; Strachan, N.
• Is Part Of: Energy policy. Volume 97(2016)
• Page Start: 13
• Page End: 26
• Publication Date: 2016-10
• Subjects: ADMD After Diversity Maximum Demand -- BIC Bayesian Information Criteria -- CHAP CREST Combined Heat and Power (model) -- CHM Cambridge Housing Model -- CHP Combined Heat and Power -- CSE Centre for Sustainable Energy -- DDM Dynamic Dispatch Model -- DF Diversity Factor -- DHAs dwelling/household archetypes -- DHW Domestic Hot Water -- EFUS Energy Follow Up Survey -- HEUS Household Energy Use Study -- HP Heat Pump -- HRP Household Representative Person -- LCTs Low Carbon Technologies -- mCHP micro-Combined Heat and Power -- MILP Mixed Integer Linear Program -- NHM National Household Model -- NRS National Readership Survey -- OA Output Areas -- PV Photovoltaics -- RC (thermal) Resistance-Capacitance (model) -- SH Space Heating -- SLP Standard Load Profile -- WholeSEM Whole Systems Energy Modelling; Households -- Buildings -- Socioeconomic factors -- Load profiles -- Distribution network -- Low carbon technologies; Energy policy -- Periodicals; Politique énergétique -- Périodiques; Electronic journals; 333.79
• DOI: 10.1016/j.enpol.2016.06.042
• Languages: English
• ISSNs: 0301-4215

Abstract

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. Highlights: Low carbon technologies (LCTs) for heat/electricity in residential buildings. Socioeconomic effects and interactions with overarching energy system. Building thermal/electrical model combined with optimisation. Significant differences between neighbourhood load profiles. Policy implications: support for LCTs and investment in infrastructure.