Recent energy price spikes have led to increased energy poverty among low-income households living in inefficient homes. Accurate statistics on energy poverty help inform resource allocation and better target relief schemes and retrofit funds. Existing indicators are predominantly defined in terms of a headcount ratio – the share of population living below a certain threshold or poverty line. In this paper we draw from the literature on income poverty evaluation to argue that the use of more elaborate energy poverty gap indices can substantiate the design and monitoring of energy poverty policies, by not only considering incidence but also intensity and inequality of energy poverty across households. We demonstrate that the choice for a particular energy poverty (gap) indicator makes the implicit welfare choices of energy poverty policies explicit. We illustrate our arguments for the case of the Netherlands, using recently developed microdata statistics on energy poverty, and an imposed energy price shock. We show that spatial targeting of relief funds based on incidence would neglect the full depth of energy poverty deprivation. Finally, we argue that visualisation techniques from the income poverty literature help to comprehend different poverty orderings and draw comparisons between time periods, regions, and subgroups.@en

A. WP1-ECN Integrating energy systems at the regional level: a model based assessment of the Dutch energy system B. WP2-KIWA Integrating local and regional energy systems; basic data collection C. WP3-TUD Designing institutions for future energy systems D. WP4-TNO Description of an agent-based model of dynamically evolving, coupled, regional distribution grids, conditional on grid balancing@en