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In many European countries, energy poverty is measured on the basis of real energy bills, as theoretical energy costs are hard to calculate. The UK is an exception—the data inputs for the Low Income-High Cost (LIHC) indicator are based on reasonable energy costs, these data are collected through specially designed surveys, often an intensive and costly procedure. Approaches which calculate energy needs are valid when energy bill data are unreliable or where households restrict consumption. In this analysis, energy poverty levels are evaluated for Greece, the municipality of Évora (Portugal), and the Basque Country (Spain): energy bills are modeled based on building energy performance data and other energy uses, and adjusted according to socio-demographic variables. To this end, equivalization weights are calculated using socio-economic data from the aforementioned southern European countries/regions. Data are analyzed to compare measurements with actual versus modeled bills using the Ten-Percent Rule (TPR) and Hidden Energy Poverty (HEP) against twice the median (2M) indicator, enhancing the identification of households with low energy consumption. In conclusion, theoretical energy needs can be combined with socio-demographic data instead of actual energy bills to measure energy poverty in a simplified way, avoiding the problem of targeting households that under consume.

The experience of operating an energy-related Living Lab (LL) in mountainous Greece is presented in this paper in an attempt to explore the dynamics of such initiatives to address energy vulnerability. The LL is situated in Metsovo, which is a typical mountainous town of Greece with increased vulnerability issues identified in previous studies. Since Greek mountainous societies have proved to be particularly exposed to energy poverty, the LL aimed to function as an exemplary case on how to tackle energy poverty issues in mountainous regions, mainly through reducing energy consumption and improving energy efficiency. The methodological context was based on a holistic LL approach consisting of various activities, such as conduction of energy cafés, questionnaire surveys, home visits from Energy Advisors, installation of monitoring equipment, ICT tools and processing, etc. In particular, the LL consisted of three independent rounds, each of which involved 50 households, with 30 of them being equipped with monitoring tools. Energy advisors repeatedly visited households to collect information (on heating expenses, behavioral aspects, etc.) and offer household-specific advice on potential energy savings measures. Overall, the LL operation proved to have benefited most participants (76%), especially households with monitoring equipment, as 85.5% of the last ones already applied energy-efficiency measures and 80% made further plans for future investments. Through the particular LL example, apart from the benefits delivered to the local society, useful information can be provided to policy-makers toward addressing more effectively energy vulnerability in mountainous societies.

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