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Abstract Beyond the definition and measurement of energy poverty, which have mainly attracted research interest over the last decades, attention has recently begun to turn to a broader notion of energy vulnerability. So far, this has mostly been approached on a theoretical base, suggesting the incorporation of broader socio-economic aspects into the energy poverty framework. However, the quantitative measurement of energy vulnerability is still an unexplored field of research. In this paper, the "Vulnerability Index" is developed, which, based on stochastic analysis, quantifies the vulnerability of a population to the energy poverty ratio, compared to a reference population. Moreover, Sensitivity Analysis quantifies the particular contribution of various parameters to the problem, by determining their weighting factors. As case study, the vulnerability of Greek mountainous regions with respect to the country level was studied. The results showed that households living in mountainous regions are more vulnerable versus those of the whole country, at 89.7%. It was also found that energy policy should focus on raising incomes of mountainous population and, afterwards, on energy saving measures and reduction of heating cost in mountains. The methodology suggested can address social inequalities of vulnerable population groups, in terms of energy poverty. [ABSTRACT FROM AUTHOR]

Policy makers have realized that without significant increases in the energy efficiency and notable reductions in the energy use of the household sector, it will be impossible to lower carbon dioxide emissions and mitigate the risks of climate change at the global level. The energy demand in residential buildings is influenced by several parameters, such as national economic growth, climate and weather, demographic structure, and technological development. In this paper, we analyze the determinants of electricity and natural gas consumptions in Italy during the period from 2004 to 2013. We provide estimates of price and income elasticities of the demand for both the energy sources in the residential sector. The role played by both energy price and household income is worth attention because it provides evidence for the occurrence of the direct rebound effect. Therefore, the economic drivers of the energy demand are important to improve the policies meant to reduce greenhouse gas emissions and contrast the global warming. [ABSTRACT FROM AUTHOR]

Energy consumption has long been emphasized as an important policy issue in today's economies. In particular, the energy efficiency of residential buildings is considered a top priority of a country's energy policy. The paper proposes a genetic programming-based framework for estimating the energy performance of residential buildings. The objective is to build a model able to predict the heating load and the cooling load of residential buildings. An accurate prediction of these parameters facilitates a better control of energy consumption and, moreover, it helps choosing the energy supplier that better fits the energy needs, which is considered an important issue in the deregulated energy market. The proposed framework blends a recently developed version of genetic programming with a local search method and linear scaling. The resulting system enables us to build a model that produces an accurate estimation of both considered parameters. Extensive simulations on 768 diverse residential buildings confirm the suitability of the proposed method in predicting heating load and cooling load. In particular, the proposed method is more accurate than the existing state-of-the-art techniques. [ABSTRACT FROM AUTHOR]