Research on energy poverty (EP) started in the United Kingdom and other Western European countries in response to the Oil Crisis in 1973. In the last few years, the European community has made important breakthroughs on the topic, by establishing clear terminology as well as funding different multidisciplinary and intersectoral task groups that have EP understanding and alleviation as their goal. Several different methodologies have been developed to measure EP. For instance, the multidimensional energy poverty index (MEPI) by Nussbaumer et al. (2012) has been successfully used in Africa and in seven Latin American countries. Mexico does not have an official measure, indicator, or index on EP. However, a very important energy service has been overlooked: thermal comfort. In the present work, MEPI was understood as an energy services deprivation calculation, and thermal comfort was included. Understanding the regional nature of thermal comfort, we searched for weather-based regionalizations that could address a whole country diversity. We applied two regionalizations, one strongly related to political divisions (called climatic), and a another used for household design and construction standards (bioclimatic). The bioclimatic regionalization had a better fit when assessing energy services deprivation, since it addresses exclusively geographical and weather conditions, instead of the artificial political divisions. Having better ways to assess the level of EP in the local context is a key factor to develop effective public policies that might alleviate EP in a sustainable way.

The increase of energy access to households has been a global priority. By 2018, 89.59% of the world population had access to electricity, while 97.26% of the persons living in urban areas (The Mexican Government reports it at 99.99%) had access. We must now move beyond access to electricity and address energy poverty in urban spaces. A household is energy poor when their inhabitants are incapable of securing proper domestic energy services. Several different methodologies were developed to measure energy poverty. The Multidimensional Energy Poverty Index (MEPI) by Nussbaumer has been successfully used in Africa and in Latin-America. The MEPI considers five dimensions: cooking, lighting, household appliances, entertainment/education and communication. We developed a Multidimensional Energy Deprivation Index (MEDI), based on MEPI. Thermal comfort has been included as sixth dimension, by considering the temperature of the region where the household is located. We found important differences between MEPI and MEDI for Mexico at the national level (urban-MEPI at 0.028 vs. 0.071 urban-MEDI, which implies a higher degree of energy poverty). Also, differences between geopolitical and bioclimatic regions were found. Having better ways to assess energy poverty in the urban context is a key factor to develop effective public policies that might alleviate it.

This paper describes an innovative method to evaluate energy access in any of size population by applying fuzzy logic. The obtained results allow ranking regions of Mexico according to their overall energy access. The regions were determined by the country’s political division (32 states). The results presented herein are in close correspondence with other studies undertaken. This method is recommended because it is possible to use as an assessment tool due to its representativeness—that is, it poses a heuristic alternative to quantify the level of Energy Access in a particular region through qualitative data. It is also efficient and cost-effective in terms of computer resources. This is extremely important to public policy makers that require more accurate, faster and cheaper methodologies to assess energy access as an indicator of well-being.

The call for a global energy transition represents a common front in which most countries around the world can jointly engage and collaborate to reduce the shared threat of climate change. However, such a global energy transition toward a low-carbon future involves a myriad of interconnected national processes in which each country strives for the sociotechnical restructuring of its own energy systems, including the way they generate power or electricity. At the same time, structural processes of transition open the opportunity to build energy systems that are not only low-carbon but also more resilient, ideally reducing technical, social, economic, and environmental vulnerabilities at different scales, from the household to the systems level. Through examination of Colombia, Cuba, and Mexico, this chapter unpacks the relevance of energy resilience and energy vulnerability as supporting concepts in understanding energy transitions, focusing on the understudied region of Latin America. In doing so, the chapter evaluates how energy generation and consumption have recently evolved in the aforementioned countries. Such analysis is complemented by a discussion of examples of energy resilience or vulnerability in the context of each national power system engaging in low-carbon transitions.

Existing energy resilience metrics have primarily focused on the technical performance of systems, with evaluations typically conducted using mathematical algorithms. However, as several authors have noted, energy resilience involves more than the ability to recover from a blackout, as it also encompasses social and economic contexts. In response to this limitation, the present study proposes a metric for assessing energy resilience that incorporates not only technical factors, but also environmental, social, economic, and institutional dimensions. The metric was validated through the judgements of experts with more than 15 years of professional experience in the field. Given the qualitative nature of the information associated with these dimensions, fuzzy logic is employed as the analytical approach. Two fuzzy logic models were applied: a simplified model comprising five variables and a more detailed model comprising fifteen variables organised into sub-principles. The results indicate a national energy resilience value of 1.55 for the simplified model and 2.0 for the detailed model, suggesting that the inclusion of a broader set of variables yields a more representative assessment. These findings support the view that fuzzy logic is an appropriate tool for this type of evaluation, as it allows expert knowledge to be systematically incorporated into the assessment process. Furthermore, the proposed approach may be adaptable to energy resilience evaluations conducted at both national and local scales. Smart citations: https://scite.ai/reports/10.61467/2007.1558.2026.v17i1.1080 Dimensions.Open Alex.