Marieta Peña Abreu

Providing access to electricity in rural areas remains a challenge in many developing countries, where the lack of infrastructure, low population density, and high costs hinder the implementation of conventional electrification schemes. In this context, off grid solutions (microgrid and individual systems) have emerged as a promising solution, allowing the integration of local renewable energy resources and providing electricity to communities that are not connected to the main power grid. The IntiGIS model has been proposed as a tool to allow the evaluation and comparison of the various electrification technology options. However, some limitations and challenges have been identified in the original model, particularly related to the level of consumer aggregation and the distribution network layout. In this paper, we present improvements to the IntiGIS model related to the clustering of consumers for rural electrification, based on a modified agglomerative clustering algorithm and a set of performance metrics to form the clusters. We also present a comparison with the IntiGIS II version in a case study in Guamá, Santiago de Cuba to demonstrate the effectiveness of the proposed improvements. The results show that the modified IntiGIS model can generate clusters that meet the technical and economic requirements for microgrid and grid extensions systems, with better accuracy and efficiency than the original model. These improvements can contribute to the implementation of sustainable and reliable electricity access in rural areas, promoting social and economic development in these regions. Keywords Clustering Algorithm Semisupervised Learning IntiGIS Geospatial Analysis Rural Electrification Energy Access Sustainable Development

Legal Decision Support Systems in Cuba as yet show few results, but now a resurgence of this field is possible. This new opportunity is due to the worldwide boom in AI & Law research. In addition to the current efforts towards the digital transformation of society. This paper aims to review some antecedents, and discuss some proposals for the evolution of this domain in the country. We first identify the strengths and constraints of some previous contributions and outline the current state of this topic in Cuba. Then, we propose some ideas for future projects, considering the main international approaches and state of the art in Artificial Intelligence, Soft Computing, Big data, and Open Data. We argue the importance of creating different forms of legal knowledge representation, the development of specific algorithms based on the most appropriate techniques for each task, updating of jurists’ and computer specialists’ curricula, and the legislative process improvement. Besides, we advocate the feasibility of creating recommendations in natural language, and we exemplify their types and uses. Finally, the paper calls attention to the protection of personal data and the importance of jurists to participate in the development of systems and to understand how they operate.

Energy access is a crucial step for the socio-economic development of isolated communities and for preventing disease and fight pandemics across many parts of the world. In this research, is presented a freeware GIS tool for the techno-economic evaluation of rural electrification alternatives, based on a plugin for the QGIS (Quantum GIS) called LECGIS. The tool carries out an implementation of the IntiGIS model to perform the calculations, a flexible model capable of adapting to the realities of different scenarios. In addition, it allows the clustering of isolated houses, for a better modelling of the cost of the centralized systems. It is described the application of this tool in the Guamá (Cuba) case study and the comparisons of the results with the obtained in Intigis 1.0. It is concluded that the LECGIS plugin allows to calculate and compare seven technological options for the electrification of communities, supporting the decision-making in the planning of rural electrification projects.