Geothermal energy is the energy that is stored inside the earth and which may be used by man either directly (with no transformation) or to generate electricity by means of a geothermal power plant. This article estimates the participation of geothermal energy in Colombia’s electricity market by the year 2025, based on a review of current installed capacity in the country; potential sources of geothermal energy for electric power generation; the existing regulatory framework for projects involving renewable sources, and the geothermal projects currently under development in the national territory. Demand for electricity in Colombia will continue to increase, which implies that new electric power generation projects must be undertaken in order to meet the country’s demand. The conclusion is that geothermal energy is a good alternative to help achieve this objective. By 2025, geothermal sources are expected to generate at least 1400 GWh of electric power per year, equivalent to 1.65% of total electricity estimate demand in Colombia. If the full potential that has been assessed were exploited, generation capacity could reach up to 17,400 GWh/year (equivalent to close to 20% of the country’s demand) by 2025.

Buildings are currently among the largest consumers of electrical energy with considerable increases in CO₂ emissions in recent years. Although there have been notable advances in energy efficiency, buildings still have great untapped savings potential. Within demand-side management, some tools have helped improve electricity consumption, such as energy forecast models. However, because most forecasting models are not focused on updating based on the changing nature of buildings, they do not help exploit the savings potential of buildings. Considering the aforementioned, the objective of this article is to analyze the integration of methods that can help forecasting models to better adapt to the changes that occur in the behavior of buildings, ensuring that these can be used as tools to enhance savings in buildings. For this study, active and passive change detection methods were considered to be integrators in the decision tree and deep learning models. The results show that constant retraining for the decision tree models, integrating change detection methods, helped them to better adapt to changes in the whole building’s electrical consumption. However, for deep learning models, this was not the case, as constant retraining with small volumes of data only worsened their performance. These results may lead to the option of using tree decision models in buildings where electricity consumption is constantly changing.

Se analizan los resultados de la gestión administrativa en las instituciones educativas rurales del distrito de Santa Marta, Colombia, considerando dimensiones como enfoque administrativo, nivel de gestión, usos de investigación de operaciones en educación y toma de decisión. Es una investigación descriptiva, de campo y transversal, con población de 25 instituciones rurales. El instrumento fue un cuestionario tipo escala de Likert con 48 ítems, validado mediante juicio experto y confiabilidad de 0.87 Alfa de Cronbach. La estadística fue descriptiva, y se construyó un baremo de 5 categorías. Los resultados indican que no hay enfoque administrativo predominante en las instituciones educativas de la zona rural y que existe moderada presencia en el uso de técnicas de investigación operacional en la gestión administrativa de los colegios. Además, 72% de los directores no utilizan soportes para decidir, 48% no usa referentes teóricos, aunque existen condiciones para adelantar estudios de investigación operacional en cada institución.

Planning for offshore wind energy projects is intricate due to the consideration of multiple variables in identifying optimal project areas. The primary challenge lies in locating suitable sites, a process that often necessitates extensive feasibility studies spanning several years. The primary goal of this study is to apply the Fuzzy Analytic Hierarchy Process (FAHP) to prioritize criteria and sub-criteria, facilitating decision-making in choosing appropriate locations for offshore wind projects in the Colombian Caribbean Sea. The weights derived from FAHP were utilized in a Geographic Information System (GIS) to analyze the physical characteristics of the Caribbean Sea’s surface. This tool plays a critical role in evaluating and selecting sites that fulfill established criteria, providing a database of indicators and map visualizations. Four criteria were defined: technical, environmental, social, and economic, along with fourteen sub-criteria, which were prioritized through FAHP based on expert judgment. The results revealed that the most relevant sub-criteria were protected areas and wind speed. Utilizing the ArcGIS Pro software, five zones meeting the predetermined criteria were identified, defining the most feasible areas for offshore wind farm installation, located in the departments of Guajira, Magdalena, Atlántico and Bolívar. The GIS–FAHP methods proved to be useful for feasibility analysis.

The electrification of industrial processes offers sustainable opportunities for reducing carbon footprints and enhancing energy efficiency in the chemical industry. This paper presents an overview of recent research developments in incorporating electrical energy as a replacement for conventional thermal sources like gas and coal in industrial sectors. A literature review was conducted, identifying 70 relevant articles published until September 2020. The topics cover applications for industrial hydrogen generation processes and others, heat pumps, heat pumps, vapor re-compression systems, electric and magnetic fields as heat sources, nanoparticles for improved heat exchange, and ionized gases (plasma) in heating systems. While the application of industrial electrification shows promise globally, its sustainability depends on the efficiency and cost of electrical energy production and transportation at the regional and national levels. Among the various technologies, heat pumps integrated with vapor re-compression systems (VCR) for chemical processes, particularly in industrial distillation product separation columns, appear to be the most viable and widely applicable for waste heat recovery in the near future. Other technologies like electrochemical, plasma, microwave, magnetic, and electric field heating are still in the early stages of development or are limited to specific pilot or laboratory-scale processes.

Solar and wind energy systems, without storage, cannot satisfy variable load demands, but their combined use can help to solve the problem of the balance between generation and consumption. Energetic complementarity studies are useful to evaluate the viability of the use of two or more renewable energy sources with high variability in a specific interval of time in a determined region. In this paper, the monthly energetic complementarity study of solar and wind resources of Colombia is carried out. A novel approach to conduct the study is proposed. A dataset with the average monthly solar radiation and wind speed values is obtained from high-resolution images of renewable resources maps, using image processing algorithms. Then, the dataset is used to calculate the energetic complementarity of the sources employing the negative of the Pearson correlation coefficient. The obtained values are transformed to energetic complementarity maps, previously eliminating the protected areas. The obtained results show that there is a good energetic complementarity in the north and northeastern regions of the country throughout the year. The results indicate that projects related to the joint use of solar and wind generation systems could be developed in these regions.