The transformation of energy markets is at a crossroads in the search for how they must evolve to become ecologically friendly systems and meet the growing energy demand. Currently, methodologies based on bibliographic data analysis are supported by information and communication technologies and have become necessary. More sophisticated processes are being used in energy systems, including new digitalization models, particularly driven by artificial intelligence (AI) technology. In the present bibliographic review, 342 documents indexed in Scopus have been identified that promote synergies between AI and the energy transition (ET), considering a time range from 1990 to 2024. The analysis methodology includes an evaluation of keywords related to the areas of AI and ET. The analyses extend to a review by authorship, co-authorship, and areas of AI’s influence in energy system subareas. The integration of energy resources, including supply and demand, in which renewable energy sources play a leading role at the end-customer level, now conceived as both producer and consumer, is intensively studied. The results identified that AI has experienced notable growth in the last five years and will undoubtedly play a leading role in the future in achieving decarbonization goals. Among the applications that it will enable will be the design of new energy markets up to the execution and start-up of new power plants with energy control and optimization. This study aims to present a baseline that allows researchers, legislators, and government decision-makers to compare their benefits, ambitions, strategies, and novel applications for formulating AI policies in the energy field. The developments and scope of AI in the energy sector were explored in relation to the AI domain in parts of the energy supply chain. While these processes involve complex data analysis, AI techniques provide powerful solutions for designing and managing energy markets with high renewable energy penetration. This integration of AI with energy systems represents a fundamental shift in market design, enabling more efficient and sustainable energy transitions. Future lines of research could focus on energy demand forecasting, dynamic adjustments in energy distribution between different generation sources, energy storage, and usage optimization.

This article presents the design and evaluation of a hybrid groundwater pumping system with battery storage, implemented in the Puntahacienda community of Quingeo, Ecuador, as a sustainable alternative for energy supply in isolated rural areas. The system integrates solar photovoltaic, wind, and a backup diesel generator, whose operation was analyzed using HOMER Pro software. The simulation allowed for component sizing, technical performance evaluation, and operating costs estimation, prioritizing the use of renewable sources and reducing dependence on fossil fuels. The results show that solar and wind energy can cover a large portion of the demand, while the diesel generator ensures resilience during critical periods. The battery bank optimizes stability and continuous supply, ensuring the availability of water for human and agricultural consumption. Furthermore, a significant reduction in greenhouse gas emissions and an improvement in economic sustainability compared to the exclusive use of diesel were evident. The final results show that the levelized cost was $0.186/kWh, making it competitive for an isolated rural community. It was also determined that the renewable energy fraction (RES) was 83.70%, the unmet demand was 0.42%, and CO₂ emissions were 14,850 kg/year when including a diesel generator in the hybrid system. This study demonstrates the viability of hybrid renewable solutions as a tool to strengthen water and energy security in rural communities, constituting a replicable model in similar contexts in Latin America.

The Ecuadorian electrical system, with a generation mix dominated by hydroelectricity, experienced prolonged rationing during recent droughts, prompting a search for generation options that can be installed near consumption centers. Before authorizing new connections, it is necessary to determine the capacity of the subtransmission network for distributed generation and whether this limit depends on the installed technology. This study addresses the integration of renewable energy systems into the 69 kV network of the Centro-Sur Regional Electric Company (CENTROSUR, Ecuador). Hourly wind and photovoltaic energy profiles were considered at eight candidate busbars, and the coordinated integration capacity of the system was determined by simultaneously injecting power into all of them. Six configurations with equal incoming power (renewable, thermal, and three mixed) are compared using power flows, N-1 contingencies, short-circuit analysis (using the full method), and RMS transient stability analysis with the support of the DIgSILENT PowerFactory tool. Five operating points are analyzed: two full dispatch points and three extracted from the year’s chronological data based on hourly solar and wind resource availability. The overall results show that the limit is set by a shared export corridor, not the bus connection point. The coordinated capacity is 160 MW at peak demand and 60 MW at minimum demand, compared to the 620 MW and 380 MW, respectively, that would result from adding the individual capacities of each bus. The operating point governing incoming power is the export condition, which occurs during an hour of intermediate demand with high local generation, not during peak or minimum demand. The sizing procedure is potentially applicable to other meshed subtransmission networks fed from a few points of the transmission system, a situation that can be replicated in other parts of the world.