The use of underwater vehicles, either remotely operated vehicles (ROVs) or autonomous underwater vehicles (AUVs), has become increasingly relevant in the operation and maintenance (O&M) routines of offshore wind farms. This article provides a critical review of how these platforms are being integrated into inspection and maintenance tasks, contributing not only to safer and more precise operations but also to greater autonomy in challenging marine environments. Beyond the technical and operational aspects, this review highlights their growing connection with artificial intelligence, digital twins, and multi-robot collaboration. The studies analyzed indicate a progressive shift away from conventional methods, traditionally dependent on crewed vessels and manual inspections, toward more automated, sustainable, and integrated approaches that align with the environmental and social commitments of the offshore wind sector. Finally, emerging trends and persisting obstacles, notably energy autonomy, are discussed, outlining the requirements for consolidating a robust, connected, and sustainability-oriented model for offshore maintenance.

The assurance of universal access to electricity refers to not only physical access to electricity, heating, and/or cooling services but also making them affordable to families. This is the case in Brazil, where physical electricity access reaches more than 99% of the urban population, but a high proportion of households are disconnected due to lack of payment. Affordability is a key factor in planning the expansion and maintenance of the electricity grid. In this paper, therefore, we propose the development of a strategy, called the Payment Capability Indicator (PCI), that provides new information about the relationship between energy cost and family income. The classic indicator, the Ten Percent Rule (TPR), was the base, and empirical research was conducted in two low-income neighborhoods in Paraná state, southern Brazil. The results consider variables that add new information to guide local public policies, combining interventions to improve affordability, energy efficiency, alternatives to energy services and consumer behavioral changes.

This paper presents the design and validation of a low-cost educational platform for teaching photovoltaic systems in evening engineering programs. The proposed system integrates artificial irradiance, single-axis tracking, and power conversion stages within a structured Project-Based Learning (PBL) framework organized into three Learning Journeys. The artificial lighting model was implemented using a fifth-degree polynomial fit (R² > 0.97), and the tracking mechanism reduced voltage variability by approximately 75%. The push-pull DC/DC converter achieved 78% efficiency at 50 W nominal operation, while the inverter stage produced a stable 60 Hz waveform with 18% THD, suitable for laboratory experimentation. Educational assessment involving 44 students indicated positive perceived impact on applied learning and competency development. The proposed solution provides an economically accessible and technically viable alternative for photovoltaic laboratory implementation independent of daylight conditions.