Local energy systems (LESs) are becoming larger and more heterogeneous as distributed energy resources, electrified loads, and active prosumers proliferate, increasing the need for reliable coordination of operation, markets, and community governance. This Perspective synthesizes recent literature to map how artificial intelligence (AI) supports forecasting and situational awareness, optimization, and real-time control of distributed assets, and community-oriented markets and engagement, while arguing that adoption is limited by system-level credibility rather than model accuracy alone. The analysis highlights interlocking deployment barriers, such as governance-integrated explainability, distributional equity, privacy and data governance, robustness under non-stationarity, and the computational footprint of AI. Building on this diagnosis, the paper proposes principles-as-constraints for sustainable, trustworthy LES AI and a deployment-oriented validation and reporting framework. It recommends evaluating LES AI with deployment-ready evidence, including stress testing under shift and rare events, calibrated uncertainty, constraint-violation and safe-fallback behavior, distributional impact metrics, audit-ready documentation, edge feasibility, and transparent energy/carbon accounting. Progress should be judged by measurable system benefits delivered under verifiable safeguards.

The expansion of green hydrogen requires technologies that are both manufacturable at a GW-to-TW power scale and adaptable for decentralized, renewable-driven energy systems. Recent advances in proton exchange membrane, alkaline, and solid oxide electrolysis reveal persistent bottlenecks in catalysts, membranes, porous transport layers, bipolar plates, sealing, and high-temperature ceramics. Emerging fabrication strategies, including roll-to-roll coating, spatial atomic layer deposition, digital-twin-based quality assurance, automated stack assembly, and circular material recovery, enable high-yield, low-variance production compatible with multi-GW power plants. At the same time, these developments support decentralized hydrogen systems that demand compact, dynamically operated, and material-efficient electrolyzers integrated with local renewable generation. The analysis underscores the need to jointly optimize material durability, manufacturing precision, and system-level controllability to ensure reliable and cost-effective hydrogen supply. This paper outlines a convergent approach that connects critical-material reduction, high-throughput manufacturing, a digitalized balance of plant, and circularity with distributed energy architectures and large-scale industrial deployment.

Hydrogen-integrated decentralized energy systems (DIESs) promise communities higher renewable penetration, greater resilience, and sector coupling across electricity, heat, and mobility. AI supports forecasting, dispatch optimization, multi-asset coordination, and planning, yet designing AI-driven hydrogen communities is challenging because it spans physical infrastructure, cyber-control, and governance. This review (2020–2025) synthesizes design strategies for AI-enabled hydrogen DIESs, distilling architectural patterns, electricity–hydrogen co-optimization, uncertainty-aware operation, and digital-twin planning. It summarizes AI benefits (flexibility, efficiency, reduced curtailment) and recurring risks (forecast-optimization cascades, objective mismatch, data drift, safety and constraint breaches, digital-twin credibility gaps, cybersecurity and privacy issues, and weak reproducibility) and proposes a pragmatic roadmap prioritizing safety-aware control, standardized metrics, transparent assumptions, and community-appropriate governance.

Hydropower plants remain strategic assets for grid stability and decarbonization, with hydraulic turbines governing conversion efficiency, reliability, and environmental performance. This systematic review synthesizes recent methodologies for evaluating and optimizing turbine operation and maintenance to enhance efficiency, reduce impacts, and extend service life. Following a PRISMA-aligned protocol, studies published between 2020 and 2025 were screened across Web of Science and Scopus, using predefined eligibility criteria and a two-stage selection process. The resulting evidence was thematically analyzed across three domains: lifecycle and circular-economy-oriented refurbishment strategies; digitalization and predictive maintenance approaches; and environmentally optimized operating regimes. Of the 115 screened records, 37 met the inclusion criteria. Findings indicate that predictive monitoring, data-driven maintenance, and turbine selection tailored to local hydrology can significantly improve energy performance while reducing operation and maintenance costs. The literature also highlights the importance of ecological flow compliance and reduced aquatic impacts. Complementary case studies from Nepal, Switzerland, Germany, Portugal, and Romania illustrate regional challenges and modernization pathways. Overall, the review underscores the need for integrated, multi-objective turbine management that aligns techno-economic, lifecycle, and ecological considerations to support hydropower competitiveness within the energy transition.

This study explores public perceptions, involvement, and barriers to energy communities in Romania, a country where decentralized renewable energy initiatives are still in their infancy. Data were collected through a nationwide online survey based on a quantitative research design, involving 118 respondents from all four macro-regions in Romania. The survey assessed awareness of the concept of energy communities, perceived benefits, technological and regulatory challenges, and willingness to participate or invest. The results show that the perception of energy communities is generally positive, with solar and environmental benefits being the most important. However, significant barriers remain, particularly in terms of financing, institutional support, and regulatory complexity. Urban, involved, and female respondents consistently rated benefits higher and identified more barriers than rural, non-participants and male respondents. Statistical differences between groups were confirmed using the Mann–Whitney U-test. These results highlight the importance of targeted communication, improved policy frameworks, and educational initiatives to ensure broader public involvement and inclusive development of renewable energy systems in Romania.

This paper provides a comprehensive analysis of the development, implementation, and evolution of the circular economy indicator (CEI) in the context of hydroelectric turbine refurbishment over the past five decades. By systematically examining publications indexed in the Web of Science database between 1975 and 2025, the study traces the conceptual origins of the CEI, highlights methodological advances, and analyzes practical applications. The analysis focuses on key aspects such as material circularity, energy efficiency, including the share of renewable sources, and the extension of operational lifetime achieved through refurbishment. The paper also identifies persistent methodological gaps, in particular regarding the integration of social and governance dimensions, as well as the lack of standardization across projects, proposing strategies to increase the reliability and applicability of the indicator. The results provide guidance for integrating circular economy principles into hydroelectric refurbishment processes, outline good practices, and set priorities for future research oriented towards more holistic and multidimensional assessments of circularity.