Healthcare facilities are among the most energy-intensive and critical components of modern infrastructure, operating continuously under strict reliability requirements while facing increasing pressure to decarbonize. At the same time, growing exposure to grid instability, climate-related disruptions, and sustainability demands has intensified the need for energy solutions that enhance resilience, improve efficiency, and reduce emissions. Within this context, fuel cell technologies have emerged as promising alternatives owing to their modular design, enhanced efficiency, and appropriateness for decentralized applications. Consequently, this review provides a thorough and critical evaluation of the integration of fuel cells into healthcare energy infrastructure by providing evidence across technical, economic, environmental, and regulatory domains. The work starts with an analysis of the energy requirements and resilience prerequisites particular to the healthcare sector, subsequently assessing the suitability of principal fuel cell technologies and integration strategies. Additionally, representative case studies from South Africa, the United States, Italy, Japan, and Nepal are reviewed to illustrate diverse fuel cell applications and different implementation stages across emergency power, backup systems, combined heat and power, mobile clinics, and hospitals operating with weak grid infrastructure. Finally, the paper concludes that fuel cell technologies can significantly enhance energy resilience, reduce lifecycle emissions, and provide a viable pathway toward low-carbon and reliable healthcare energy infrastructure when they are appropriately selected and integrated within healthcare-specific operational frameworks.
Seasonal thermal energy storage (sTES) can enhance Thermal Source Network (TSN) flexibility by enabling inter-seasonal energy shifting and mitigating mismatches between supply and demand. This study investigates the design and integration of a retrofit sTES into TSN, using the incampus industrial park in Ingolstadt, Germany, as a case study. A dynamic co-simulation framework is developed by coupling a MATLAB/Simscape TSN model with a physics-based sTES model developed in Modelica/Dymola. A parametric assessment varies key sTES design parameters and demand characteristics. Performance is evaluated using three indicators: sTES efficiency, demand coverage, and levelized cost of thermal service (LCOTS). Results show that improved insulation and compact geometry increase storage efficiency by up to approximately 20%, while compact geometry reduces LCOTS by approximately 15%. Increasing sTES volume improves heating and cooling coverage but can increase LCOTS by approximately 80% when the additional capacity is insufficiently utilized. A heat pump-assisted charging option extends the sTES usable temperature range and increases demand coverage by approximately 20% while storage efficiency remains nearly unchanged. In contrast, increasing the demand overlap coefficient from 20% to 50% reduces sTES utilization and increases LCOTS by 125%. Overall, no single configuration performs best across efficiency, coverage, and cost. Among the configurations that improve all evaluated performance indicators relative to the reference case, t6.0_V24000_h5.6_HP400 achieves the highest combined relative improvement and is therefore identified as the most promising configuration under the investigated conditions, increasing storage efficiency by 17%, heating and cooling coverage by 58% and 34%, respectively, while reducing LCOTS by 5%. The identified design trends provide guidance for sTES design in similar TSNs under comparable operating conditions and within the investigated parameter ranges.
Energy hubs, which produce, store, manage, and consume energy, are increasingly important for reducing costs and carbon emissions. Traditionally, their design focuses on selecting the type and size of assets, such as wind, solar, and storage systems, to meet demand at minimum cost, relying on the power grid for shortfalls. However, with growing grid congestion and limited withdrawal capacities, energy security has become a critical objective. We propose a novel two-stage stochastic program that jointly optimizes costs and energy supply reliability, accounting for both short-term uncertainties (demand fluctuations, renewable production variability, and unit failures) and long-term uncertainties (technology degradation). The model integrates reliability indicators directly into hub design, enabling a trade-off between economic efficiency and supply resilience. In a case study with real-world data from five industrial consumers, reliability-oriented designs differ substantially from the lowest-cost design: they reduce the expected shortages by 98% at a long-term cost that increases from 45 to 244 k€, and avoid shortages entirely at 315 k€. A 10% lower grid withdrawal capacity more than triples the long-term cost. Capturing both short- and long-term uncertainties is essential: compared to expected-value designs, the stochastic designs reduce the expected total cost by up to 75%, and generator degradation increases the expected energy not supplied (EENS) by 9%–14%. Finally, reliability is not evenly distributed among consumers: with the lowest-cost design, the EENS of the highest-demand consumer reaches 0.26% of its demand, compared to 0.15% for the hub as a whole and at most 0.03% for the other consumers.
Renewable Energy Communities (RECs) provide a framework for combining decentralised renewable generation, collective self-consumption, and increasingly digitalised energy management, yet comparatively little attention has been given to how citizen-led initiatives progress from local energy-transition visions to practical operation. This study analyses the implementation pathway of the Culatra REC, a citizen-led initiative on a peripheral Portuguese island, focusing on the interaction between regulatory, technical, economic, organisational, social, and digital challenges. A case-study approach combines regulatory and project documentation, governance, and operational records, previous Culatra studies, whole-village electricity demand data, monitored PV generation and PV production simulations. Each dimension is examined through a challenge - response - status - outcome framework. The REC is in early operation, while governance, billing, data exchange and advanced digital and energy management functions remain at different stages of consolidation. For the expanded 293.73 kWp PV configuration under construction, when assessed against electricity demand of Culatra, simulations indicate a self-consumption index of 85.4%, an annual self-sufficiency index of 36.9%, and 71.6% self-sufficiency during PV generation hours, demonstrating the importance of matching renewable generation with local demand. Real-time smart metering, network modelling and the progressive development of a distributed energy management architecture and Digital Twin provide the basis for more advanced monitoring, demand-side management, and flexibility. The case shows that governance arrangements, business models, technical design and digital capabilities evolve as implementation progresses. Its central contribution is an implementation-oriented perspective in which implementation itself modifies design, providing transferable principles for the staged development of citizen-led smart energy communities.
