Search Results (32,638)

Natural rubber (NR) block production from cup lump conventionally requires multiple mechanical processing stages, resulting in high energy consumption and complex manufacturing operations. This study presents a modern process approach by using a Rotary Disc Granulator (RDG) to integrate size reduction and cleaning into a simplified two-step processing. The modern process was evaluated in terms of energy consumption, productivity, drying performance, molecular characteristics, rheological behavior, and final product properties, with comparison to the conventional process. The modern process reduced Specific Energy Consumption (SEC) from 89.64±9.52 to 62.56±4.40 kWh/ton, corresponding to an energy saving of approximately 30%, while maintaining comparable productivity and meeting Standard Thai Rubber (STR 20) quality requirements. Improved drying efficiency was achieved through enhanced heat transfer associated with the more uniform pellet morphology produced by the RDG. Molecular and rheological analyses further demonstrated higher molecular weight, lower long-chain branching, and improved thermal stability, indicating reduced mechanical degradation during processing. Despite the simplified process, the cured rubber exhibited comparable curing characteristics and mechanical properties to those produced by the conventional process. These findings demonstrate that process intensification using an RDG provides a practical and sustainable strategy for improving the energy efficiency of industrial natural rubber manufacturing while preserving product quality. Full article

This article presents a scoping review of the literature on digital twins (DTs) for sustainable groundwater resources management, which constitutes a very recent and rapidly expanding research field, with literature moving quickly from conceptual frameworks to application-oriented systems. The literature, selected through the PRISMA 2020 methodology, is organized into seven sub-topics: AI and ML foundations, digital twin architectures and frameworks, aquifer-scale DT applications, agricultural and water–energy–food (WEF) nexus DTs, basin and urban water DTs, sensing, monitoring and IoT infrastructures, and governance, resilience and socio-hydrology. This structure shows how the field is shifting from monitoring and prediction toward integrated decision support, where process-based models, machine learning surrogates, real-time sensing and optimization are combined to support drought mitigation, saltwater intrusion control, irrigation management, climate adaptation and basin-scale planning. Across the reviewed studies, the most recurrent contributions are the construction of hybrid model architectures, the use of DTs to close the loop between observation and control, and the growing recognition that groundwater management must incorporate governance, stakeholder decision-making and socio-hydrological feedbacks. At the same time, the literature still faces key limitations, especially uncertainty quantification, interoperability between models and data streams, transferability to data-scarce settings and limited validation under real operational conditions. Future research should therefore focus on physics-informed and explainable AI, federated and scalable DT architectures, stronger coupling with socio-hydrological and governance frameworks, and more field-tested implementations that can demonstrate robust performance across diverse hydrogeological and institutional contexts. Full article

Remote island buildings often operate under isolated environmental conditions where conventional water supply infrastructures are unavailable or unreliable. However, the lack of theoretical frameworks and integrated technologies for building-scale autonomous water supply remains a critical challenge in sustainable construction and resilient building development. Existing atmospheric water harvesting technologies mainly focus on material-level adsorption capacity or short-term water production performance, while systematic principles for integrating sorption materials, heat transfer structures, and renewable energy subsystems into autonomous building water systems remain insufficiently established. This study develops and validates an active, continuous atmospheric water harvesting (AWH) system utilizing MIL-101(Cr) coated on finned tubes. The system alternates cold water (25 °C) and hot water (50–70 °C during actual experiments; 50–80 °C in simulations) through the piping, allowing the two parallel modules to independently undergo adsorption and desorption phases-thereby breaking away from the traditional daily single-cycle mode. A coupled heat and mass transfer model is developed and validated using experimental measurements obtained from the MIL-101(Cr)-coated finned tube component, with root-mean-square deviations below 8.5% for all key parameters. Under simulated coastal island conditions (75–87% RH, 29–32 °C), the dual-module system achieves a water productivity up to 1.989 kg·m⁻²·day⁻¹ at a desorption temperature of 80 °C, with cycling frequencies reaching 9 cycles per module over 48 h. Parametric analysis reveals that synergy between desorption temperature (50–80 °C) and desorption extent (50–80%) governs daily water yield, while the per-cycle adsorption capacity remains stable at ≈0.91 g/g. Energy and economic analysis shows that the auxiliary electricity required ranges from 0.38 (50 °C) to 6.36 kWh·m⁻³ (80 °C), with a preliminary levelized cost of water of 1.85–3.2 USD·m⁻³ competitive with conventional island supply methods. Full article

Buildings account for roughly 37% of energy-related CO₂ emissions, and space cooling already consumes nearly 10% of global electricity. Cooling demand is rising fastest in tropical cities, where air-conditioning could reach 45% of peak load, especially in India by 2050. This review critically examines thermal energy storage (TES) as a flexibility resource across three distinct scales: individual buildings, district heating and cooling networks, and city-level multi-energy systems. Using a Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA)- based search of Scopus, Web of Science, and IEEE Xplore with primary and supplementary strings, 4447 records were identified, of which 174 were included. Each quantitative study was classified by validation level (simulation, laboratory, pilot, or operational) and by the centrality of thermal storage. Sensible, latent, and thermochemical storage technologies are compared using energy density (10–500 kWh/m³), efficiency (40–95%), cycle stability, and technology readiness. The review then evaluates the role of artificial intelligence (AI), machine learning, and Internet of Things platforms in forecasting, predictive control, and operational optimization of TES networks. Thirteen method families, grouped into AI and machine learning methods, optimization methods, control methods, and digital enabling technologies, are assessed against six explicitly defined criteria with evidence-coded scores. Among 47 quantitative studies, 37 (78.7%) are simulation-only, and only four (8.5%) report operational data. Direct TES-AI studies report simulated energy savings of 8–64% and peak load reductions of about 35%, whereas field-validated intelligent control reports 17% energy savings in a single real building experiment. The review also identifies inherent drawbacks of artificial intelligence-based operations, including limited interpretability, high data and computational demands, concept drift, and cyber vulnerabilities that increased peak electric load by 17.4% in a simulated attack. A structural imbalance in the literature is evident: most validated deployments remain at the building-scale, whereas urban-scale evidence is confined to district cooling, aquifer and pit storage, and multi-energy hub studies; no study reports the coordinated operation of distributed TES assets across multiple districts. A conceptual framework and a staged roadmap linking building, district, and urban scales are proposed. Priority research needs include urban-scale pilots in tropical climates, techno-economic assessment, interpretable and drift-robust AI, and interoperability standards that support United Nations’ Sustainable Development Goals 7, 11, and 13. Full article

The rapid transition toward electric vehicles (EVs) in Saudi Arabia requires reliable and sustainable charging infrastructure capable of supporting long-distance highway transportation. However, the deployment of emergency charging systems is challenged by sparse charging infrastructure, stochastic emergency charging demand, battery degradation under harsh climatic conditions, and the need for cost-effective integration of renewable energy resources. This study presents a three-stage unified techno-economic planning framework for renewable-assisted emergency EV charging networks that integrates strategically located charging hubs with a coordinated fleet of solar-assisted Mobile Emergency Charging Vehicles (MECVs). The proposed framework jointly optimizes charging hub locations, photovoltaic (PV) generation capacity, battery energy storage system (BESS) sizing, and MECV allocation while explicitly accounting for stochastic emergency charging demand, renewable-energy utilization, and temperature-dependent battery degradation. Emergency charging demand is modeled using Monte Carlo simulation based on EV penetration scenarios, and battery aging is incorporated into the optimization through a temperature-dependent degradation model. The planning problem is formulated as a Mixed Integer Nonlinear Programming (MINLP) model and comparatively solved using three independent metaheuristic algorithms, namely the Musical Chairs Algorithm (MCA), Particle Swarm Optimization (PSO), and Grey Wolf Optimization (GWO). The proposed framework is evaluated using two representative highway corridors in Saudi Arabia. The results indicate that renewable-assisted charging can reduce annual grid-related CO₂ emissions by approximately 25,360 and 57,641 t CO₂/year for the Riyadh–Dammam and Riyadh–Makkah corridors, respectively. Battery degradation contributes approximately 12.7–14.2% of the total annualized system cost, highlighting the importance of incorporating lifecycle degradation into infrastructure planning. Temperature sensitivity analysis further indicates the significant influence of harsh climatic conditions on battery lifetime, renewable-energy utilization, and overall system economics. The proposed framework provides a practical planning methodology for developing reliable, sustainable, and economically viable emergency EV charging infrastructure in regions with similar geographical and climatic characteristics. Full article

Polymer nanocomposites have attracted considerable attention owing to their ability to achieve substantial improvements in mechanical, thermal, electrical, barrier, and multifunctional properties through the incorporation of low concentrations of nanoscale fillers. This review provides a comprehensive analysis of recent advances in polymer nanocomposites, focusing on the relationships between nanofiller characteristics, processing strategies, interfacial interactions, and the resulting material performance. Different classes of nanofillers, including carbon-based, ceramic, metallic, polymeric, and hybrid nanostructures, are systematically compared with respect to their morphology, surface chemistry, of processing routes, including melt blending, solution processing, in situ polymerization, and surface functionalization, on nanoparticle dispersion and polymer–nanofiller interfacial adhesion is critically discussed. The review further evaluates how these factors govern the mechanical, thermal, electrical, dielectric, and barrier properties of polymer nanocomposites and summarizes their applications in aerospace, automotive engineering, electronics, biomedical devices, energy systems, construction, and advanced packaging. Current technological challenges, including nanoparticle aggregation, long-term stability, process scalability, environmental impact, and nanomaterial safety, are also examined. Finally, emerging research directions, including hybrid nanofillers, sustainable polymer systems, digital materials design, and machine-learning-assisted optimization of polymer nanocomposites, are highlighted. This review provides an integrated perspective on the design and processing of high-performance polymer nanocomposites and identifies key opportunities for future research and industrial implementation. Full article

Ensuring economic supplies of secure, affordable and clean energy is a global sustainability challenge. Previous studies have shown that, on balance, nuclear energy, based on today’s dominant light water reactors with the once-through use of nuclear fuel, compares well with renewable energy technologies and so should be considered a sustainable energy source. However, the energy-producing nuclear reactor requires a complex infrastructure around it to produce the fuel and to deal with highly radioactive products. The end-to-end fuel cycle thus has significant implications when assessing the overall sustainability of nuclear energy and the “most sustainable” pathways for future nuclear energy. The simplest fuel cycle option is the Once-Through Cycle (OTC) with disposal of used nuclear fuels. More technologically complex options involve different degrees of closing the fuel cycle by recycling and reusing materials from the used fuels. This paper defines six options with different degrees of materials recycling—innovatively presenting them in the form of a “Tube Map” based on that of the London Underground system. The results of this critical review show that recycling has positive impacts on the use of natural resources, environmental footprint, management of high-level radioactive wastes, and energy security. Challenges to the acceptance of closed cycles, however, include safety, security, proliferation, and economics; but our preliminary analysis shows either that solutions exist or that they are not discriminating factors in the choice of fuel cycle. To address these issues, it is important to learn from past experience of implementing closed cycles, and this review looks at the United Kingdom as an interesting case study. Overall, it is concluded that whilst nuclear energy per se should be recognised as sustainable, when implementing the OTC, the development of closed fuel cycles should be considered as a strategic choice that can enhance the overall sustainability of the system. Lastly, an update to the “level playing field” analysis previously proposed for analysing different energy systems is made to account for the differences between different nuclear fuel cycle choices. The only factors that are worse for closed cycles than the OTC are the lower technological maturity (due to greater technological complexity) of closed cycles—particularly those with multiple recycling—and proliferation resistance and physical security (due to the separation of materials in closed cycles). Full article

The building industry is the largest consumer of energy and the largest source of carbon emissions, and the sustainable development of building envelopes is thus inevitable. Among the facade systems, metal cladding materials offer a number of benefits such as high durability, architectural freedom, and recyclability; however, the choice of these materials needs to be based on several performance aspects. This research presents a novel comprehensive approach for analyzing metal cladding options in a health care building through the integration of building energy simulation and multi-attribute decision analysis (MADA) techniques. A primary health care facility in Istanbul, Türkiye, was used as a case example. Eight metal cladding materials—steel, aluminum, copper, zinc, titanium, stainless steel, Corten steel, and magnesium alloy—were evaluated against various wall and insulation combinations. The assessment combined energy with physical–mechanical, thermal, acoustic, and sustainability indicators such as density, thermal conductivity, Young’s modulus, damping capacity, traffic noise insulation, service life, and recyclability. A series of building energy simulations was performed to estimate the effect of facade design options on yearly energy consumption, and the resulting data set was analyzed based on the CRITIC, LOPCOW and ALPAS methods. This method allows the comprehensive evaluation of metal cladding material on energy efficiency, structural strength, acoustic performance, durability, and circularity simultaneously. The results provide a practical decision support framework for sustainable facade material selection in health care and other energy-intensive buildings. Titanium emerged as the optimal metal cladding material, distinguished by its superior combination of low thermal conductivity, damping capacity, and recyclability under both CRITIC and LOPCOW weighting schemes. Comparative analysis across nine MADA methods (ρ = 0.932) and sensitivity analysis over 70 scenarios confirmed the robustness of this finding, with titanium retaining first place in 64 out of 70 perturbation scenarios. These outcomes provide materials engineering insight into how the mechanical, thermal, and durability characteristics of structural metals and alloys translate into differentiated in-service performance, offering evidence-based guidance for metal selection in facade applications. The outcomes reported relate to one health care facility located in Istanbul and demonstrate the potential of the novel framework for the specific investigated case but are not intended to be generalized across all building types and climatic zones or to provide universally applicable material rankings. Full article

Reliable and sustainable electricity supply remains a major challenge for public infrastructure in Sub-Saharan Africa, where frequent grid interruptions and abundant solar resources create favorable conditions for hybrid renewable energy systems. This study presents a comprehensive techno-economic assessment of a hybrid photovoltaic–battery energy storage system–green hydrogen (PV–BESS–H₂) system designed for a public administrative building in Ouagadougou, Burkina Faso. The system was evaluated using an annual building load profile together with locally measured solar irradiance and ambient temperature data. Dynamic simulations were performed in MATLAB/Simulink to assess the technical performance, energy flows, economic viability, and operational behavior of the proposed system. The selected configuration consists of a 77 kWp solar PV array, an 80 kWh lithium-ion battery, a 2 Nm³ h⁻¹ electrolyzer, an 8.4 kg hydrogen storage tank, and a 10.6 kW fuel cell. Annual simulations show that the system generates 140.69 MWh of solar PV electricity and achieves a self-sufficiency ratio of 98.7% while limiting the unmet load to 1.3% of the annual electricity demand. Comparative analysis demonstrates that integrating battery and hydrogen storage substantially reduces the required storage capacities compared with standalone PV–BESS and PV–H₂ configurations. The economic assessment yields a Levelized Cost of Electricity (LCOE) of USD 0.095 kWh⁻¹ and a Levelized Cost of Hydrogen (LCOH) of USD 21.544 kg⁻¹. Sensitivity analysis identifies the discount rate, solar PV investment cost, electrolyzer cost, and project lifetime as the principal drivers of the system’s economic performance. The results demonstrate that the complementary operation of battery and hydrogen storage can enhance the technical and economic performance of renewable energy systems of public buildings in regions with abundant solar resources while providing a practical framework for the design and evaluation of hybrid PV–BESS–H₂ systems. Full article

Biocomposites reinforced with natural fibres are receiving increased attention due to growing concern over the environmental impacts of their synthetic counterparts. Grass mowed from roadside verges has the potential to serve as an alternative to commonly used natural fibres and as a renewable feedstock for the biocomposite industry. However, it is generally treated as waste due to its high volume, seasonal availability, contamination (e.g., with metals and plastic bottles), and legal status. In this study, a techno-economic assessment was performed for different roadside grass valorisation scenarios covering the entire value chain from mowing and pre-treatment to fibre and biocomposite granule production. In addition, a screening greenhouse gas emissions assessment based on the main energy and material inputs was performed for fibre production. This screening assessment provides an initial indication of the operational environmental performance and is not intended to represent a complete life cycle or integrated sustainability assessment. One scenario investigated a value chain with flail mowing and grass fibres as the final product. Grass fibres can be produced at €528/t when mowing costs are included and as low as €295/t when mowing costs are excluded under the processor/incremental-cost perspective. A reduction of 6.4% in fibre price was estimated for the rotary-mowing scenario when mowing costs were excluded. In comparison, the market price of commonly available natural fibres ranges from €300 to €4000/t, although the price is strongly dependent on fibre quality, which was not considered in this assessment. Another scenario considered biocomposite granules consisting of 25% fibres, 60% polylactic acid, and 15% filler as the final product. The biocomposite granules can be produced at €1073/t and €1013/t with and without mowing costs, respectively. The production cost of the granules is largely influenced by the price of the polymer matrix and the compound composition, while the average market price is approximately €2000/t. Overall, the results indicate that roadside grass fibres may be cost-competitive under the evaluated assumptions. The screening assessment resulted in 364.20–701.32 kg CO₂-eq/t fibre for the flail system and 275.96–327.96 kg CO₂-eq/t fibre for the rotary system, depending on whether mowing was excluded or included. Drying energy and diesel consumption associated with mowing and collection were identified as the main operational emission sources. Full article

This study evaluates basalt fiber-reinforced rubberized concrete for building envelopes in Jordan’s hot, dry climate. Two mixes with 6% rubber and 0.5% basalt fibers (M1) or 0.8% basalt fibers (M2) were compared with a reference. Rubber reduced density by 1.0–2.2% but increased absorption by 9.7–24.7% and porosity by 8.7–22.1%. Fibers improved tensile strength by 14–26% and flexural strength by 23–35%, promoting ductile failure. Thermal conductivity decreased by 13.0% (M1) and 4.3% (M2); CTE increased by 10.8% (M1) and 2.0% (M2). M1 achieved the lowest annual energy consumption (0.15–0.28% reduction, with >95% simulation robustness). While material-level thermal improvements are confirmed, they do not translate proportionally into building-scale savings because insulation layers dominate the overall thermal resistance. Tensile enhancements exceeded additive predictions; however, this interpretation is limited by the absence of rubber-only and fiber-only control mixtures and direct microstructural evidence. Therefore, synergy is presented solely as a hypothesis requiring verification through a full factorial experimental design and microstructural investigation. Both materials suit non-load-bearing Jordanian envelopes, with mass-based replacement enabling direct technology transfer. The materials represent a potentially more sustainable option for envelope applications, though long-term durability validation and comprehensive lifecycle assessment are urgently needed. The findings are strongly connected with Jordanian conditions, and direct generalization to other regions is limited and should be stated explicitly. Full article

Conventional anaerobic digestion (AD), despite its proven efficiency in wastewater treatment, faces limitations due to energy requirements and extended hydraulic retention times, with methane yields from waste-activated sludge rarely exceeding 50% of the stoichiometric maximum at retention times of 20 days or more and with the resulting biogas containing 50–75% methane. It also has a constrained capacity for high-grade resource valorization except energy in the form of methane-enriched biogas. This review focuses on bioelectrochemical systems (BES) and hybrid configurations as promising alternatives for sustainable wastewater management. BES mechanisms, including microbial fuel cells (MFC), microbial electrolysis cells (MEC), and microbial electrosynthesis (MES), are analyzed in detail, with emphasis on their capacity to directly convert organic pollutants into electricity or high-value chemicals (hydrogen, acetate) with minimal external energy input. Key advantages include potential electrical energy production, significantly reduced excess sludge production, and high level of waste mineralization. Reported performance reaches power densities of 2203 and 4990 mW/m² for sludge-fed microbial fuel cells and up to 26,680 mW/m² in algae-assisted configurations, chemical oxygen demand (COD) removal of up to 92%, and excess sludge production of 0.09 g/g COD against 0.159 g/g COD for anaerobic digestion treating the same stream. Limitations in terms of scalability and capital costs remain barriers to industrial implementation. Special attention is given to hybrid configurations integrating BES with AD through direct interspecies electron transfer (DIET), which accelerates biodegradation kinetics and enhances resource recovery pathways; compiled MEC-AD data report methane increases of about 3–228% over unpolarized controls, and in a 1.7 L reactor treating alkaline-thermally pretreated waste-activated sludge, the optimum of 0.6 V raised the methane yield from 213.2 ± 9.5 to 308.7 ± 5.9 mL CH₄/g COD removed. These integrated approaches close material and energy cycles, enabling the simultaneous recovery of energy, nutrients (N, P), and bio-chemicals, transforming wastewater treatment plants into zero-waste biorefineries aligned with circular economy principles. Full article

The increased deployment of electric vehicles (EVs) has increased the demand for intelligent energy management strategies to ensure reliable and efficient operation during long-distance travel. Existing EV energy management methods are mainly concerned with energy optimization of the batteries and charging scheduling; however, they often assume reliable charging infrastructure and fixed travel routes. In real-world environments, charging stations can be congested, unavailable, or out of service, and traffic incidents and road closures can affect route feasibility and energy usage. These uncertainties may lead to energy depletion (vehicle stranding) and may compromise successful trip completion. Therefore, this paper proposes a resilience-oriented predictive energy management and route-adaptation framework for long-distance EVs operating under uncertainties in charging infrastructure and the transportation network. The proposed unified decision-making framework incorporates the ability to predict the battery state of charge, estimate the energy requirement of an EV, and determine the availability of charging stations, traffic conditions, disruptions in the road network, and regenerative energy recovery opportunities. A safety-constrained predictive controller is developed to dynamically manage energy consumption while maintaining a minimum energy reserve that guarantees access to feasible charging alternatives under adverse operating conditions. Further, real-time route adaptation is achieved via continuous monitoring of charging station conditions, projected wait times, and road network conditions to determine the most energy-efficient and resilient routes. To assess operational robustness, a resilience index is introduced to quantify the vehicle’s capability to complete a trip while satisfying energy safety constraints in the presence of infrastructure and traffic disturbances. Monte Carlo simulation results on a representative long-distance corridor demonstrate that the proposed framework achieves a 99.3% mission success rate versus 67.3% for a naive shortest-distance baseline, while reducing generalized operating costs by 21.5% and charging stops by 42% relative to a conservative full-charge baseline. These results are simulation-based case study outcomes for the representative corridor and disturbance model studied here and are not measured or expected real-world performance. The proposed approach provides a practical pathway toward resilient, intelligent, and reliable next-generation electric mobility systems. Full article

The transition towards sustainable cities requires material selection strategies capable of balancing environmental, economic and social performance while accounting for the emerging functionalities offered by smart materials. This work proposes a sustainability-driven methodology based on normalized multi-dimensional indicators for the objective comparison of functionally equivalent conventional and smart materials in the built environment and demonstrates its application through the parametric design of an urban bench. The quantitative assessment showed substantial differences among the investigated materials: Shape Memory Polymers (SMPs) resulted in a panel mass of 5 kg, CO₂ emissions of 2.4 kg CO₂/kg, and embodied energy of 37 MJ/kg, compared with 32 kg, 13 kg CO₂/kg, and 260 MJ/kg for NiTi, and 40 kg, 15 kg CO₂/kg, and 320 MJ/kg for magnetic Shape Memory Alloys, respectively. Finite element analysis further demonstrated the influence of structural design, with the maximum principal stress decreasing from approximately 0.073 MPa at a panel thickness of 10 mm to 0.015 MPa at 50 mm, corresponding to a reduction of approximately 79%. The results demonstrate that smart materials do not inherently represent more sustainable alternatives than conventional materials; rather, their adoption should be justified when their adaptive functionalities provide measurable benefits capable of compensating for their environmental and economic burdens. The proposed framework provides a practical decision-support tool that shifts material selection from property-driven choices toward function-oriented, sustainability-based design, supporting more informed decisions for next-generation urban infrastructure. Full article

On-demand data sensing and Wireless Power Transfer (WPT) enable sustainable operation in large-scale Industrial Internet of Things (IIoT) networks. Existing scheduling frameworks are inherently reactive, initiating charging only after an IoT node’s residual energy falls below a predefined threshold, which increases the risk of energy outages and service disruption. This paper proposes a Digital Twin (DT)-enabled proactive scheduling framework for self-sustainable IIoT networks under stochastic operating conditions. The proposed framework integrates three key components. First, a DT layer continuously mirrors IoT node states and predicts future energy availability over a finite prediction horizon. Second, a predictive charging strategy proactively schedules WPT before energy depletion occurs. Third, physical-layer security and DT-based anomaly detection protect the network against eavesdropping, false-data injection, and energy depletion attacks. Fourth, the scheduling framework is reformulated using chance constraints to explicitly account for uncertainty in wireless channels, energy consumption, and DT prediction errors while providing probabilistic reliability guarantees. The resulting sensing and WPT scheduling problems are formulated as multi-slot integer optimization problems and solved using branch-and-bound, with a low-complexity greedy heuristic for latency-sensitive deployments. Simulation results show that the proposed framework reduces energy outage events to below 1%, maintains reliable operation under increasing energy uncertainty with only a modest sensing-utility reduction, and incurs negligible computational overhead compared with the deterministic formulation. Full article