Search Results (293)

The use of different energy sources for heating and year-round domestic water heating is driven by the European Union’s increasingly strict environmental and climate requirements. For this reason, consumers are seeking alternatives and show growing interest in implementing installations that utilize solar energy. Modern households typically employ at least two different energy sources for this purpose. In practice, these are hybrid installations that, depending on the season, can operate with one, two, or more energy sources. The system examined in this paper is of this type, comprising a pellet boiler, solar vacuum tubes, and electric heaters. Managing such a system is complex, and based on the conducted studies, process optimization can be pursued. This report presents an artificial neural network (ANN) model developed to predict the behavior of a real solar installation for domestic hot water heating during the summer season. This study aims, through the obtained model, to forecast the system’s performance during transitional periods such as autumn and spring, thereby enabling more efficient control. Full article

Many studies on solar heating systems have examined individual techniques to enhance the performance of solar water collectors, such as flow obstructions, increased turbulence, nanofluids, and investment in thermal storage. The benefits of integrating these sustainability strategies into a single, sustainable system have yet to be fully established. This work displays a hybrid water-heating system that contains a solar water collector (SWC) and an electric water heater (EWH), a photovoltaic panel (PV), and nano-additives to increase the outlet water temperature and improve thermal efficiency. Numerical and experimental analyses were used to estimate the influence of water flow rate (2.5, 3.5, and 4.5 L/min) and different Al₂O₃ concentrations (0.1%, 0.2%, and 0.3%) on system performance using U-shaped pipe in SWC model. The results highlight that lower flow rates consistently yield higher ΔT values because water spends a longer time in the collector, allowing it to absorb more heat. Also, when using water only, the collector efficiency increases pro-aggressively with flow rate. A significant performance enhancement is observed upon incorporating Al₂O₃ nanoparticles into the fluid, with a 0.1% Al₂O₃ volume concentration improving efficiency by ~7.4% over water. At 0.3%, the highest improvement is recorded, yielding a ~9.3% gain in efficiency compared to the base case. Full article

The development of integrated renewable energy and high-density thermal energy storage systems has been fueled by the need for environmentally friendly heating and cooling in buildings. In this paper, MiniStor, a hybrid thermochemical and phase-change material storage system, is presented. It is equipped with a heat pump, advanced electronics-enabled control, photovoltaic–thermal panels, and flat-plate solar collectors. To optimize energy flows, regulate charging and discharging cycles, and maintain operational stability under fluctuating solar irradiance and building loads, the system utilizes state-of-the-art power electronics, variable-frequency drives and modular multi-level converters. The hybrid storage is safely, reliably, and efficiently integrated with building HVAC requirements owing to a multi-layer control architecture that is implemented via Internet of Things and SCADA platforms that allow for real-time monitoring, predictive operation, and fault detection. Data from the MiniStor prototype demonstrate effective thermal–electrical coordination, controlled energy consumption, and high responsiveness to dynamic environmental and demand conditions. The findings highlight the vital role that digital control, modern electronics, and Internet of Things-enabled supervision play in connecting small, high-density thermal storage and renewable energy generation. This strategy demonstrates the promise of electronics-driven integration for next-generation renewable energy solutions and provides a scalable route toward intelligent, robust, and effective building energy systems. Full article

The rapid growth and seasonal availability of agricultural materials, such as straws, stalks, husks, shells, and processing wastes, present both a disposal challenge and an opportunity for renewable fuel production. Solar-assisted thermochemical conversion, such as solar-driven pyrolysis, gasification, and hydrothermal routes, provides a pathway to produce bio-oils, syngas, and upgraded chars with substantially reduced fossil energy inputs compared to conventional thermal systems. Recent experimental research and plant-level techno-economic studies suggest that integrating concentrated solar thermal (CSP) collectors, falling particle receivers, or solar microwave hybrid heating with thermochemical reactors can reduce fossil auxiliary energy demand and enhance life-cycle greenhouse gas (GHG) performance. The primary challenges are operational intermittency and the capital costs of solar collectors. Alongside, machine learning (ML) and AI tools (surrogate models, Bayesian optimization, physics-informed neural networks) are accelerating feedstock screening, process control, and multi-objective optimization, significantly reducing experimental burden and improving the predictability of yields and emissions. This review presents recent experimental, modeling, and techno-economic literature to propose a unified classification of feedstocks, solar-integration modes, and AI roles. It reveals urgent research needs for standardized AI-ready datasets, long-term field demonstrations with thermal storage (e.g., integrating PCM), hybrid physics-ML models for interpretability, and region-specific TEA/LCA frameworks, which are most strongly recommended. Data’s reporting metrics and a reproducible dataset template are provided to accelerate translation from laboratory research to farm-level deployment. Full article

Thermally driven heat pumps primarily use thermal energy to drive a compression cycle. The thermal energy can be waste heat, natural-gas combustion, or solar, helping increase efficiency and reduce greenhouse-gas emissions. We study a thermal compressor heat pump (TCHP) in which Stirling-type thermal compressors (TCs) are heat-driven rather than electrically driven, delivering a nominal heat capacity of 8 kW with CO₂ as the refrigerant. Unlike most existing dynamic models of CO₂ cycles, which focus on electrically driven or single-stage systems, this work targets a heat-driven multi-stage configuration and includes transient validation. Like any vapor compression cycle (VCC), a TCHP requires a dynamic model for control and optimization; its predictive reliability must be validated on experimental data. We therefore describe the test bench and performance expressions, collect steady-state and transient datasets, and derive a hybrid dynamic model: finite-volume (FV) differential equations for slow components and quasi-static submodels (linear regressions and correlations) for fast elements. The contribution of this work is the development and experimental validation of a hybrid FV model for a multi-stage heat-driven CO₂ TCHP. Validation against both steady-state and transient datasets shows good agreement. On 15 steady-state operating points, the model reproduces pressures within ∼1 bar mean absolute error (MAE) and system-level performance (total recovered heat, $CO{P}_{\mathrm{th}}$) within ∼6% mean absolute percentage error (MAPE), with $R^2\gtrsim 0.8$; component heat-rate predictions are within ∼20% MAPE. Under transient step tests on expansion valve openings and burner fan speed, the thermal COP and total recovered heat track within $4\%$ MAPE (up to $R^2=0.96$), pressures within $1.5$ bar MAE, and the evaporator heat rate within 14–$22\%$ MAPE. Full article

Improving ship energy efficiency has become a critical priority for reducing fuel consumption and meeting international decarbonization targets. In this study, eight major groups of energy efficiency improvement systems—including wind and solar energy technologies, hull and propeller modifications, air lubrication, green propulsion options, waste heat recovery, and engine power limitation—were evaluated against seven critical success factors. A hybrid neutrosophic fuzzy multi-criteria decision-making (MCDM) framework was employed to capture expert uncertainty and prioritize alternatives. Neutrosophic fuzzy sets were adopted because they more comprehensively represent uncertainty—simultaneously modeling truth, indeterminacy, and falsity, providing superior capability to address expert ambiguity compared with classical fuzzy, intuitionistic fuzzy, gray, or other uncertainty-handling frameworks. Trapezoidal Neutrosophic Fuzzy Analytic Hierarchy Process (AHP) (TNF-AHP) was first applied to determine the relative importance of the criteria, highlighting fuel savings and cost-effectiveness as dominant factors with 38% weight. Subsequently, the Fuzzy Combined Compromise Solution (F-CoCoSo) method was used to rank the alternatives. Results indicate that solar energy systems and wind-assisted propulsion consistently rank highest (with 3.35 and 2.92 performance scores) across different scenarios, followed by green propulsion technologies, while waste heat recovery and engine power limitation show lower performance. These findings not only provide a structured assessment of current technological options, but also offer actionable guidance for shipowners, operators, and policymakers seeking to prioritize investments in sustainable maritime operations. Full article

This study presents a cradle-to-grave Life Cycle Assessment (LCA) and cost analysis of next-generation low-temperature district heating networks based on water-condensed electric booster heat pumps. The research, conducted within the ENEA Portici Research Center framework, evaluates multiple case studies to assess environmental and economic sustainability. The system boundaries include heat generators (geothermal heat pump, solar thermal, and photovoltaic–thermal hybrid), network configurations (tree vs. ring), supply temperatures (25 °C vs. 45 °C), and renewable electricity shares (0–100%). Environmental impacts were quantified using the Environmental Footprint 3.1 method, focusing on key indicators such as climate change, resource use, and human toxicity. The results show that supply temperature is a critical factor: 45 °C scenarios lead to notably higher impacts, while network configuration has only marginal effects. Among generation technologies, the photovoltaic–thermal system proved the most sustainable, despite higher investment costs, whereas the solar thermal system displayed the largest environmental burden but lower costs. Geothermal systems showed intermediate performance, with notable impacts from mineral resource use. Renewable electricity integration consistently improved environmental outcomes, reducing climate change impacts by up to 10%. Storage system comparison revealed lithium iron phosphate (LFP) batteries as the most advantageous solution for electrical storage, and phase-change materials (PCM), particularly Rubitherm15, as the most environmentally favorable option for thermal storage, although traditional water tanks remain more cost-effective. Overall, the study highlights the crucial role of renewable integration and temperature optimization in enhancing the eco-efficiency of low-temperature district heating networks, providing guidelines for future sustainable design and deployment. Full article

Urban environments, particularly university campuses, are increasingly exposed to thermal discomfort due to the Urban Heat Island (UHI) effect and intense solar radiation. This study evaluates the effectiveness of passive and hybrid cooling strategies, specifically sun-sail shading and mist cooling, in enhancing outdoor thermal comfort (OTC) in a university courtyard. The Van Dyck courtyard at the American University of Beirut, located on the East Mediterranean coast, was selected due to its heavy use between 10 am and 2 pm during summer, when ambient temperatures ranged between 32 and 36 °C and relative humidity between 21 and 33%. Thermal variations across four seating areas were analyzed using ENVI-met, a high-resolution microscale model validated against on-site data, achieving Mean Absolute Percentage Errors of 4% for air temperature and 5.2% for relative humidity. Under baseline conditions, Physiological Equivalent Temperature (PET) exceeded 58 °C, indicating severe thermal stress. Several mitigation strategies were evaluated, including three shading configurations, two mist-cooling setups, and a combined system. Results showed that double-layer shading reduced PET by 17.1 °C, mist cooling by 1.2 °C, and the combined system by 20.7 °C. Shading minimized radiant heat gain, while mist cooling enhanced evaporative cooling, jointly bringing thermal sensations closer to slightly warm–comfortable conditions. These cooling interventions also have sustainability value by reducing dependence on mechanically cooled indoor spaces and lowering campus air-conditioning demand. As passive or low-energy measures, shading and mist cooling support climate-adaptive outdoor design in heat-stressed Mediterranean environments. Full article

In the context of the zero-carbon transition, this article provides a comprehensive review of Organic Rankine Cycle (ORC) technologies for low-grade heat recovery and conversion to power. It surveys a wide range of renewable and waste heat sources—including geothermal, solar thermal, biomass, internal combustion engine exhaust, and industrial process heat—and discusses the integration of ORC systems to enhance energy recovery and thermal efficiency. The analysis examines various configurations, from basic and regenerative cycles to advanced transcritical and supercritical designs, cascaded systems, and multi-source integration, evaluating their thermodynamic performance for different heat source profiles. A critical focus is placed on working fluid selection, where the landscape is being reshaped by stringent regulatory frameworks such as the EU F-Gas regulation, driving a shift towards low-GWP hydrofluoroolefins, natural refrigerants, and tailored zeotropic mixtures. The review benchmarks ORC against competing technologies such as the Kalina cycle, Stirling engines, and thermoelectric generators, highlighting relative performance characteristics. Furthermore, it identifies key trends, including the move beyond single-source applications toward integrated hybrid systems and the use of multi-objective optimization to balance thermodynamic, economic, and environmental criteria, despite persistent challenges related to computational cost and real-time control. Key findings confirm that ORC systems significantly improve low-grade heat utilization and overall thermal efficiency, positioning them as vital components for integrated zero-carbon power plants. The study concludes that synergistically optimizing ORC design, refrigerant choice in line with regulations, and system integration strategies is crucial for maximizing energy recovery and supporting the broader zero-carbon energy transition. Full article

Coastal ecosystems represent a complex and dynamic interface for renewable energy development, combining solar radiation, coastal winds, and marine biomass. In regions such as La Guajira (Colombia), these resources create a unique opportunity to design hybrid systems that integrate solar, wind, and bio-based energy generation. This study applied a multicriteria assessment encompassing technical, economic, environmental, and social dimensions to evaluate the feasibility of this integration. The study adopts a narrative review approach supported by peer-reviewed literature, satellite-derived environmental datasets, and regional technical reports. Three criteria were used to assess the potential of these bioresources: (i) availability and spatiotemporal variability, (ii) physicochemical and energetic characteristics, and (iii) suitability for thermochemical and biochemical valorisation routes. Reported data indicate that pelagic Sargassum reaching the wider Caribbean contains 20–30% ash, 25–35% carbohydrates, and lower heating values between 8 and 12 MJ kg⁻¹, while cactus biomass in arid environments can reach LHV of 13–16 MJ kg⁻¹ and moisture contents below 15%. The coastal region of La Guajira also receives solar irradiation levels exceeding 6 kWh m⁻² day⁻¹ and wind speeds above 8 m s⁻¹, creating favourable conditions for hybrid bioenergy–renewable systems. Finally, the multicriteria analysis reveals that integrating coastal renewable resources could drive the transition towards a circular, inclusive, and low-carbon bioeconomy in coastal territories such as La Guajira. Full article

Although numerous studies have investigated individual methods to improve the performance of solar air heaters (SAHs), such as flow obstruction barriers, porous media, nanofluids, and thermal energy storage units, the overall integration of these reinforcement strategies into a unified, sustainable system remains to be defined. The current study presents a hybrid solar air heating configuration that combines a solar air collector (SAC) with an electric air heater (EAH) powered by photovoltaic (PV) panels, aiming to stabilize outlet air temperature and enhance overall thermal efficiency. Experimental and numerical approaches were employed to evaluate the influence of barrier geometry (flat, trapezoidal, and V-groove) and airflow rate (53, 158, and 317 L/min) on system performance using three SAC models. Experimental results revealed that lower airflow rate promotes greater temperature rise (ΔT) due to longer air–surface contact, while V-groove barriers achieved the highest ΔT and collector efficiency among all configurations. At higher airflow rates, the absorbed energy factor Fc (τα) increased to approximately 0.73, whereas the heat loss factor FcU decreased, indicating reduced thermal losses and improved energy transfer. Model III demonstrated the most effective heat absorption, confirming its superior thermal design. The integrated SAC–EAH system exhibited improved overall efficiency, with the SAC functioning effectively as a preheating unit and the EAH sustaining thermal stability during variable solar conditions. Numerical results showed that the highest temperature difference occurs at the V-groove barriers at an air flow rate of 53 L/min. In contrast, the difference between inlet and outlet temperatures decreases across the remaining models, with reduced percentages of 11.8% and 12.7% for Model II and Model I, respectively. Numerical simulations ensured the experimental outcomes, showing close agreement with the temperature variation trends and validating the system’s enhanced thermal performance. Full article

Protected agriculture increasingly requires solutions that reduce energy consumption and environmental impacts while maintaining stable microclimatic conditions. The integration of Artificial Intelligence (AI), Machine Learning (ML), and Deep Learning (DL) with solar technologies has emerged as a pathway toward autonomous and energy-efficient greenhouses and solar dryers. This study analyzes the scientific and technological evolution of this convergence using a mixed review approach bibliometric and systematic, following PRISMA 2020 guidelines. From Scopus records (2012–2025), 115 documents were screened and 79 met the inclusion criteria. Bibliometric results reveal accelerated growth since 2019, led by Engineering, Computer Science, and Energy, with China, India, Saudi Arabia, and the United Kingdom as dominant contributors. Thematic analysis identifies four major research fronts: (i) thermal modeling and energy efficiency, (ii) predictive control and microclimate automation, (iii) integration of photovoltaic–thermal (PV/T) systems and phase change materials (PCMs), and (iv) sustainability and agrivoltaics. Systematic evidence shows that AI, ML, and DL based models improve solar forecasting, microclimate regulation, and energy optimization; model predictive control (MPC), deep reinforcement learning (DRL), and energy management systems (EMS) enhance operational efficiency; and PV/T–PCM hybrids strengthen heat recovery and storage. Remaining gaps include long-term validation, metric standardization, and cross-context comparability. Overall, the field is advancing toward near-zero-energy greenhouses powered by Internet of Things (IoT), AI, and solar energy, enabling resilient, efficient, and decarbonized agro-energy systems. Full article

The growing global population has resulted in a higher demand for energy, leading researchers to prioritize the development of alternative energy sources and the improvement of current technologies. Nanofluids (NFs) are a promising method for enhancing heat transfer and efficiently utilizing solar thermal energy. This study describes the preparation of four NFs: two mono NFs of SiC and HfC containing nanoparticle concentrations ranging from 0.10–1.0 wt.%. Moreover, two hybrid NFs were synthesized within the same concentration range (0.10–1.0 wt.%) of SiC-HfC nanocomposites in proportions of 60 wt.% SiC-40 wt.% HfC and 40 wt.% SiC-60 wt.% HfC, all dispersed in a mixture of ethylene glycol (EG) and distilled water (50EG-50H₂O). The materials were synthesized by carbothermal reduction, and the NFs were prepared using the two-step method. The NFs showed stable dispersion, with HfC and 40SiC-60HfC systems exhibiting the higher zeta potential (ζ) values. Viscosity remained largely unaffected by particle addition. The thermal diffusivity of the NFs was measured by the thermal lens spectroscopy (TLS) technique using 1:20 diluted samples. The hybrid nanofluid 40SiC-60HfC improved diffusivity by 66.93%, presenting a synergistic effect in its performance, highlighting its potential in clean energy systems. Full article

The transition to low-carbon energy systems necessitates innovative design strategies for decarbonizing hydrogen production, particularly in industrial-scale applications where steam methane reforming (SMR) remains predominant. This study proposes a novel, integrated process design for blue hydrogen production that addresses both energy and environmental sustainability through process intensification and resource valorization. A hybrid system was developed that combines solar thermal energy input with the catalytic potential of industrial waste, specifically, red mud, a byproduct of alumina refining. A solar parabolic dish (SPD) was engineered to contribute 10% of the heat demand, generating superheated steam at 477 °C. This work serves as a proof-of-concept, demonstrating the technical viability of integration at a bench scale. In parallel, red mud was characterized, thermochemically activated, and formulated into a low-cost catalyst for the SMR process. The integrated system includes solar-assisted steam generation, red mud-based catalytic reforming, CO₂ capture using methyl diethanolamine (MDEA), and hydrogen purification via pressure swing adsorption (PSA). The full process was modeled and optimized using ASPEN Plus, ASPEN Adsorption, and COMSOL Multiphysics^® Under optimal conditions (900 °C, 25 bar, steam-to-carbon ratio of 3), the system produced 1070 kg/h of hydrogen, achieving 95% CO₂ capture efficiency and 99.99% hydrogen purity. Techno-economic analysis revealed the red mud-derived catalyst costs 3.89 SAR/g (1.04 USD/g), a 77% cost reduction compared to conventional Ni-based catalysts. The integration of solar thermal energy, while offering modest direct economic savings of approximately 9500 SAR (2530 USD) annually, primarily demonstrates the technical feasibility of renewable heat integration for reducing the carbon intensity of hydrogen production. Full article

This study evaluates the thermal performance of a prototype vacuum-tube solar cooker adapted to the climatic conditions of the Amazon region, Peru. Four grain types (Zea mays L., Triticum aestivum, Zea mays var. morochon, and Hordeum vulgare) were tested to assess temperature evolution, exposure time, and incident solar radiation. Hordeum vulgare was selected as a food model for calibration due to its well-characterized thermophysical properties and reproducible heating behavior. The results showed individual thermal efficiencies ranging from 19.3% to 35.3%, with an average of 27.3% across the three tubes. The most efficient treatment, obtained with Zea mays L., reached 180 °C under an irradiance of approximately 980 W/m². A direct relationship was observed between solar radiation intensity, exposure time, and thermal efficiency. These findings confirm that the proposed hybrid design combining a cylindrical parabolic collector with vacuum U-tubes achieves higher and more stable performance than conventional box-type cookers. The system allows complete grain cooking without fossil fuels, demonstrating its potential as a sustainable and low-cost solution for rural communities in the Andean Amazonian region, promoting clean energy adoption and reducing environmental impact. Full article