Search Results (1,030)

The global energy landscape is transitioning towards cleaner solutions, with hydrogen emerging as a key energy source. To unlock hydrogen’s potential, it is crucial to prioritize the development of a more efficient, cost-effective, and environmentally friendly production process. Enhancing the efficiency and scalability of these technologies will not only reduce their environmental impact but also accelerate the adoption of hydrogen as a viable alternative energy solution, fostering a cleaner and more sustainable future. This paper presents a study on simulating a heat recovery system in an alkaline electrolyser consisting of 30 cells, which integrates a plate heat exchanger to preheat the water entering the system, and assessing how it affects efficiency. The study uses a thermal model, employing the concept of lumped thermal capacitance, to analyze the impact of the heat recovery system utilization on the overall performance of the electrolyser. MATLAB/Simulink was used to simulate and provide a detailed visualization of how recovery systems affect the electrolyser’s efficiency. The results of the simulations confirmed that incorporating a heat recovery system significantly improves the efficiency of alkaline electrolysers up to 8%. The study provides a promising outlook for the future of hydrogen production, emphasizing the potential of waste heat recovery systems to make green hydrogen production more viable and sustainable. Full article

Supercritical carbon dioxide (SC-CO₂) power cycles offer a promising solution for offshore platforms’ gas turbine waste heat recovery due to their compact design and high thermal efficiency. This study proposes a novel parallel-preheating recuperated Brayton cycle (PBC) using SC-CO₂ for waste heat recovery on offshore gas turbines. An integrated energy, exergy, and economic (3E) model was developed and showed good predictive accuracy (deviations < 3%). The comparative analysis indicates that the PBC significantly outperforms the simple recuperated Brayton cycle (SBC). Under 100% load conditions, the PBC achieves a net power output of 4.55 MW, while the SBC reaches 3.28 MW, representing a power output increase of approximately 27.9%. In terms of thermal efficiency, the PBC reaches 36.7%, compared to 21.5% for the SBC, marking an improvement of about 41.4%. Additionally, the electricity generation cost of the PBC is 0.391 CNY/kWh, whereas that of the SBC is 0.43 CNY/kWh, corresponding to a cost reduction of approximately 21.23%. Even at 30% gas turbine load, the PBC maintains high thermoelectric and exergy efficiencies of 30.54% and 35.43%, respectively, despite a 50.8% reduction in net power from full load. The results demonstrate that the integrated preheater effectively recovers residual flue gas heat, enhancing overall performance. To meet the spatial constraints of offshore platforms, we maintained a pinch-point temperature difference of approximately 20 K in both the preheater and heater by adjusting the flow split ratio. This approach ensures a compact system layout while balancing cycle thermal efficiency with economic viability. This study offers valuable insights into the PBC’s variable-load performance and provides theoretical guidance for its practical optimization in engineering applications. Full article

High regeneration energy demand remains a critical barrier to the large-scale deployment of ethanolamine-based (MEA-based) CO₂ capture. This study adopts an Al₂O₃ ceramic-membrane heat exchanger (CMHE) to recover both sensible and latent heat from the stripped gas. Experiments confirm that heat and mass transfer within the CMHE follow a coupled mechanism in which capillary condensation governs trans-membrane water transport, while heat conduction through the ceramic membrane dominates heat transfer, which accounts for more than 80%. Guided by this mechanism, systematic structural optimization was conducted. Alumina was identified as the optimal heat exchanger material due to its combined porosity, thermal conductivity, and corrosion resistance. Among the tested pore sizes, CMHE-4 produces the strongest capillary-condensation enhancement, yielding a heat recovery flux (q value) of up to 38.8 MJ/(m² h), which is 4.3% and 304% higher than those of the stainless steel heat exchanger and plastic heat exchanger, respectively. In addition, Length-dependent analyses reveal an inherent trade-off: shorter modules achieved higher q (e.g., 14–42% greater for 200-mm vs. 300-mm CMHE-4), whereas longer modules provide greater total recovered heat (Q). Scale-up experiments demonstrated pronounced non-linear performance amplification, with a 4 times area increase boosting q by only 1.26 times under constant pressure. The techno-economic assessment indicates a simple payback period of ~2.5 months and a significant reduction in net capture cost. Overall, this work establishes key design parameters, validates the governing transport mechanism, and provides a practical, economically grounded framework for implementing high-efficiency CMHEs in MEA-based CO₂ capture. Full article

This study investigates the feasibility of using waste heat from generator sets as the low-temperature heat source for heat pumps in off-grid energy systems, addressing the need for more efficient and self-sufficient heating solutions. A conceptual model was developed in which a generator and an air-to-water heat pump operate within an insulated thermal chamber, enabling the recovery of waste heat to maintain a stable 15 °C inlet temperature for the heat pump. Theoretical analysis was supplemented with preliminary experimental tests performed on a small generator placed in a thermally insulated enclosure. Measurements of temperature rise and heat output allowed for verification of the real heat-recovery efficiency, which reached approximately 28%. Based on real household heating demand, this study evaluated annual heat demand, heat pump electricity consumption, and fuel requirements for several recovery scenarios (28%, 45%, and 60%). The results show that maintaining a constant 15 °C source temperature significantly improves heat-pump efficiency, reducing annual electricity demand. Increasing heat-recovery efficiency from 28% to 60% reduces fuel consumption by more than half and lowers the annual operating costs. The findings confirm the potential of generator-supported heat-pump systems to enhance energy efficiency in off-grid applications and provide a sound basis for further optimization and real-scale validation. Full article

The waste heat generated by high-performance computing (HPC) represents an opportunity for advancing the decarbonization of energy systems. Seasonal storage is necessary to regulate the balance between waste heat production and demand. High-temperature aquifer thermal energy storage (HT-ATES) is a particularly well-suited technology for this purpose due to its large storage capacity. However, integrating HT-ATES into energy systems for district heating is complex, affecting existing components. Therefore, this study applies a bi-objective mixed-integer quadratically constrained programming (MIQCP) approach to optimize the energy system at Forschungszentrum Jülich (FZJ) regarding total annualized costs (TAC) and global warming impact (GWI). The exascale computer Jupiter, which is hosted at FZJ, generates a substantial amount of renewable waste heat that is suitable for integration into district heating networks and seasonal storage. Case studies show that HT-ATES integration into the investigated system can reduce GWI by 20% and increase TAC by 1% compared to the reference case. Despite increased TAC from investments and heat pump (HP) operation, summer charging of the HT-ATES remains flexible and cost-effective. An idealized future scenario indicates that HT-ATES with a storage capacity of 16,990 MWh and HPs could cover most of the heating demand, reducing GWI by up to 91% while TAC increases by 6% relative to the reference system. Full article

With the rapid advancement of integrated thermal management systems (ITMS) for new energy vehicles (NEVs), flow losses and hydrodynamic characteristics within multi-way valves have become critical determinants of system performance. In this study, a three-dimensional computational fluid dynamics model is established for a multi-way valve used in a representative NEV ITMS, where PAG46 coolant is employed as the working fluid. The steady-state pressure-loss characteristics under three typical operating modes—cooling, heating, and waste heat recovery—are investigated, together with the transient hydrodynamic response during mode switching. The steady-state results indicate that pressure losses are primarily concentrated in regions with abrupt changes in flow direction and sudden variations in cross-sectional area, and that the cooling mode generally exhibits the highest overall pressure loss due to the involvement of all flow channels and stronger flow curvature. Furthermore, a parametric analysis of the valve body corner chamfers and valve spool fillets reveals a non-monotonic dependence of pressure drop on chamfer radius, highlighting a trade-off between streamline smoothness and the effective flow cross-sectional area. Transient analysis, exemplified by the transition from heating to waste heat recovery mode, demonstrates that dynamic changes in channel opening induce a significant reconstruction of the internal velocity and pressure fields. Local high-velocity zones, transient pressure peaks, and pronounced fluctuations of hydraulic torque on the valve spool emerge during the switching process, imposing higher requirements on the torque output and motion stability of the actuator mechanism. Consequently, this study provides a theoretical basis and engineering guidance for the structural optimization and actuator matching of multi-way valves in NEV thermal management systems. Full article

Growing cooling demand and environmental concerns motivate research into alternative technologies capable of converting low-grade heat into useful cooling. This study proposes a regression-assisted multi-objective optimisation framework using the Ant Lion Optimiser and its multi-objective variant to jointly maximise the coefficient of performance (COP), cooling capacity ($Q_{cc}$) and waste-heat recovery efficiency (${\eta }_e$). Pareto-optimal solutions exhibit a one-dimensional ridge in which ${\eta }_e$ declines, and COP and $Q_{cc}$ increase simultaneously. Within the explored bounds, non-dominated ranges span COP = 0.674–0.716, $Q_{cc}=$ 18.3–27.5 kW and ${\eta }_e=$ 0.118–0.127, with a practical compromise near COP ≈ 0.695, $Q_{cc}$ ≈ 24 kW and ${\eta }_{e }\approx$0.122–0.123. Compared to the typical reported COP band for single-stage silica-gel/water ADCs, the practical compromise solution (COP ≈ 0.695) offers a conservative COP improvement of approximately 16% when benchmarked against COP = 0.6, while the compromise $Q_{cc}$ ($Q_{cc}$ ≈ 24 kW) represents a conservative increase of approximately 20% relative to the upper product-class reference (20 kW). A one-at-a-time sensitivity analysis with re-optimisation identifies the hot- and chilled-water inlet temperatures and exchanger conductance as the dominant decision variables and maps diminishing-return regions. This framework can effectively utilise low-grade heat in future low-carbon buildings and processes, supporting the configuration of ADC systems. Full article

The global shift toward renewable energy and circular economy models requires industrial systems that minimize waste and recover value across entire life cycles. This review synthesizes recent advances in by-product recovery technologies supporting renewable energy and circular industrial processes. Thermal, biological, chemical/electrochemical, and biotechnological routes are analyzed across battery and e-waste recycling, bioenergy, wastewater, and agri-food sectors, with emphasis on integration through Life Cycle Assessment (LCA), techno-economic analysis (TEA), and multi-criteria decision analysis (MCDA) coupled to process simulation, digital twins, and artificial intelligence tools. Policy and economic frameworks, including the European Green Deal and the Critical Raw Materials Act, are examined in relation to technology readiness and environmental performance. Hybrid recovery systems, such as pyro-hydro-bio configurations, enable higher resource efficiency and reduced environmental impact compared with stand-alone routes. Across all technologies, major hotspots include electricity demand, reagent use, gas handling, and concentrate management, while process integration, heat recovery, and realistic substitution credits significantly improve life cycle outcomes. Harmonized LCA-TEA-MCDA frameworks and digitalized optimization emerge as essential tools for scaling sustainable, resource-efficient, and low-impact industrial ecosystems consistent with circular economy and renewable energy objectives. Full article

High renewable energy penetration in Integrated Energy Systems (IES) introduces significant challenges related to bilateral source-load uncertainty and low-carbon economic dispatch. To address these issues, this paper proposes a novel scheduling framework that synergizes data-driven scenario generation with multi-objective distributionally robust optimization (DRO). Specifically, a deep temporal feature extraction model based on Long Short-Term Memory Autoencoder (LSTM-AE) is integrated with K-Means clustering to generate four typical operation scenarios, effectively capturing complex source-load fluctuations. To further enhance system efficiency and environmental sustainability, a refined Power-to-Gas (P2G) model considering waste heat recovery is developed to realize energy cascading, coupled with a joint market mechanism that integrates Green Certificate Trading (GCT) and tiered carbon pricing. Building on this, a multi-objective DRO model based on Conditional Value at Risk (CVaR) is formulated to optimize the trade-off between operating costs and carbon emissions. Case studies based on California test data demonstrate that the proposed method reduces total operating costs by 9.0% and carbon emissions by 139.9 tons compared to traditional robust optimization (RO). Moreover, the results confirm that the system maintains operational safety even under extreme source-load fluctuation scenarios. Full article

Growing demand for computing resources is increasing electricity use and cooling needs in data centres (DCs). Simultaneously, it creates opportunities for decarbonisation through the integration of waste heat (WH) into district heating (DH) systems. Such integration reduces primary energy (PE) consumption and emissions, particularly in low-temperature DH networks. In this study, the possibility for utilisation of WH from DC hybrid cooling system into third generation (3G), fourth generation (4G), and fifth generation (5G) DH systems is investigated. The work is based on the dynamic simulations in TRNSYS. The model of the hybrid cooling system consists of a direct liquid cooling (DLC) loop (25–30 °C) and a chilled water rack coolers (CRCC) loop (10–15 °C). For 3G DH, a high-temperature water-to-water heat pump (HP) is applied to ensure the required water temperature in the system. Measured meteorological and equipment data are used to reproduce real DC operating conditions. Relative to the reference system, integrating WH into 5G DH reduces PE consumption and CO₂ emissions by 88%. Results indicate that integrating WH into 5G DH and 4G DH minimises global cost and achieves a payback period of less than one year, whereas 3G DH, requiring high-temperature HPs, achieves 14 years. This approach to integrating waste heat from a hybrid DLC+CRCC DC cooling system is technically feasible, economically and environmentally viable for planning future urban integrations of waste heat into DH systems. Full article

Electrolytic aluminum is one of the most energy-intensive industrial processes and offers strong potential for demand-side flexibility and renewable energy integration. However, existing studies mainly focus on operational scheduling, while comprehensive planning frameworks at the industrial-park scale remain limited. This study proposes an optimal planning framework for electrolytic aluminum that co-optimizes renewable energy investments, waste heat recovery, and green power trading while capturing the temperature safety constraints of electrolytic cells. The electrolytic aluminum process is explicitly modeled with heat exchangers to enable combined cooling–heating–power supply for nearby users. A wind power priority subscription mechanism and green certificate compliance are incorporated to enhance practical applicability and support future decarbonization requirements. Moreover, a two-stage particle swarm-deterministic optimization scheme is developed to provide a tractable solution to the inherently nonconvex mixed-integer nonlinear model. Case studies based on a real plant in Xinjiang, China, demonstrate that the proposed framework can raise the green electricity aluminum share to 60.4%, reduce annual carbon emissions by 52.0%, and significantly increase total system profit compared with the benchmark configuration, highlighting its economic and sustainability benefits for industrial park development. 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

The paper focuses on the characteristics of fouling from copper production on the tube surface in a waste heat recovery boiler during the transfer of heat from the flash furnace process gas. The likely mechanism of deposit formation on the tubes is described, and the morphology and chemical composition of the bound deposit taken from the radiation zone of the waste heat recovery boiler are reviewed. In addition, the impact of the presence of bound and loose deposits on the tube’s surface on the increase in the deposit surface temperature and the decrease in the heat transferred at the inner side of the tube is evaluated. Changes in the chemical, mineralogical, and phase constitutions along the thickness of the build-up were established on the basis of XRF, SEM, and XRD quantitative analyses. The heat exchanger tube temperature distribution was computed with the finite element method using an axi-symmetrical solution of the heat conductivity equation. Computing was carried out for a clean tube surface as well as for a case with loose and bound deposits present on the surface, with thicknesses of 0.5 cm, 1 cm, and 2 cm. The boundary conditions at the deposit side varied. For loose deposits with a thickness of 0.5 cm, the decline in the heat transferred was similar to the values obtained for a bound deposit with a thickness of 2 cm. It was established that, for a deposit with a thickness of 20 mm, there was an approximately 80% decline in the energy transferred by the walls compared to the clean tube surface. This study represents a novel approach by integrating mineralogical and phase analyses with finite element modelling to comprehensively assess the impact of both bound and loose deposits on heat transfer efficiency in waste heat recovery boilers from copper production. Full article

Integrating electrochemical fuel cells and internal combustion engines can enhance the total efficiency and sustainability of power systems. This study presents a promising solution by integrating a Proton Exchange Membrane Fuel Cell (PEMFC) with a mini gas turbine, forming a hybrid system called the “Oya System.” This approach aims to mitigate the efficiency losses of gas turbines during high ambient temperatures. The hybrid model was designed using Aspen Plus for modelling and the EES simulation program for solving mathematical equations. The primary objective of this research is to enhance the efficiency of gas turbine systems, particularly under elevated ambient temperatures. The results demonstrate a notable increase in efficiency, rising from 37.97% to 43.06% at 10 °C (winter) and from 31.98% to 40.33% at 40 °C (summer). This improvement, ranging from 5.09% in winter to 8.35% in summer, represents a significant achievement aligned with the goals of the Oya System. Furthermore, integrating PEMFC contributes to environmental sustainability by utilising hydrogen, a clean energy source, and reducing greenhouse gas emissions. The system also enhances efficiency through waste heat recovery, further optimising performance and reducing energy losses. This research highlights the critical role of interface engineering in the hybrid system, particularly the interaction between the PEMFC and the gas turbine. Integrating these two systems involves complex interfaces that facilitate the transfer of electrochemistry, energy, and materials, optimising the overall performance. This aligns with the conference session’s focus on green technologies and resource efficiency. The Oya System exemplifies how innovative hybrid systems can enhance performance while promoting environmentally friendly processes. Full article

Thermoelectric systems configured in multistring arrays of thermoelectric generators (TEGs) represent a promising solution for energy harvesting in environments with non-uniform thermal gradients. However, the presence of multiple maximum power points (MPPs) in such configurations poses significant challenges to energy extraction efficiency. This study presents a comprehensive performance evaluation of four maximum power point tracking (MPPT) algorithms, Perturb and Observe (P&O), Incremental Conductance (InC), Particle Swarm Optimization (PSO), and Genetic Algorithm (GA), applied to multistring thermoelectric generator (TEG) arrays under multiple and asymmetric thermal gradients. The simulated systems, modeled in MATLAB/Simulink, replicate real-world thermoelectric configurations by employing series-parallel topologies and eleven distinct thermal scenarios, including uniform, localized, and sinusoidal temperature distributions. The key contribution of this work lies in demonstrating the superior capability of metaheuristic algorithms (PSO and GA) to locate the global maximum power point (GMPP) in complex thermal environments, outperforming classical methods (P&O and InC), which consistently converged to local maxima under multi-peak conditions. Notably, PSO achieved the best average convergence time (0.23 s), while the GA recorded the fastest response (0.05 s) in the most challenging multi-peak scenarios. Both maintained high tracking accuracy (error ≈ 0.01%) and minimized power ripple, resulting in conversion efficiencies exceeding 97%. The study emphasizes the crucial role of algorithm selection in maximizing energy harvesting performance in practical TEG applications such as embedded systems, waste heat recovery, and autonomous sensor networks. Future directions include physical validation through prototypes, incorporation of dynamic thermal modeling, and development of hybrid or AI-enhanced MPPT strategies. Full article