Abstract

This study addresses the issue of reduced driving range in electric vehicles under cold climate conditions by developing a phase change material-based thermal energy storage system. Through numerical simulation, the effects of different fin quantities and fin arrangement on the solidification process of the phase change material were systematically investigated. The results demonstrate that increasing the number of fins significantly enhances solidification rates, albeit with diminishing marginal returns. Furthermore, the fin arrangement substantially impacts solidification process, while moderate top-concentrated arrangements can shorten solidification time, excessive concentration conversely prolongs the process.

Abstract

The carbon emissions from the construction sector account for a large proportion of the total carbon emissions in society. Energy-saving retrofitting of existing buildings has become an important means to achieve carbon reduction in the construction sector. This study statistically analyzes the basic conditions, retrofitting measures, and retrofitting effects of 76 projects in a retrofitting practice in Shenzhen. It summarizes the practical experiences in retrofitting existing public buildings. The analysis reveals that the measures for light systems, domestic hot water, and air conditioning systems were widely adopted in these energy-saving projects, with generally positive results. The energy-saving rates were mostly concentrated in the range of 0-20%. Moreover, this study analyzes building retrofitting policies from Shenzhen and compares them with actual practices. It serves as a reference for future building energy-saving retrofit strategies.

Abstract

Methanol steam reforming (MSR) is a promising technology capable of continuous and efficient hydrogen production. The miniaturization of the reforming system through microreactors is the preferred choice for distributed mobile hydrogen production. However, the highly integrated design inherently limits heat and mass transport efficiency, which can reduce device lifespan and severely constrain improvements in hydrogen production performance. To enhance the heat and mass transfer and chemical reaction performance within the reforming system, this study employs the variable density method to conduct a topology optimization design of the flow channel structure for a 2D MSR microreactor. The governing equations and objective functions within the design domain are reformulated, and the finite element method is adopted to simulate the fluid flow, heat transfer, and chemical reaction processes occurring in the MSR microreactor. Performance comparisons are made against a homogeneous porous reforming microreactor. The results demonstrate that the microreactor obtained via topology optimization develops thicker flow channels at the inlet and outlet while generating fine-branched channel structures during the gradual structural evolution process. Compared with the homogeneous porous microreactor, the TO-III microreactor exhibits an 87.49% increase in Nusselt number, along with an optimal methanol conversion rate. This study provides a general and potentially highly effective method for improving hydrogen production microreactors.

Abstract

Passive sky radiative cooling systems, which utilize the universe as a natural heat sink, have emerged as a critical technology for providing low-carbon solutions to urban cooling. Surface downwelling longwave radiation (SDLR), originating from the atmosphere, significantly influences the cooling potential of such systems. Therefore, accurately estimating SDLR is pivotal for the design and performance evaluation of these cooling systems. However, real-time SDLR data is generally scarce or lacks accuracy, primarily due to the complex interactions between atmospheric radiation and the inherent variability of clouds. To address this challenge, this work proposes a novel K-means-multilayer perceptron (MLP) model to estimate cloud optical properties and SDLR using high-resolution (5-min, 2-km) geostationary satellite imagery combined with an enhanced two-stream, spectrally resolved radiative model. When validated against one year (2019) of SDLR measurements from the Surface Radiation Budget Network (SURFRAD) across diverse climatic regions in the contiguous United States, the proposed model achieves root mean square error values ranging from 20-25 W/m² across all stations. These findings highlight the capability of this data-driven model to deliver low-latency, accurate estimations of cloud optical properties and SDLR using real-time satellite imagery. The advancement provides promising tools and atmospheric data sources to support the development of advanced sustainable energy systems in urban environment.

Abstract

Solar-driven methane dry reforming represents a promising approach for converting greenhouse gases into syngas using renewable energy, offering both environmental and energy benefits. However, conventional methane dry reforming systems are typically plagued by low solar-to-fuel conversion efficiency and limited syngas yield, primarily due to inefficient heat utilization and poor reactor scalability. In this study, a kilowatt-scale solar-driven methane dry reforming systems incorporating a cavity-type solar reactor and a self-synthesized porous Ni/CeO₂ catalysts was developed. The system was evaluated under varying feeding rates to identify its thermochemical performance. The results demonstrated that the new system achieves a maximum solar-to-fuel conversion efficiency of 33.26%, with CH₄ and CO₂ conversions of 69.36% and 66.50%, respectively, the product generation rate is the L/min level, and can operate continuously for over 8 hours. The work highlights the potential of porous Ni/CeO₂ catalysts in high-flux solar methane dry reforming systems. It presents a scalable and efficient method for solar-natural gas hybrid fuel production, offering valuable insights for industrial solar thermochemical applications.

Abstract

Realization of carbon neutrality and net zero emission policies require a detailed vision of the target energy systems and accurate planification of the transition paths. Open-Source Energy System Optimization Models (ESOMs) are consolidated tools used to back policy makers and stakeholders to examine technological and economic requirements of such goals. Nevertheless, the restriction of these tools to only-energy commodities represent a significant drawback of such models since they may lead to overlooking impact of the actions on resources with other natures. In addition, it is essential to evaluate the feasibility of the policies considering the availability restrictions and limits of other resources. Water is one of the commodities that is highly tight with energy systems, whether directly or indirectly. This paper presents a methodology for water-energy nexus implementation within the upstream and residential sectors of the TEMOA-Piedmont open-source ESOM.

Abstract

The transport industry is currently facing significant challenges as it is transitioning toward low-emitting technologies. Uncertainty about the future evolution of the transport sector may discourage the adoption of more sustainable solutions, promoting the continued reliance on fossil-fuel based technologies. Indeed, most of the current investments are devoted to battery electric vehicles, that may represent a valuable solution in specific conditions, such as urban transportation. However, not all the sectors can be efficiently electrified as cars. In this regard, the adoption of sustainable fuels may lead to an emission reduction in both urban and extra urban areas. The deployment of synthetic fuels obtained from CO2 capture, biofuels and hydrogen may replace the traditional fossil fuels and support the transport electrification. The urgent need to address future uncertainty and identify effective solutions to reduce the transport sector impact can be supported by tools like Energy System Optimization Models. These models enable the optimization of the future evolution of energy systems under specific assumptions. This study aims at identifying potential solutions for decarbonizing the hard-to-abate transport sectors, that cannot be effectively addressed by battery technologies. Focusing on the Italian transport sector, the TEMOA-Italy model is adopted to analyze possible future scenarios involving the deployment of alternative low-emitting fuels.

Abstract

Rural dwellings in cold regions face the dual challenge of reducing energy consumption while maintaining thermal comfort and daylight. Although sunspaces are effective passive solar strategies, their optimization remains underexplored due to complex variable interactions and conflicting performance goals. This study proposes a multi-objective optimization framework to evaluate and enhance sunspace design in cold-climate rural buildings. Four comparative scenarios are established to decouple sunspace effects from baseline building performance: (1) unoptimized building, (2) optimized building, (3) unoptimized building with sunspace, and (4) optimized building with sunspace. Optimization integrates a genetic algorithm with EnergyPlus and Radiance simulations, targeting total energy demand (EDtot), thermal comfort (PNTave), and daylighting (UDIave). Sensitivity analysis highlights key variables such as window-to-wall ratio and solar heat gain coefficient (SHGC). A two-stage assessment compares cost-free and cost-constrained scenarios. Results show that combining an optimized envelope with a sunspace achieves the best outcome, reducing EDtot by 89.82% and raising PNTave to 77.66%. Optimizing the envelope alone reduces EDtot by 62.41% with a 1.91-year payback, while a cost-constrained sunspace alone provides limited improvement (14.85% EDtot reduction). This structured approach isolates the impact of sunspaces and offers practical guidance for cost-effective retrofits of rural housing in cold regions.

Abstract

With the growth of renewable energy installed capacity, power systems urgently require flexible resources to participate in demand response, and electrolytic aluminum enterprises possess excellent load regulation potential. However, traditional demand response mechanisms suffer from poor execution effectiveness and singular incentives, making it difficult to fully mobilize enterprise participation enthusiasm. This paper establishes a comprehensive decision-making model for electrolytic aluminum enterprise participation in electricity markets to provide demand response. First, a user credit evaluation model based on improved subscription performance indicators is proposed, and a subsidy mechanism combining credit incentives with segmented assessment is constructed, linking credit scores with subsidy prices to form positive incentives. Then, considering production stability, an electrolytic aluminum load model incorporating power, temperature, and daily production constraints is established. Finally, case study analysis demonstrates that after adopting the proposed method, the electrolytic aluminum enterprise’s credit value increases by 22.3% and overall revenue grows by 24.6%, validating the effectiveness of the proposed model.

Abstract

This study aims to reveal the plugging mechanism of nanocellulose, a natural and environmentally friendly nanomaterial, in porous media with different permeabilities. To achieve this, we designed three homogeneous 2.5D microfluidic chips with varying permeabilities and one heterogeneous microfluidic chip, and conducted dynamic experiments to observe the plugging effects of nanocellulose. The results show that nanocellulose migrates, captures, and aggregates, blocking the pore throats in porous media, significantly improving the heterogeneity of the model and expanding the displacement volume. In the homogeneous low-permeability chips, the permeability reduction was more pronounced, and the degree of permeability reduction showed an approximately linear relationship with the amount of nanocellulose injected. Under water-flooding conditions, the permeability reduction was greater compared to gas-flooding, indicating that nanocellulose contributes to enhancing the relative permeability of the gas phase. In the heterogeneous model, nanocellulose exhibited stronger plugging effects on high-permeability channels, further reducing the heterogeneity of the model. This study provides new experimental evidence for the application of nanocellulose in plugging porous media, demonstrating its broad potential for industrial applications.