Energy Conversion and Management-X最新文献

Thermoelectric generators (TEGs) are widely recognized as clean energy solutions that can convert low-grade waste heat into electricity through a temperature gradient. Despite their significant potential, challenges such as low conversion efficiency and high costs have limited their practical applications. In this paper, we present an innovative metamaterial design concept for TEGs with significantly improved efficiency. A Finite Element Model is validated using Bi_0.5Sb_1.5Te₃ bulk samples fabricated via the drop-cast method. This model can predict open-circuit voltage and output power as a function of an arbitrary metamaterial design using the commercial software ANSYS®. Four different metastructure designs, including 2D Triangular Honeycomb, Re-entrant, body-centered cubic (BCC), and triply periodic minimal surface (TPMS) structures, are systematically investigated. Through experiments and numerical analysis, the effects of annealing temperature, porosity, and unit cell numbers (UCNs) on the performance of TE legs are explored. It is found that 2D Triangular Honeycomb and BCC structures outperform other configurations due to their capacity to maintain a higher thermal gradient. Optimizing their porosity and UCNs can further enhance the output power. Compared to the traditional designs with bulk TE legs, implementing a 2D metastructure design with 30 % porosity and UCNs of 4 × 4 × 4 can lead to approximately a 100 % increase in power output.

In the context of greenhouse agriculture, the integration of Artificial Intelligence (AI) is evaluated for its potential to enhance sustainability and crop production efficiency. This study reanalyzes publicly available datasets, using advanced time series analysis and noise reduction techniques through seasonality detection and removal. This novel approach reveals trends more clearly, providing a detailed comparison between AI-driven methods and traditional agricultural practices. An extensive review of literature on AI applications in agriculture is conducted to establish a broad understanding of its current state and future prospects. The core focus is the Autonomous Greenhouses Challenge, an initiative where research teams apply AI technologies in real-world greenhouse settings. This challenge offers crucial data for a thorough assessment of AI’s practical impact. The analysis reveals that AI significantly reduces heating energy consumption, indicating a notable improvement in energy efficiency. However, reductions in CO₂ emissions, along with improvements in electricity and water usage, are only marginal when compared to traditional farming methods. Similarly, enhancements in crop quality and profitability achieved through AI are found to be on par with conventional techniques. These findings highlight the dual nature of AI’s impact in greenhouse agriculture: it shows significant promise in some areas, while its effectiveness in other key sustainability aspects remains limited. The study emphasizes the need for further research and investment in technological advancements, as well as the importance of a robust data infrastructure. It also highlights the necessity of education and training in AI technologies for effective implementation in the agricultural sector. The results of this research aim to inform policymakers, researchers, and industry stakeholders about the mixed impacts of AI on sustainable greenhouse farming. By offering a comprehensive evaluation of the benefits and challenges of AI integration, this study contributes to the ongoing discussion on sustainable agricultural practices and provides insights into the future direction of AI in this field.

This study presents the first attempt to explore the technical and financial feasibility of combining incentives for Italian Renewable Energy Communities (REC) with those for high-efficiency cogeneration. The community has local wooden biomass availability and was assembled around two prosumers: an industrial laundry with biomass-fuelled CHP and a school with photovoltaic panels. Other members include residential users. Electric loads were derived from available quarter-hour meters and electric bills. Thermal demand for the laundry was reconstructed from an energy audit. First, the CHP optimal mode of operation was selected among the two suggested by the manufacturer (matching the electric or the thermal load), providing energy, financial and environmental performance in both scenarios. Then the photovoltaic system of the school was sized. Finally, an optimal number of users was selected using a genetic algorithm, with financial performance of the REC as objective functions. Energy, economic and environmental impact performance of prosumers and REC are discussed, finding that the optimal configuration reduces CO₂ emissions by 722 tons/year, with further 1360 tons/year coming from biomass combustion. In an optimal REC configuration members cut 250 €/year of electric bills, with an overall performance of 21 % in valorization of shared energy, while a social-focused REC can increase its NPV from 233 to 769 k€. The scenario can be applied to other prosumers with similar thermal demand and can be replicated or adjusted to local requirements.

Hydrogen plays a crucial role in the transition to low-carbon energy systems, especially when integrated into energy storage applications. In this study, the concept of exergy-return on exergy-investment (ERoEI) is applied to investigate the exergetic efficiency (defined as the ratio of useful exergy output to invested exergy input) and CO₂ equivalent intensity of the hydrogen supply chain, with a specific focus on the underground hydrogen storage process. Our findings reveal that the overall exergetic efficiency of the electricity-to-hydrogen-to-electricity conversion process can reach up to 25 %. Among the hydrogen production methods, green hydrogen, produced via electrolysis powered by renewable energy, exhibits the lowest CO₂ equivalent intensity. Blue hydrogen, produced from natural gas with carbon capture, can significantly reduce the carbon footprint of electricity generation, though this advantage comes at the expense of decreased exergetic efficiency. Analysis further indicates that the exergetic efficiency of underground storage components ranges from 72 % to 92 %. A substantial fraction of the exergy is lost during compression and injection of the stored hydrogen. Nevertheless, the subsurface operations contribute a minimal CO₂ emission, between 1.46–4.56 grams of equivalent CO₂ per megajoule (gr-CO_2eq/MJ) when powered by low-carbon energy sources. Furthermore, it is found that hydrogen loss in the reservoir, along with methane and hydrogen leak during surface operations, notably affects the overall efficiency of the storage process.

In response to the urgent need for sustainable and resilient energy solutions, Hybrid Renewable Energy Systems (HRES) offer a promising alternative to single-source energy systems, providing safer and more cost-effective power generation. This study assesses the efficiency and cost-effectiveness of a hybrid renewable energy system without energy storage, concentrating on energy, economic, and environmental performance, in urban settings where surplus renewable electricity can be sold back to the utility grid. Four scenarios were evaluated using HOMER Pro software to determine the most efficient configuration. The analysis identified the optimal setup as a PV/wind/DG/grid system without energy storage. This configuration achieves a cost of energy (COE) of $0.0172/kWh, a return on investment (ROI) of 8.8 %, and a payback period of 7.64 years. The system includes 117 kW of solar PV, 6 kW of wind capacity, a 25-kW diesel generator for backup, and minimal grid reliance, resulting in 94.8 % renewable energy penetration and annual CO₂ emissions of just 7,460 kg. Sensitivity analysis indicates that increased solar and wind resources reduce costs, while higher loads and temperatures drive costs up. This study demonstrates the feasibility of providing reliable, sustainable energy without battery storage for urban campuses, showcasing significant economic and environmental benefits.

Marine macroalgae is a biomass resource for the manufacture of fuels and chemicals, which can be sustainably harvested from seaweed farms or from man-made structures where it accumulates as a biofouling organism. However, in temperate regions farmed macroalgae can only be harvested between late Spring and early Summer, limiting year-round availability. Here we show that a conventional grass ensilage procedure preserves Saccharina latissima dominated biomass on the tonne scale for 30 months, enabling year-round use of this biomass. Following processing, the resulting dried and pelletised ensiled macroalgae material was subject to Thermo-Catalytic Reforming™, comprising sequential pyrolysis (450 °C) and either dry or steam catalytic reforming (700 °C) processes. Both processing methods produced a mixture of bio-oil (1.6–1.9 wt%) and hydrogen-rich permanent gases (30.9–31.1 wt%) with higher heating values of 34.8–35.4 MJ/kg and 18.0–24.2 MJ/m³, respectively, together with char (45.5–48.5 % wt). The permanent gases can be used directly for heat generation, while hydro-treatment of the bio-oil would afford a material that can be blended with traditional transport fuels. This work demonstrates that if operated at scale, the combined harvesting, ensilaging and Thermo-Catalytic Reforming™ of preserved macroalgal biomass offers a year-round decentralised energy resource.

Managing agricultural waste by burning it in the fields is a straightforward method, but leads to significant pollution. One promising alternative is to convert agricultural waste into solid fuel, such as charcoal, to support renewable energy from biomass. The quality of barbecue charcoal depends upon selecting suitable materials and employing heating methods to ensure efficient transformation. This research aims to study the charcoal conversion process from agricultural waste using two types of kilns: 1) direct heating (gasification kiln: GK) and 2) indirect heating (pyrolysis kiln: PK) designed to recirculate syngas from wood as fuel for the pyrolysis process. The study tested three types of agricultural waste materials, including coconut shells (CS), cassava rhizome (CR), and acacia wood (AW), to examine the differences in charcoal produced by the two heating methods. The tests revealed that the maximum temperatures inside the kilns were 792.45 ± 127.18 °C, 907.67 ± 37.3 °C, and 980.07 ± 110.56 °C for the GK, and 921.88 ± 57.84 °C, 801.93 ± 10.16 °C, and 937.82 ± 95.85 °C for the PK. The charcoal from the PK exhibited higher calorific values than the GK, with 7474.68 ± 36.62, 6429.04 ± 72.22, and 7268.33 ± 52.86 calories per gram. The charcoal yield was also higher in the PK, at 31.29 ± 4.39, 34.33 ± 3.39, and 17.58 ± 2.09 percent for coconut shells charcoal (CSC), cassava rhizome charcoal (CRC), and acacia wood charcoal (AWC), respectively. However, the PK required more fuel and longer ignition times. The resulting charcoal from the slow pyrolysis process in the PK is suitable as barbecue fuel due to its size, which is similar to the original material. In contrast, the charcoal from the GK, which tends to shrink or break into smaller pieces, is more suitable for grinding into briquettes. This study provides a guideline for producing high-quality barbecue charcoal, offering commercial benefits including the gasification and pyrolysis processes that improve combustion efficiency and reduce pollution by producing high-quality gas for fuel, unlike traditional kilns that emit a large amount of CO during the conversion of wood to charcoal and enabling the selection of appropriate raw materials for different heating methods to maximise the utility of the products. This approach adds value to agricultural raw materials and helps effectively manage agricultural waste (zero waste) for further utilisation and development.

Adsorption cooling systems (ACS) powered by low-temperature heat offer an energy-efficient and environmentally friendly alternative to traditional vapor-compression systems. The effectiveness of ACS is significantly influenced by the alignment of the adsorbent properties with the operating conditions of the cycle. Metal-Organic Frameworks (MOFs) are considered the next generation of water harvesting and ACS. Many MOFs are synthesized and tested for water harvesting systems, one of these MOFs is MOF-303 which was reported to have very rapid water sorption dynamics under atmospheric conditions. However, MOF-303 has never been tested under the same conditions as ACS (under vacuum). In this study, the isotherms and kinetics of water adsorption on MOF-303, as an efficient adsorbent of water vapor, is experimentally investigated for the ACS using the linear driving force model. The diffusion coefficients across a wide range of relative pressures under two different temperatures were estimated. The study compares the adsorption process of MOF-303 with traditional silica gel (SG) in the context of diffusion kinetics relevant to ACS. Based on the output and at a constant temperature of 25 °C and across all relative pressure ranges, MOF-303 exhibited an average increase of approximately eight times in diffusion kinetics compared to SG. Specifically, within the relative pressure range of 10–30 %, which is optimal for ACS, MOF-303 demonstrated a seven-fold increase in diffusion kinetics over SG. The diffusion values for SG display a clear upward trend with increasing temperature. In contrast, the diffusion values for MOF-303 are subject to fluctuations with temperature changes under investigation. Notably, the isotherm for MOF-303 shows an inflection point at relative pressures between 10–15 %, causing a significant reduction in diffusion at these specific relative pressures compared to other relative pressure values. The findings in this study highlight the potential use of MOF-303 as a highly efficient water adsorbent for the ACS which will enable scientists and engineers to develop sustainable low-grade energy systems.

This research puts forward the modeling of a Hydrogen Fuel Cell Electric Vehicle (HFCEV) and its validation, in comparison with battery electrical vehicle (BEV) based on a postal vehicle and its subsystems. The main investigation parameters are the amount of hydrogen consumed, and the change in the state of charging of the battery. For the profile of the same speed route, an HFCEV model and a BEV model, consisting of multiple subsystems, were developed, and simulated in the MATLAB® Simulink environment. We make use of various sources of drive cycles to obtain our outcomes such as the New European Diving Cycle (NEDC). By running simulations for different stages, we are able to generate simulation results. The discrepancies in the graphs and the visual demonstrations guided us to variable conclusions on how different factors affect an electric vehicle’s performance and efficiency. The simulation result shows that the (BEV) is 30% more effective for NEDC drive cycle comparing with (HFCEV).

This article conducted a comprehensive study on a three-story residential building in Yazd, Iran, which was meticulously modeled using DesignBuilder. The primary objective was to investigate the impact of BioPCMs (Bio Phase Change Materials), which are environmentally friendly materials, on the building’s thermal performance. For this purpose, BioPCM® M182/Q21 was selected due to its effectiveness in enhancing energy efficiency. The study involved a practical comparison of the building’s energy consumption under three scenarios. The first scenario represented the baseline condition where no PCM was used. The second scenario incorporated PCM into the external walls, while the third scenario extended the use of PCM to both the external and internal walls. In the second scenario, where PCM was applied only to the external walls, there was a 9% reduction in annual energy consumption. The third scenario, which utilized PCM in both the external and internal walls, resulted in a reduction of 15.5% in annual energy consumption. Additionally, when PCM was used in both the external and internal walls, the total energy consumption for cooling and heating the building decreased by 5.4% and 18.9%, respectively.