Energy Conversion and Management-X最新文献

Electromagnetic vibrational harvesters are low-cost devices featuring high-power densities and robust structures, often used for capturing the energy of environmental vibrations (civil infrastructures, transportation, human motion, etc.,). Based on Faraday’s law, energy generation relies on the modification of the magnetic field distribution within a magnetic element caused by mechanical vibrations inducing an electromotive force (EMF) in a pick-up coil. However, the practical implementation of this type of vibrational harvester is currently limited due to the reduced generated power under low-frequency vibrations. In this work, an electromagnetic vibrational harvester is experimentally characterized and analyzed employing magnetic circuit analysis. The harvester consists of a ferromagnetic U-shaped cantilever, a NdFeB magnet and a ferrite magnet used as “magnetic tip mass” to enhance the magnetic flux changes under vibrations of frequency < 100 Hz. For this configuration, an experimental voltage of ∼ 1.2 V peak-to-peak (open circuit) was obtained at a resonant frequency of 77 Hz, enabling the subsequent electronic rectification stage. Additionally, Finite Element Method (FEM) is used to explore different design possibilities including the modeling of complex geometries, mechanical properties and non-linear magnetic materials, enabling the tuning of the resonance frequency from 51 to 77 Hz, keeping constant the induced voltage.

Over time, the use of wind turbines has evolved in terms of the size and number of the turbines. The change in wind turbines comes as a result of major structural changes and then an increase in their production capacity. In the framework of the most stable operation for the surface of the terrain used in this study, a series of configurations have been proposed that are directly related to technical and economic sustainability. The complete scenarios will be realized in Koznica, where one-year measurements are done. In the framework of the realized scenarios, it can be seen that there is variability in terms of energy output from these configurations, which maximally comes from wake losses caused by the terrain. In cases where the scenarios with the addition of small turbines are studied, they, in the technical aspect, affect the increase in energy production, which, if those turbines were not installed, would not be applied. As an important part, the economic aspect of the realization of the previous optimization scenarios is analyzed by using Monte-Carlo simulation for LCOE analysis. Thus, it can be concluded that the analyzed scenarios with the addition of small turbines in the optimization process are more suitable and feasible for implementation.

Effective treatment of plant biomass with potentially toxic elements (PTEs) is crucial for phytoremediation. Hydrothermal carbonization (HTC) offers an economical and eco-friendly solution by converting biomass into high-value hydrochar. However, the effects of reaction temperature and medium on the characteristics and metals distribution in hydrochars from PTEs-containing biomass remain unclear. This study explores the effects of different hydrothermal temperature (180–240 °C) and reaction media (H₂O, HCl, H₂SO₄, H₃PO₄) on the hydrothermal properties of willow biomass containing PTEs, and the distribution and transfer rules of PTEs (Cd and Zn) and the application potential of hydrochar. The results indicated that hydrothermal temperature and acid medium significantly influenced WB conversion, affecting hydrochar properties such as carbonization degree and surface functional groups. Higher hydrothermal temperatures enhanced Cd and Zn fixation in the solid phase, while acid facilitated their migration to the liquid phase. More than 91.08 % of Cd and 88.41 % of Zn in the acid-added system are migrated into the liquid phase at hydrothermal temperature of 180 °C Hydrochar prepared under 180 °C and H3PO4 exhibited excellent adsorption performance for Cd²⁺ and Cu²⁺ (2.17 mg/g and 34.38 mg/g, respectively) in aqueous solution. Additionally, hydrochars exhibit high calorific values (20.52–28.01 MJ/kg), suggesting their potential as biofuel. This study provides technical foundation to support the resource processing and safe utilization of forest biomass containing PTEs.

This research examines four categories of international bulk carriers and forecasts their ability, from 2025 to 2050, to meet the IMO targets for emission reduction: a 20% reduction by 2030 and a 70% reduction by 2040 compared to 2008 levels, with the ultimate aim of achieving net-zero emissions by 2050, utilizing a life cycle assessment (LCA) methodology. It evaluates various scenarios involving different rates of ship demolition and alternative fuel adoption to achieve these targets. Additionally, it investigates the potential costs associated with carbon credits and natural carbon sinks (such as seagrass) in cases where emissions targets are not met. The findings suggest that, under the baseline scenario and Scenario 1, despite increased usage of alternative fuels and declining emission factors, none of the four ship types meet the IMO targets in terms of life cycle greenhouse gas (GHG) emissions. However, in Scenario 2, where the ship demolition rate steadily increases until the usage of traditional fuel ships reaches zero, and with concurrent reductions in emission factors, emissions decrease substantially and approach the desired targets, though they still fall short. Furthermore, the study analyzes the financial implications of employing carbon credits versus natural carbon sinks to offset emission shortfalls, indicating that Scenario 2 is comparatively less costly. It also demonstrates that leveraging natural carbon sinks is more cost-effective in reducing emission expenses compared to relying solely on carbon credits. Consequently, the research recommends prompt adoption of alternative fuels, acceleration of ship demolition rates, and utilization of natural carbon sinks not only to meet international shipping emission reduction objectives but also to rejuvenate marine ecosystems, thereby fortifying marine environments.

Transformation of municipal solid waste into refuse-derived fuel (RDF) offers a promising solution for waste-to-energy conversion. In this context, a systematic literature review and scientometric analysis is conducted showing refinements in RDF application for energy-from-waste (EfW) initiatives, forging a comprehensive approach to sustainable waste management. Key aspects of EfW projects using RDF are examined, focusing on methodologies for calorific value estimation, waste characterization, quality assessment, and public–private partnerships (PPPs). Emphasis is placed on the necessity of accurate energy potential measurement and advanced characterization techniques, including computer vision, for effective waste sorting and analysis. Quality assessments of RDF are highlighted for their impact on decisions within the biomass fuel supply chain, emphasizing the importance of optimizing energy recovery. PPP’s are identified as key to successful execution of EfW projects, with their roles, trends, and risk modeling crucial for fostering effective collaboration between public and private sectors. The study concludes by identifying research gaps, such as the deficiency of new frameworks to support technical assessments of waste processing facilities for strategic, tactical, and operational improvements. Additionally, RDF applications in EfW are limited because of inconsistent waste sorting, deviation from specifications and environmental regulations. This approach aims to enhance sustainable waste management and energy recovery, guiding future research and implementation in the field.

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.