Sustainable Energy Technologies and Assessments最新文献

英文中文

Assessment of performance and quality indices of glutinous rice under different drying methods

IF 7.1 2区工程技术 Q1 ENERGY & FUELS

Sustainable Energy Technologies and Assessments

Pub Date : 2025-01-01 DOI: 10.1016/j.seta.2024.104161

Kabiru Ayobami Jimoh , Norhashila Hashim , Rosnah Shamsudin , Hasfalina Che Man , Mahirah Jahari

Drying is an energy-intensive process that prolongs grain shelf life and reduces postharvest losses from moisture-induced spoilage. Stakeholders in the grain supply chain have diverse interests regarding grain quality, energy efficiency, environmental impact, and the economic performance of the drying process. Therefore, the processing industries are highly concerned with the selection of most appropriate drying method for grain. This study experimentally evaluated various performance indices of glutinous rice under different drying methods, including hot air box drying (BD: 50 °C−70 °C), convective oven drying (COD: 50 °C−70 °C), infrared drying (IRD, at 200 W/m²−600 W/m²) and microwave drying (MWD: 1000 W/kg−3000 W/kg). The results demonstrated that MWD outperformed other methods in terms of drying kinetics, with an average production rate of ∼1.65, ∼2.02, and ∼2.37 times higher than IRD, BD, and COD, respectively. Also, MWD has the most promising economic performance with least environmental impact which was ∼28.64, ∼16.31 and ∼2.21 times lower than BD, COD and IRD, respectively. Despite the excellent drying efficiency, sustainability indices, energy and exergy efficiency exhibited by IRD and MWD compared to other methods, they are still characterized with low milling quality and macronutrients retention in the final product. Therefore, while IRD and MWD excel in drying efficiency and sustainability, they need further quality improvements before widespread industrial use.

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引用次数: 0

Corrigendum to “Application of hybrid nanofluid and a twisted turbulator in a parabolic solar trough collector: Energy and exergy models” [Sustain. Energy Technol. Assess. 49 (2022) 101708] “混合纳米流体和扭曲湍流器在抛物型太阳能槽集热器中的应用：能量和火用模型”的更正[可持续]。能源抛光工艺。评估。49 (2022)101708]

IF 7.1 2区工程技术 Q1 ENERGY & FUELS

Sustainable Energy Technologies and Assessments

Pub Date : 2024-12-01 DOI: 10.1016/j.seta.2024.104102

Yacine Khetib , Ali Alzaed , Ahmad Alahmadi , Goshtasp Cheraghian , Mohsen Sharifpur

引用次数: 0

Artificial intelligence and machine learning models application in biodiesel optimization process and fuel properties prediction 人工智能和机器学习模型在生物柴油优化工艺和燃料性能预测中的应用

IF 7.1 2区工程技术 Q1 ENERGY & FUELS

Sustainable Energy Technologies and Assessments

Pub Date : 2024-11-29 DOI: 10.1016/j.seta.2024.104097

Muhammad Arif , Adel I. Alalawy , Yuanzhang Zheng , Mostafa Koutb , Tareq Kareri , El-Sayed Salama , Xiangkai Li

Inefficient transesterification, low-quality fuel properties, and high resource consumption are the bottlenecks associated with conventional biodiesel production. The current research trends include the application of artificial intelligence (AI) and machine learning (ML) to optimize the biodiesel process for improved yield and fuel quality. Previous reviews discussed the applications of ML in the optimization of transesterification parameters and fuel properties. However, there is a lack of deep discussion on feedstock selection, optimization, process monitoring, and cost analysis. The challenges during biodiesel production, ML model selection, and assessment of plant and animal lipid potential for biodiesel under different conditions using AI tools are reviewed. All the parameters that affect biodiesel yield and fuel properties through ML, the efficiency of different models, and pilot-scale techno-economic analyses are also discussed. Biodiesel production from animal and plant lipids showed high yield potential ranging from 78-99 %. ML models demonstrated higher efficacy in transesterification optimization to attain > 90 % yield. Various AI models exhibit a predictive efficiency range (R² = 0.85 to 0.99) for yield and fuel qualities. Economic analyses reveal that the choice of feedstock and catalyst significantly impacts final production costs. ML and AI approaches exhibit the potential for improving the biodiesel process.

传统生物柴油生产的瓶颈是效率低下的酯交换反应、低质量的燃料性能和高资源消耗。目前的研究趋势包括应用人工智能（AI）和机器学习（ML）来优化生物柴油的过程，以提高产量和燃料质量。前面的综述讨论了机器学习在优化酯交换参数和燃料性能方面的应用。然而，在原料选择、优化、过程监控和成本分析方面缺乏深入的讨论。综述了生物柴油生产过程中的挑战、机器学习模型的选择以及利用人工智能工具在不同条件下评估生物柴油的动植物脂质潜力。本文还讨论了影响生物柴油产率和燃料性能的所有参数、不同模型的效率以及中试规模的技术经济分析。以动植物脂为原料生产生物柴油的产率在78- 99%之间。ML模型在酯交换优化中表现出更高的效率。90%收率。各种人工智能模型在产量和燃料质量方面表现出预测效率范围（R2 = 0.85至0.99）。经济分析表明，原料和催化剂的选择对最终生产成本有显著影响。ML和AI方法显示出改善生物柴油过程的潜力。

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引用次数: 0

Seasonal variation in photovoltaic generation efficiency due to bioaerosol particle accumulation 生物气溶胶粒子积累引起的光伏发电效率的季节变化

IF 7.1 2区工程技术 Q1 ENERGY & FUELS

Sustainable Energy Technologies and Assessments

Pub Date : 2024-11-28 DOI: 10.1016/j.seta.2024.104106

Kenji Miki , Shinnosuke Mori

Photovoltaic (PV) panels have been developed as a carbon-free, environmentally friendly method of generating energy. However, because PV panels are placed outdoors, the surrounding environment strongly affects the power generation efficiency. In this study, the soiling effect of pollen accumulation on PV panels on the power generation efficiency was calculated. For accuracy, we used the measured transmittance and the reflectance of the pollen grains and quartz panel in the calculation. In addition, airborne Cryptomeria japonica pollen grain concentrations measured at 120 sites across the country were used to estimate the effect of the accumulated pollen grains on PV panels. The seasonal changes in the PV power generation efficiency due to the accumulated C. japonica pollen alone were estimated as about 5 % at most. However, the power generation efficiency changed logarithmically with the pollen size. Therefore, the dominant pollen type is expected to have a major effect on the seasonal change in the power generation efficiency of PV panels.

光伏（PV）板已经发展成为一种无碳、环保的发电方法。然而，由于光伏板放置在室外，周围环境对发电效率的影响很大。本研究计算了光伏板上花粉堆积对发电效率的污染效应。为提高计算精度，我们采用实测的花粉粒和石英板的透射率和反射率进行计算。此外，利用在全国120个站点测量的空气传播的柳杉花粉颗粒浓度来估计积累的花粉颗粒对光伏板的影响。单独积累的粳稻花粉对光伏发电效率的季节变化估计最多为5%左右。发电效率随花粉大小呈对数变化。因此，优势花粉类型有望对光伏板发电效率的季节变化产生重大影响。

引用次数: 0

Analysis of vehicle-to-grid economy based on sustainable development grounded in game theory 基于博弈论的可持续发展的车联网经济分析

IF 7.1 2区工程技术 Q1 ENERGY & FUELS

Sustainable Energy Technologies and Assessments

Pub Date : 2024-11-27 DOI: 10.1016/j.seta.2024.104087

Jingjin Wu , Qian Sun , Chuang Li , Weihao Tang , Hui Zhang , Rongnian Tang , Conghui Han

In a vehicle-to-grid (V2G) peaking system based on coordination games, ultimate goal realized a positive total net return in V2G operations, while ensuring that the interests of all stakeholders reached a balanced equilibrium. This study examined the cost and benefit dynamics of BYD (Build Your Dreams) electric vehicles, encompassing electric vehicle users, power grid companies, and power plants, before and after participating in V2G peak load balancing services. Pre-game analysis revealed that power plants led in terms of revenue, significantly surpassing electric vehicle users, whereas grid companies incurred negative net income. An increase in peak load exacerbated the power company’s net loss, posing a significant challenge to V2G’s sustainable development. However, post-game, a cooperative alliance between the power grid company and car users was forged through financial means, with the power grid company and power plants offering invaluable data support through collaborative efforts. The disparity between optimized peak and base load generation costs narrowed to 79% of pre-optimization levels, with a 3.14% reduction in carbon emissions. Furthermore, the implementation of this collaboration strategy can result in a maximum reduction of 9% in the power grid company’s losses and an enhancement of 6.7% in the net revenue of the entire V2G peak-shaving system. Consequently, this strategy significantly promotes the development of V2G operations.

在基于协调博弈的车联网（V2G）调峰系统中，最终目标是在 V2G 运营中实现正的总净回报，同时确保所有利益相关者的利益达到平衡。本研究考察了比亚迪（Build Your Dreams）电动汽车在参与 V2G 调峰服务前后的成本和收益动态，包括电动汽车用户、电网公司和发电厂。赛前分析显示，发电厂在收入方面遥遥领先，大大超过了电动汽车用户，而电网公司的净收入则为负数。高峰负荷的增加加剧了电力公司的净亏损，对 V2G 的可持续发展构成了巨大挑战。然而，比赛结束后，电网公司和汽车用户通过经济手段结成了合作联盟，电网公司和发电厂通过共同努力提供了宝贵的数据支持。优化后的调峰和基本负荷发电成本差距缩小到优化前的 79%，碳排放量减少了 3.14%。此外，实施这一合作战略后，电网公司的损失最多可减少 9%，整个 V2G 调峰系统的净收入可增加 6.7%。因此，这一战略极大地促进了 V2G 业务的发展。

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引用次数: 0

Residential energy consumption and price forecasting in smart homes based on the internet of energy 基于能源互联网的智能家居中的住宅能源消耗和价格预测

IF 7.1 2区工程技术 Q1 ENERGY & FUELS

Sustainable Energy Technologies and Assessments

Pub Date : 2024-11-27 DOI: 10.1016/j.seta.2024.104081

Shijiao Zhao , SiZhuo Chen , Theyab R Alsenani , Badr Alotaibi , Mohammed Abuhussain

Smart home applications require automatic energy management and control of unwanted energy consumption prices using Artificial intelligence techniques. Previously, there were more studies on price forecasting. However, efficient results are still under research. This study introduces real-time residential energy management systems based on the Internet of Energy with a scheduling strategy. The proposed method employs a Gated Recurrent Unit and Bird Swarm Optimizer (GRU-BSO) along with Real-Time Electricity Scheduling (RTES) based on Price Forecasting (PF) for efficient residential energy management. The research emphasises the optimisation algorithm’s ability to minimise energy costs and promote energy conservation, significantly contributing to the field. Price forecasting (PF) is the central objective in distributed energy production. By forecasting the optimal price, this approach can improve the efficiency of power grids and solve issues with microgrid management and planning. It is suggested that the tariffs for shoulder-peak and on-peak hours be determined using the Time of Use (ToU) model. The proposed method also predicts the energy price used in home energy management. The cloud server and MATLAB-implemented microgrid system are linked via a two-level communications network. The current communications level uses the local communication level as a protocol, which uses IP/TCP and MQTT. The study’s proposed scheduling controller successfully achieved energy savings of 17 kW and 47 cents by utilising the proposed method.

智能家居应用需要使用人工智能技术进行自动能源管理和控制不必要的能源消耗价格。此前，关于价格预测的研究较多。然而，有效的结果仍在研究之中。本研究介绍了基于能源互联网的实时住宅能源管理系统与调度策略。所提出的方法采用了门控循环单元和鸟群优化器（GRU-BSO）以及基于价格预测（PF）的实时电力调度（RTES），以实现高效的住宅能源管理。该研究强调了优化算法最大限度降低能源成本和促进节能的能力，为该领域做出了重大贡献。价格预测（PF）是分布式能源生产的核心目标。通过预测最优价格，这种方法可以提高电网效率，解决微电网管理和规划问题。建议使用使用时间（ToU）模型确定肩峰和高峰时段的电价。建议的方法还能预测家庭能源管理中使用的能源价格。云服务器和 MATLAB 实现的微电网系统通过两级通信网络连接。当前的通信级别以本地通信级别为协议，使用 IP/TCP 和 MQTT。该研究提出的调度控制器利用所建议的方法成功实现了 17 千瓦和 47 美分的节能效果。

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引用次数: 0

Towards a rational framework for economic and risk assessment of energy efficiency projects 建立合理的能效项目经济和风险评估框架

IF 7.1 2区工程技术 Q1 ENERGY & FUELS

Sustainable Energy Technologies and Assessments

Pub Date : 2024-11-27 DOI: 10.1016/j.seta.2024.104090

Géremi Gilson Dranka , José Donizetti de Lima , Dalmarino Setti , Gilson Adamczuk Oliveira , Marcelo Gonçalves Trentin , Tânia Regina Sieminkoski Sirota , Paula Ferreira

Shifting towards a low-carbon and sustainable economy requires both a shift to Renewable Energy Sources (RES) and a significant increase in Energy Efficiency (EE) targets. This paper introduces a novel, user-friendly, and step-by-step framework for the techno-economic and risk-based assessment of EE Projects (FEEP). The four-stage methodology represents a step beyond traditional methods by systematically identifying intervention areas, conducting technical evaluations, and providing a comprehensive tool for economic and risk assessment. The proposed tool may empower decision-makers to select the most suitable approaches for the economic viability analysis of future projects. The framework incorporates environmental assessment, quantifying anticipated CO₂ reductions from EE measures. A real-world case study demonstrates how the new framework allows structuring the decision-making process under a reliable and straightforward approach, providing additional confidence to the investors through visual risk assessment indicators. The paper concludes with how managers and EE analysts of private and public institutions can take advantage of the proposed methodology to evaluate and benchmark a broader range of EE initiatives.

向低碳和可持续经济转型既需要转向可再生能源 (RES)，也需要大幅提高能源效率 (EE) 目标。本文介绍了一个新颖的、用户友好的、循序渐进的节能项目（FEEP）技术经济和风险评估框架。通过系统地确定干预领域、进行技术评估以及提供经济和风险评估的综合工具，该四阶段方法超越了传统方法。建议的工具可帮助决策者为未来项目的经济可行性分析选择最合适的方法。该框架结合了环境评估，量化了节能减排措施的预期二氧化碳减排量。一个实际案例研究展示了新框架如何以可靠、直接的方法构建决策过程，并通过可视化风险评估指标为投资者提供更多信心。本文最后介绍了私营和公共机构的管理者和能源效率分析师如何利用所提出的方法来评估更广泛的能源效率措施并制定基准。

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引用次数: 0

Convective heat transfer coefficient for realistic turbulence parameters using LES vs. RANS turbulence models in case of free-standing photovoltaic panel 使用 LES 与 RANS 湍流模型计算独立式光伏板上现实湍流参数的对流传热系数

IF 7.1 2区工程技术 Q1 ENERGY & FUELS

Sustainable Energy Technologies and Assessments

Pub Date : 2024-11-26 DOI: 10.1016/j.seta.2024.104108

Ivo Marinić-Kragić , Mišo Jurčević , Filip Grubišić-Čabo , Sandro Nižetić

The efficiency of photovoltaic (PV) and hybrid photovoltaic-thermal (PVT) solar panels partly depends on the heat transfer to the ambient air. The exact value of the convective heat transfer coefficient (HTC) is particularly important for the development of cooling techniques. The HTC values are usually determined from experimental data available for flat plates and similar geometries. Since the HTC depends on the geometrical details of the PV panel and the environment, the HTC values are usually estimated using computational fluid dynamics (CFD) based on the Reynolds-averaged Navier-Stokes equations (RANS). In this work, a free-standing PV panel is considered, and the main objective of the work is to compare the RANS results with the large eddy simulation (LES), which is expected to provide more reliable results compared to the available experimental data. The research includes the effects of inlet velocity, turbulence intensity and turbulence length scale. It was shown that the HTC depends on both turbulence intensity and turbulence length scale. The results show that RANS models significantly overestimate the influence of inlet turbulence on the HTC, by up to 70% at high inlet turbulence intensities. Meanwhile, the LES values are within 5 % of the experimental HTC values.

光伏（PV）和光伏-热混合（PVT）太阳能电池板的效率部分取决于向环境空气的热传递。对流传热系数（HTC）的精确值对于冷却技术的发展尤为重要。HTC 值通常是根据平板和类似几何形状的实验数据确定的。由于 HTC 取决于光伏板和环境的几何细节，因此通常使用基于雷诺平均纳维-斯托克斯方程（RANS）的计算流体动力学（CFD）来估算 HTC 值。本研究考虑的是独立式光伏板，主要目的是将 RANS 结果与大涡流模拟 (LES) 结果进行比较，预计后者与现有实验数据相比能提供更可靠的结果。研究包括入口速度、湍流强度和湍流长度尺度的影响。研究表明，HTC 取决于湍流强度和湍流长度尺度。结果表明，RANS 模型明显高估了入口湍流对 HTC 的影响，在入口湍流强度较高时，高估幅度可达 70%。同时，LES 值与实验 HTC 值的误差不超过 5%。

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引用次数: 0

Challenges and opportunities in Machine learning for bioenergy crop yield Prediction: A review 生物能源作物产量预测机器学习的挑战与机遇：综述

IF 7.1 2区工程技术 Q1 ENERGY & FUELS

Sustainable Energy Technologies and Assessments

Pub Date : 2024-11-25 DOI: 10.1016/j.seta.2024.104057

Joseph Lepnaan Dayil , Olugbenga Akande , Alaa El Din Mahmoud , Richard Kimera , Olakunle Omole

Bioenergy offers a sustainable alternative to fossil fuels, addressing energy security and climate change concerns. This paper reviews the current landscape of machine learning (ML) applications in predicting bioenergy crop yields. It explores the potential of ML models, such as random forests, support vector machines, and neural networks, to improve yield predictions by analyzing complex agricultural datasets, including soil quality, weather conditions, and crop characteristics. The review highlights the challenges of implementing ML in bioenergy systems, such as data limitations, model interpretability, and scalability. Key findings indicate that integrating ML with traditional agricultural practices can optimize resource allocation, enhance yield predictions, and promote more sustainable bioenergy production. The paper also discusses future research directions for improving ML techniques to advance bioenergy crop yield prediction and sustainability.

生物能源是化石燃料的可持续替代品，可解决能源安全和气候变化问题。本文回顾了机器学习（ML）在预测生物能源作物产量方面的应用现状。它探讨了随机森林、支持向量机和神经网络等 ML 模型的潜力，通过分析复杂的农业数据集（包括土壤质量、天气条件和作物特征）来提高产量预测。综述强调了在生物能源系统中实施 ML 所面临的挑战，如数据限制、模型可解释性和可扩展性。主要研究结果表明，将 ML 与传统农业实践相结合，可以优化资源配置，提高产量预测，促进更可持续的生物能源生产。本文还讨论了改进 ML 技术以促进生物能源作物产量预测和可持续性的未来研究方向。

引用次数: 0

Stability performance of pumped-storage units considering elastic water hammer effects in pressurized piping systems: Mechanism analysis and quantitative criterion 考虑加压管道系统中弹性水锤效应的抽水蓄能装置稳定性能：机理分析和定量标准

IF 7.1 2区工程技术 Q1 ENERGY & FUELS

Sustainable Energy Technologies and Assessments

Pub Date : 2024-11-25 DOI: 10.1016/j.seta.2024.104105

Yi Liu , Chao Hu , Sheng Chen , Weixin Qiu , Jian Zhang

The flow characteristics of water columns in pressurized piping systems significantly influence the stability of pumped-storage power stations (PSPSs). However, the complex mathematical representation of the elastic water column often leads to its simplification to a rigid column in stability analyses. This study established elastic and rigid models of a PSPS system based on elastic and rigid water columns, respectively. The stability regions of the governor parameters for these two models were determined and compared. Results indicate that the stability region of the elastic model is smaller than that of the rigid model. Consequently, using a simplified rigid model to evaluate the stability of an actual elastic system would pose potential instability risks. Furthermore, the primary cause of the stability difference between the elastic and rigid models is identified as the water hammer wave velocity. As the wave velocity increases, the stability region of the elastic model expands, eventually approaching that of the rigid model. Lastly, the coupling mechanism between the pressurized pipe and the pumped-storage unit is clarified. The modulus of the water hammer reflection coefficient is proposed to quantify the stability performance of the pumped-storage unit. These findings provide crucial insights for ensuring the stable operation of PSPSs.

加压管道系统中水柱的流动特性对抽水蓄能电站（PSPS）的稳定性有很大影响。然而，由于弹性水柱的数学表达较为复杂，在稳定性分析中往往将其简化为刚性水柱。本研究分别基于弹性水柱和刚性水柱建立了 PSPS 系统的弹性模型和刚性模型。确定并比较了这两个模型的调速器参数稳定区域。结果表明，弹性模型的稳定区域小于刚性模型。因此，使用简化的刚性模型来评估实际弹性系统的稳定性会带来潜在的不稳定性风险。此外，造成弹性模型和刚性模型稳定性差异的主要原因是水锤波速。随着波速的增加，弹性模型的稳定区域也随之扩大，最终接近刚性模型的稳定区域。最后，阐明了加压管道与抽水蓄能装置之间的耦合机制。提出了水锤反射系数模量来量化抽水蓄能装置的稳定性能。这些发现为确保 PSPS 的稳定运行提供了重要的启示。

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