Energy Science & Engineering最新文献

{"title":"Assessing Computational Complexity in Selecting Periods for LMDI Techniques in Energy-Related Carbon Dioxide Emissions: An Alternative Approach","authors":"Juan David Rivera-Niquepa,&nbsp;Jose M. Yusta,&nbsp;Paulo M. De Oliveira-De Jesus","doi":"10.1002/ese3.70187","DOIUrl":"https://doi.org/10.1002/ese3.70187","url":null,"abstract":"<p>The Logarithmic Mean Divisia Index (LMDI) decomposition analysis is widely employed to examine the drivers behind changes in carbon dioxide emissions related to energy consumption. This analysis has been applied using single-period, year-by-year, and multi-period time frames worldwide. However, these time frames often overlook trend changes in carbon emission time series, which may lead to inaccurate and biased identification of driving factors. This study replicates previous findings and proposes a novel multi-period methodology for defining time frames in decomposition analysis. The proposed approach addresses the limitations of traditional methods by accounting for trend changes in the time series and performing an exhaustive search to optimally identify the most suitable time frames for LMDI-based decomposition. The methodology comprises two stages: the first generates an exhaustive list of possible time series partitions, and the second determines the optimal partition by minimizing the total mean square error (TMSE) using sequential linear models. The results, supported by computational performance tests, demonstrate that the proposed method effectively identifies optimal time frame definitions, making it particularly suitable for annualized case studies on carbon dioxide emissions decomposition in the context of the energy transition.</p>","PeriodicalId":11673,"journal":{"name":"Energy Science & Engineering","volume":"13 7","pages":"3464-3472"},"PeriodicalIF":3.5,"publicationDate":"2025-06-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/ese3.70187","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144615523","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Optimizing of Integrated Energy Systems With CCHP-P2G on FTS Operation Strategy Using a Matrix Modeling Approach","authors":"Hui Lu,&nbsp;Hongzhi Lu,&nbsp;Zhuojia Xu,&nbsp;Wendong Huang,&nbsp;Heng Wu,&nbsp;Huiwen Zhang,&nbsp;Aoli Wang,&nbsp;Yufang Chang","doi":"10.1002/ese3.70049","DOIUrl":"https://doi.org/10.1002/ese3.70049","url":null,"abstract":"<p>With carbon peaking and carbon neutrality goals, the integrated energy system (IES) is an effective way to achieve energy transition. To improve energy efficiency and reduce carbon dioxide emissions of the IES, a model of IES with CCHP-P2G and the FTS operation strategy is proposed. Firstly, a matrix modeling method is adopted in this model. This effectively improves the accuracy of system modeling. Meanwhile, a correction matrix is used to describe uncertain factors such as energy storage and renewable energy. Besides, this paper proposes the FTS operation strategy to avoid heating waste problems in traditional operation strategy, such as FEL and FTL. In the end, a method akin to a per-unit value is applied to structure evaluation criteria. The superiority of the proposed method is verified by the simulation results. The results demonstrate that the proposed model using CCHP-P2G and FTS operation strategy can improve the utilization of renewable energy, and reduce carbon emissions and thus achieve reductions in total operation costs and carbon emissions.</p>","PeriodicalId":11673,"journal":{"name":"Energy Science & Engineering","volume":"13 7","pages":"3491-3502"},"PeriodicalIF":3.5,"publicationDate":"2025-06-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/ese3.70049","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144614976","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Front Cover Image","authors":"Goran Shirzad,&nbsp;Mehdi Assareh","doi":"10.1002/ese3.70181","DOIUrl":"https://doi.org/10.1002/ese3.70181","url":null,"abstract":"<p>COVER CAPTION:</p><p>The cover image is based on the article <i>Dual Porosity Simulation of Gravity Drainage Mechanism Induced by Geological Acid Gas Storage in Naturally Fractured Reservoirs</i> by Mehdi Assareh et al., https://doi.org/10.1002/ese3.70094.\u0000\u0000 <figure>\u0000 <div><picture>\u0000 <source></source></picture><p></p>\u0000 </div>\u0000 </figure></p>","PeriodicalId":11673,"journal":{"name":"Energy Science & Engineering","volume":"13 6","pages":""},"PeriodicalIF":3.5,"publicationDate":"2025-06-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/ese3.70181","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144244384","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Advanced Ignition and Combustion Analysis of Second-Generation Biodiesels in Turbocharged Diesel Engines","authors":"Balamurugan Mani,&nbsp;Ratchagaraja Dhairiyasamy,&nbsp;Deepika Gabiriel,&nbsp;C. Ahamed Saleel,&nbsp;Nasim Hasan,&nbsp;Fayaz Hussain","doi":"10.1002/ese3.70012","DOIUrl":"https://doi.org/10.1002/ese3.70012","url":null,"abstract":"<p>This study investigates the energy release characteristics of second-generation biodiesel blends derived from beef tallow and castor bean in a turbocharged compression ignition engine. The primary objective was to evaluate ignition delay, combustion phasing, and energy release rates at various engine loads using blends of B10 and B20 biodiesel concentrations. A comprehensive experimental setup, including a diesel engine and a detailed thermodynamic model, was employed for this analysis. Dynamometric testing was conducted to assess the performance of the biodiesel blends compared to mineral diesel and soybean biodiesel. Key parameters such as cetane number, viscosity, and fatty acid composition of the biodiesels were correlated with their combustion behavior. Energy release characteristics were measured under low (250 kPa), medium (500 kPa), and high (750 kPa) load conditions. The study revealed that beef tallow biodiesel advanced ignition timing, reducing premixed combustion phases across all loads. At low load, castor bean biodiesel showed significant ignition delays (around 3° crank angle longer than diesel), leading to higher peak energy release rates, notably at high loads where it surpassed mineral diesel. The B20 blend of castor bean biodiesel emitted 320 mg/kg of unburned hydrocarbons at low load, compared to 21 mg/kg for diesel, indicating challenges in achieving complete combustion. Beef tallow biodiesel exhibited favorable ignition characteristics, while castor bean biodiesel faced issues with delayed ignition and higher energy release rates due to its high viscosity and low cetane number. Optimizing the molecular composition of castor bean biodiesel and exploring advanced fuel injection strategies could enhance its combustion efficiency. Further research is recommended to investigate the long-term effects on engine wear and emissions, ensuring these biodiesels' viability as sustainable alternatives to conventional fuels.</p>","PeriodicalId":11673,"journal":{"name":"Energy Science & Engineering","volume":"13 6","pages":"2620-2630"},"PeriodicalIF":3.5,"publicationDate":"2025-05-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/ese3.70012","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144245038","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Workflow Design and Operational Analysis of a Coal-Based Multi-Energy Combined Supply System for Electricity, Heating, Cooling, and Gas","authors":"Shiwei Yu,&nbsp;Dedong Li,&nbsp;Zhongyi Zuo,&nbsp;Mingjie Feng","doi":"10.1002/ese3.70137","DOIUrl":"https://doi.org/10.1002/ese3.70137","url":null,"abstract":"<p>The combined cooling, heating, and power (CCHP) system, as a typical representative of novel distributed energy systems, demonstrates significant advantages in the cascade utilization of energy and the control of transmission and distribution losses. However, the inherent reliance of traditional CCHP systems on natural gas as fuel structurally conflicts with China's energy endowment, characterized by abundant coal and scarce natural gas, severely limiting their large-scale application. To adapt to this energy consumption profile and fully leverage the strengths of CCHP systems, this study establishes a coal-fueled electricity-gas-heating-cooling polygeneration system based on physical and mathematical models within the Aspen Plus 9.0 commercial simulation platform. The reliability of the proposed model is validated through comparisons with data from relevant literature. To identify the optimal operating parameters, the effects of coal-water slurry concentration and oxygen-to-coal ratio on key gasification indicators (e.g., gasifier temperature, syngas composition, syngas calorific value, and cold gas efficiency) and system output loads (e.g., electricity, heating, cooling, and municipal gas) are systematically investigated. Finally, a comprehensive simulation of the entire system is conducted, with energy and exergy analyses performed on major functional units. The results indicate that coal-water slurry concentration and oxygen-to-coal ratio significantly influence gasifier temperature, syngas composition, calorific value, and cold gas efficiency. The system achieves optimal performance at an oxygen-to-coal ratio of 1.05 and a coal-water slurry concentration of 65%. Under design conditions, the system attains a comprehensive energy efficiency of 66.18% and an exergy efficiency of 34.43%. This study provides an innovative solution to address technological bottlenecks in China's energy transition, not only enhancing the efficiency of clean coal utilization but also offering a new technical pathway for coal-fired power transformation under the “dual carbon” goals (carbon peaking and carbon neutrality).</p>","PeriodicalId":11673,"journal":{"name":"Energy Science & Engineering","volume":"13 7","pages":"3791-3805"},"PeriodicalIF":3.5,"publicationDate":"2025-05-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/ese3.70137","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144615470","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A Comparative Life Cycle Assessment of Residential Heating Systems in Tehran, Iran","authors":"Hossein Vahidi,&nbsp;Mohsen Esfahanizadeh","doi":"10.1002/ese3.70129","DOIUrl":"https://doi.org/10.1002/ese3.70129","url":null,"abstract":"<p>Environmental pollution from different gas heating systems in residential buildings has significant impacts, especially in urban areas due to their high density. This study conducts a comparative life cycle assessment of two commonly used residential heating systems in Tehran: the Central Boiler Room (CBR) and the wall-hung boiler (WHB). Using OpenLCA (version 1.10) software and the Ecoinvent 3.7 database, the environmental impacts of natural gas consumption for both systems were evaluated across key categories, including global warming potential (GWP100), human toxicity potential, acidification potential, and terrestrial ecotoxicity potential. The analysis revealed that the environmental impacts of the CBR were consistently higher than those of the WHB, with average differences of 12% for all impact categories. The disparity is attributed to the greater natural gas consumption, lower combustion efficiency, and higher maintenance requirements of the CBR. The study also highlights the significant contribution of pollutant emissions such as NOx, lead, and mercury to human health risks, particularly in Tehran's urban context, where air quality is a critical concern. While the focus of the research was on the operational phase of the systems, construction and installation factors, such as energy use for pumping and piping, were also considered for the CBR. Given Tehran's climatic and geographic constraints, renewable technologies such as solar or geothermal energy were not included, as they are neither conventional nor widely feasible. The findings suggest that the WHB is a more sustainable heating option for Tehran, offering reduced environmental impacts and operational advantages. This study provides valuable insights for policymakers and stakeholders aiming to optimize residential heating solutions in urban areas.</p>","PeriodicalId":11673,"journal":{"name":"Energy Science & Engineering","volume":"13 7","pages":"3515-3524"},"PeriodicalIF":3.5,"publicationDate":"2025-05-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/ese3.70129","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144614985","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Identification of Low-Value Defects in Infrared Images of Porcelain Insulators Based on STCE-YOLO Algorithm","authors":"Shaotong Pei,&nbsp;Weiqi Wang,&nbsp;Chenlong Hu,&nbsp;Keyu Li,&nbsp;Haichao Sun,&nbsp;Mianxiao Wu,&nbsp;Bo Lan","doi":"10.1002/ese3.70136","DOIUrl":"https://doi.org/10.1002/ese3.70136","url":null,"abstract":"<p>Insulators, as a key component of the power system, their low-value defect detection is of great significance to ensure the safe and stable operation of the power system. However, traditional detection methods have many shortcomings in the face of a complex environment and small target recognition. To solve the above problems, this paper optimizes the small target and complex environment problems in the low-value defect recognition of insulator infrared images, and proposes the STCE-YOLO algorithm: based on YOLOv8, the deformable large kernel attention is used to improve the detection ability of small targets; then the cross-modal contextual feature module is applied to Integrate the features of different scales to reduce the computation of the model. And the multiple attention mechanism improved to the third generation of variability convolution is used to detect the head to improve the accuracy of the algorithm's target localization. Finally, the SIoU loss function is employed to further enhance performance in complex scenes containing small targets. Experimental validation has shown that the STCE-YOLO algorithm proposed in this paper achieves an average improvement of 7.64% in mAP compared to the original YOLOv8, with GFLOPs reduced from 8.1 to 7.7. This meets the requirements for identifying low-value defects in small target insulators. Furthermore, ablation and comparative experiments have demonstrated the effectiveness and superiority of the proposed algorithm.</p>","PeriodicalId":11673,"journal":{"name":"Energy Science & Engineering","volume":"13 7","pages":"3779-3790"},"PeriodicalIF":3.5,"publicationDate":"2025-05-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/ese3.70136","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144614986","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Wastewater Treatment for Energy Conservation and Zero Carbon Footprint: A Review","authors":"Ravikumar Jayabal,&nbsp;Rajkumar Sivanraju","doi":"10.1002/ese3.70142","DOIUrl":"https://doi.org/10.1002/ese3.70142","url":null,"abstract":"<p>This article explores innovative wastewater treatment (WWT) methods that promote energy conservation and a zero-carbon footprint. It emphasizes the transition to sustainable WWT practices by focusing on resource recovery, energy efficiency, and reducing greenhouse gas emissions. The study employs a comprehensive literature review to assess various technologies based on their effectiveness in pollutant removal while conserving energy. It includes only methods that have been successfully implemented or show strong potential for practical use. The research integrates industry reports, case studies, and peer-reviewed articles to evaluate accessible technologies and policy frameworks supporting sustainable WWT adoption. Innovative solutions are identified to address the challenges of traditional methods, such as high energy consumption and inadequate pollutant removal. The study also highlights the importance of nutrient removal to prevent eutrophication. In conclusion, the article advocates adopting cutting-edge WWT technologies that enhance energy efficiency and contribute to carbon neutrality. It underscores the necessity of ongoing innovation in wastewater management to address environmental challenges. By transforming WWT into a more sustainable and efficient process, these advancements benefit both the environment and public health, reinforcing the importance of integrating advanced technologies and supportive policies in achieving sustainable water treatment.</p>","PeriodicalId":11673,"journal":{"name":"Energy Science & Engineering","volume":"13 7","pages":"3806-3820"},"PeriodicalIF":3.5,"publicationDate":"2025-05-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/ese3.70142","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144615494","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Physical Property Prediction and Simulation Analysis of Hydrogen-Doped Natural Gas Pipeline","authors":"Lianghui Guo,&nbsp;He Zhang,&nbsp;Ran Liu,&nbsp;Keke Zhi,&nbsp;Xinzhe Li","doi":"10.1002/ese3.70135","DOIUrl":"https://doi.org/10.1002/ese3.70135","url":null,"abstract":"<p>Hydrogen-doped natural gas, a blend of hydrogen and natural gas, has emerged as a promising candidate due to its potential to reduce greenhouse gas emissions and enhance energy efficiency. However, the physical properties and operational dynamics of hydrogen-doped natural gas restrict the efficient operation of natural gas pipelines. Physical properties and operational dynamics of hydrogen-doped natural gas pipelines are investigated to combine machine learning techniques and simulation models, which promote the development of zero carbon emission energy, hydrogen energy, thereby contributing to the reduction of global carbon emissions. The REFPROP software is utilized to construct databases for predicting the physical properties of hydrogen-doped natural gas. Among various machine learning models, the Wide Neural Network emerges as optimal, exhibiting an exceptional R² value exceeding 0.9999 and the ability to predict over 264,000 data points per second for density and viscosity. Additionally, a simulation model is developed and rigorously validated against COMSOL 5.0 commercial software, demonstrating its capability to accurately simulate pipeline operations. Matching the calorific value of hydrogen-doped natural gas is very important to ensure downstream energy supply and production operations' efficiency. Thus, various operation cases such as constant pressure and constant calorific value were studied. Overall, this study provides valuable insights into optimizing hydrogen-doped natural gas pipeline operations and advancing green energy initiatives.</p>","PeriodicalId":11673,"journal":{"name":"Energy Science & Engineering","volume":"13 7","pages":"3765-3778"},"PeriodicalIF":3.5,"publicationDate":"2025-05-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/ese3.70135","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144615427","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Assessing the Impact of Artificial Intelligence and Green Finance on Energy Efficiency: Based on Super-Efficiency SBM and Tobit Two-Stage Models","authors":"Hongji Zhou,&nbsp;Rong Wang","doi":"10.1002/ese3.70132","DOIUrl":"https://doi.org/10.1002/ese3.70132","url":null,"abstract":"<p>To enhance energy efficiency (EE) and achieve sustainable development. This study measures EE through super-efficiency SBM model, and verifies artificial intelligence (AI) and green finance (GF) impact on EE by Tobit model, conclusions as follows: (1) The EE of each region and the country is the spread of the low, with a lot of opportunity for improvement. The EE decreases in the following order: the regions in eastern, central, and western. (2) At the national level, AI has a significant positive effect on EE, implying that advances in AI can effectively improve EE. From different regions, AI impact on EE in both the eastern and central regions shows positive effect, and the effect in the central is larger than that eastern, while in the western region is positive but statistically insignificant. (3) At the national level, GF promotes EE but the elasticity coefficient is small; in the eastern region, GF has the biggest effect on EE, while in the central and western regions, it has weaker effects on EE. (4) Energy endowment inhibits EE; environmental regulation can promote EE at the national and regional levels, with the biggest effect in the eastern region and the least effect in the western region. The industrial structure coefficient in all regions reduces the EE. The technology level inhibits EE only in the central region. The thesis through the analysis of the relationship between the three and the reliability of the conclusions drawn from the analysis, to be able to better play the GF and AI in the energy sector of the policy implementation effect, effectively improve EE, improve the energy structure, for the comprehensive promotion of the energy transition is of great significance.</p>","PeriodicalId":11673,"journal":{"name":"Energy Science & Engineering","volume":"13 7","pages":"3727-3740"},"PeriodicalIF":3.5,"publicationDate":"2025-05-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/ese3.70132","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144615275","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}