Energy Reports最新文献

Methane and carbon dioxide post-combustion capturing: A step towards low carbon aviation fuel

IF 4.7 3区工程技术 Q2 ENERGY & FUELS

Energy Reports

Pub Date : 2025-02-05 DOI: 10.1016/j.egyr.2025.01.065

Abdulkarem I. Amhamed , Zeineb Thiehmed , Rim Ismail , Mohamed Nasery , Aya Talal , Raeesh Muhammad , Rachid Zaffou , Odi Fawwaz Alrebei , Tareq Al-Ansari

This study addresses the critical challenge of reducing greenhouse gas emissions in the aviation sector by focusing on post-combustion methane (CH₄) and carbon dioxide (CO₂) capture as a step toward the development of Low Carbon Aviation Fuels (LCAF). A novel combustion process was developed and evaluated, utilizing an innovative approach that integrates methane (CH₄) recycling, carbon dioxide (CO₂) capture, and electrolysis-generated hydrogen (H₂) and oxygen (O₂). The methodology involved benchmarking the performance of the proposed process against conventional combustion processes. Experiments were conducted using two types of fuels—Type A and Type B—selected for their distinct carbon-to-hydrogen ratios to represent a spectrum of aviation fuel properties. Key performance metrics, including heat release, emissions, and methane (CH₄) and oxygen (O₂) production, were analyzed across multiple integration scenarios. The findings demonstrate that the proposed system significantly reduces nitrogen oxide (NOx) emissions, enhances methane (CH₄) recycling efficiency, and optimizes resource utilization compared to conventional methods. The integration of carbon dioxide (CO₂) methanation and oxygen (O₂) recycling not only minimizes environmental impact but also aligns with global decarbonization goals for aviation. These results highlight the potential of the proposed process to contribute to the sustainable transition of the aviation industry, offering an effective pathway to achieve energy security and climate targets. The proposed system achieves a methane (CH4) production of 1.71 kmol/hr, a 15 % reduction in NOx emissions, and a 4.4 % lower energy intensity compared to conventional processes.

{"title":"Methane and carbon dioxide post-combustion capturing: A step towards low carbon aviation fuel","authors":"Abdulkarem I. Amhamed , Zeineb Thiehmed , Rim Ismail , Mohamed Nasery , Aya Talal , Raeesh Muhammad , Rachid Zaffou , Odi Fawwaz Alrebei , Tareq Al-Ansari","doi":"10.1016/j.egyr.2025.01.065","DOIUrl":"10.1016/j.egyr.2025.01.065","url":null,"abstract":"<div><div>This study addresses the critical challenge of reducing greenhouse gas emissions in the aviation sector by focusing on post-combustion methane (CH₄) and carbon dioxide (CO₂) capture as a step toward the development of Low Carbon Aviation Fuels (LCAF). A novel combustion process was developed and evaluated, utilizing an innovative approach that integrates methane (CH₄) recycling, carbon dioxide (CO₂) capture, and electrolysis-generated hydrogen (H₂) and oxygen (O₂). The methodology involved benchmarking the performance of the proposed process against conventional combustion processes. Experiments were conducted using two types of fuels—Type A and Type B—selected for their distinct carbon-to-hydrogen ratios to represent a spectrum of aviation fuel properties. Key performance metrics, including heat release, emissions, and methane (CH₄) and oxygen (O₂) production, were analyzed across multiple integration scenarios. The findings demonstrate that the proposed system significantly reduces nitrogen oxide (NOx) emissions, enhances methane (CH₄) recycling efficiency, and optimizes resource utilization compared to conventional methods. The integration of carbon dioxide (CO₂) methanation and oxygen (O₂) recycling not only minimizes environmental impact but also aligns with global decarbonization goals for aviation. These results highlight the potential of the proposed process to contribute to the sustainable transition of the aviation industry, offering an effective pathway to achieve energy security and climate targets. The proposed system achieves a methane (CH4) production of 1.71 kmol/hr, a 15 % reduction in NOx emissions, and a 4.4 % lower energy intensity compared to conventional processes.</div></div>","PeriodicalId":11798,"journal":{"name":"Energy Reports","volume":"13 ","pages":"Pages 2230-2244"},"PeriodicalIF":4.7,"publicationDate":"2025-02-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143154850","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}

引用次数: 0

State of charge estimation for lithium-ion batteries based on a digital twin hybrid model

IF 4.7 3区工程技术 Q2 ENERGY & FUELS

Energy Reports

Pub Date : 2025-02-03 DOI: 10.1016/j.egyr.2025.01.046

Chunhui Ji , Guang Jin , Ran Zhang

The estimation of the state of lithium-ion batteries is a critical aspect of battery management systems. However, the accuracy of such estimates deteriorates over time due to complex chemical reactions occurring within the battery as a result of repeated charging and discharging. To address this issue, this paper introduces a digital twin hybrid model (DTHM), integrating both an equivalent circuit model (ECM) and a neural network model (NNM). The method employs a residual technique to merge and enhance these models throughout battery operations, utilizing periodic operational outcomes to formulate calibration rules and dynamically calibrate parameters. Specifically, the augmented adaptive unscented Kalman filter method is applied within the ECM to reflect the dynamic behaviors and internal state of the battery. For the NNM, an importance sampling mechanism augments the training effect of neural network. Moreover, a dynamic calibration strategy, informed by digital twin technology, mitigates parameter uncertainties due to the internal evolution of the battery. Experiments conducted under diverse working and temperature conditions reveal that the DTHM achieves a synchronization error of less than 0.2% when aligning the physical and digital models, which attests to its high fidelity. Furthermore, at the early cycle, the DTHM demonstrated a maximum mean absolute error and a maximum root-mean-square error in estimating battery SOC of 0.0046 and 0.0058, respectively. Towards the end cycle, these errors were 0.0057 and 0.0065, respectively. Compared to statistical results from other state-of-the-art models, the DTHM consistently exhibits superior stability and robustness, particularly in estimating the state of batteries at various aging stages.

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引用次数: 0

Evaluation of the short and medium-term forecast quality of global solar irradiance from GFS-MOS and WRF-Solar models for the northeast region of Brazil

IF 4.7 3区工程技术 Q2 ENERGY & FUELS

Energy Reports

Pub Date : 2025-02-03 DOI: 10.1016/j.egyr.2025.01.073

Francisco José Lopes de Lima , Thalyta Soares dos Santos , Diogo Nunes da Silva Ramos , Arthur Lúcide Cotta Weyll , William Duarte Jacondino , Allan Rodrigues Silva , Luana Kruger Melgaço Pereira , Ana Paula Paes dos Santos , José Bione Melo Filho , Márcio de Carvalho Filho , Alex Álisson Bandeira Santos , Davidson Martins Moreira

The prediction of global horizontal irradiance (GHI) is crucial due to the rapid growth of photovoltaic energy, a sustainable and increasingly important source in the global energy landscape. The Northeast region of Brazil has exceptional potential for solar energy generation, thanks to its high levels of solar radiation throughout the year. This underscores the need for accurate irradiance forecasts to optimize the use and efficiency of photovoltaic systems in the region. This study aims to predict GHI over short- and medium-term horizons using the Global Forecast System (GFS), the Weather Research and Forecasting-Solar (WRF-Solar) model, and a hybrid method called GFS-MOS for the Northeast of Brazil (NEB). The GFS-MOS combines GFS forecasts with the Model Output Statistics (MOS) algorithm, which uses observational data for statistical refinement. The results demonstrate that GFS-MOS outperforms WRF-Solar in most aspects, particularly in simulating low GHI values, where GFS-MOS demonstrated superior accuracy. GHI forecasts were validated against data from 137 meteorological stations of the National Institute of Meteorology (INMET) for the period from 2020 to 2022. Additionally, the GFS-MOS method further improved the accuracy of GHI predictions. The performance of the GFS, the GFS-MOS, and the WRF-Solar was compared, with the GFS-MOS demonstrating the best overall performance. It is concluded that the application of statistical refinement techniques, such as GFS-MOS, can significantly improve solar irradiance forecasting.

{"title":"Evaluation of the short and medium-term forecast quality of global solar irradiance from GFS-MOS and WRF-Solar models for the northeast region of Brazil","authors":"Francisco José Lopes de Lima , Thalyta Soares dos Santos , Diogo Nunes da Silva Ramos , Arthur Lúcide Cotta Weyll , William Duarte Jacondino , Allan Rodrigues Silva , Luana Kruger Melgaço Pereira , Ana Paula Paes dos Santos , José Bione Melo Filho , Márcio de Carvalho Filho , Alex Álisson Bandeira Santos , Davidson Martins Moreira","doi":"10.1016/j.egyr.2025.01.073","DOIUrl":"10.1016/j.egyr.2025.01.073","url":null,"abstract":"<div><div>The prediction of global horizontal irradiance (GHI) is crucial due to the rapid growth of photovoltaic energy, a sustainable and increasingly important source in the global energy landscape. The Northeast region of Brazil has exceptional potential for solar energy generation, thanks to its high levels of solar radiation throughout the year. This underscores the need for accurate irradiance forecasts to optimize the use and efficiency of photovoltaic systems in the region. This study aims to predict GHI over short- and medium-term horizons using the Global Forecast System (GFS), the Weather Research and Forecasting-Solar (WRF-Solar) model, and a hybrid method called GFS-MOS for the Northeast of Brazil (NEB). The GFS-MOS combines GFS forecasts with the Model Output Statistics (MOS) algorithm, which uses observational data for statistical refinement. The results demonstrate that GFS-MOS outperforms WRF-Solar in most aspects, particularly in simulating low GHI values, where GFS-MOS demonstrated superior accuracy. GHI forecasts were validated against data from 137 meteorological stations of the National Institute of Meteorology (INMET) for the period from 2020 to 2022. Additionally, the GFS-MOS method further improved the accuracy of GHI predictions. The performance of the GFS, the GFS-MOS, and the WRF-Solar was compared, with the GFS-MOS demonstrating the best overall performance. It is concluded that the application of statistical refinement techniques, such as GFS-MOS, can significantly improve solar irradiance forecasting.</div></div>","PeriodicalId":11798,"journal":{"name":"Energy Reports","volume":"13 ","pages":"Pages 2187-2203"},"PeriodicalIF":4.7,"publicationDate":"2025-02-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143154813","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}

引用次数: 0

Spray cooling for enhancing cooling performance and reducing power consumption of radiator in hydrogen fuel cell system

IF 4.7 3区工程技术 Q2 ENERGY & FUELS

Energy Reports

Pub Date : 2025-02-03 DOI: 10.1016/j.egyr.2025.01.068

Bo Shi , Qiguang Xie , Feng Zhou , Jiawang Zhou , Wenju Ma , Lihui Feng , Jinxiao Zhao , Baifeng Ji , Kejun Wei , Jincheng Wang , Zufei Guo , Yiyuan Huang , Qizhong Li

During the development of hydrogen fuel cell systems, with the augmentation of power, conventional air-cooling systems, which are frequently employed in portable scenarios, encounter difficulties in maintaining the balance between radiator heat dissipation and power consumption. In contrast, liquid-cooling systems are widely adopted in high-power applications. In this regard, aiming to address the heat dissipation problem and make use of the wastewater from the stack tailpipe, a novel spray cooling system integrated with the traditional air-cooling for the radiator of hydrogen fuel cell systems is put forward. Through experimental investigations based on heat transfer theory and the design principles of fuel cell systems, it is discovered that under specific nozzle apertures and spray water pressures, the heat dissipation rate can be enhanced by 40 % and 30 % respectively. With particular radiator internal water flow rates and fan speeds, the heat dissipation rate can be increased by 30 % and 108 % respectively. And the spray angle of 60 ° is the best angle. In contrast to the conventional air-cooling system, the spray-air cooling system exhibits a heat dissipation rate that is approximately 50 % higher. Experimental analyses demonstrate that the new system effectively harnesses water resources and enhances the heat dissipation performance of the radiator, thereby providing a technical reference for the application of spray cooling in the radiators of hydrogen fuel cell systems.

{"title":"Spray cooling for enhancing cooling performance and reducing power consumption of radiator in hydrogen fuel cell system","authors":"Bo Shi , Qiguang Xie , Feng Zhou , Jiawang Zhou , Wenju Ma , Lihui Feng , Jinxiao Zhao , Baifeng Ji , Kejun Wei , Jincheng Wang , Zufei Guo , Yiyuan Huang , Qizhong Li","doi":"10.1016/j.egyr.2025.01.068","DOIUrl":"10.1016/j.egyr.2025.01.068","url":null,"abstract":"<div><div>During the development of hydrogen fuel cell systems, with the augmentation of power, conventional air-cooling systems, which are frequently employed in portable scenarios, encounter difficulties in maintaining the balance between radiator heat dissipation and power consumption. In contrast, liquid-cooling systems are widely adopted in high-power applications. In this regard, aiming to address the heat dissipation problem and make use of the wastewater from the stack tailpipe, a novel spray cooling system integrated with the traditional air-cooling for the radiator of hydrogen fuel cell systems is put forward. Through experimental investigations based on heat transfer theory and the design principles of fuel cell systems, it is discovered that under specific nozzle apertures and spray water pressures, the heat dissipation rate can be enhanced by 40 % and 30 % respectively. With particular radiator internal water flow rates and fan speeds, the heat dissipation rate can be increased by 30 % and 108 % respectively. And the spray angle of 60 ° is the best angle. In contrast to the conventional air-cooling system, the spray-air cooling system exhibits a heat dissipation rate that is approximately 50 % higher. Experimental analyses demonstrate that the new system effectively harnesses water resources and enhances the heat dissipation performance of the radiator, thereby providing a technical reference for the application of spray cooling in the radiators of hydrogen fuel cell systems.</div></div>","PeriodicalId":11798,"journal":{"name":"Energy Reports","volume":"13 ","pages":"Pages 2204-2218"},"PeriodicalIF":4.7,"publicationDate":"2025-02-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143154897","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}

引用次数: 0

Feedback action and genetic algorithm-based proportional-integral controller to improve the performance of the direct power control of a variable-speed contra-rotating wind turbine generation system

IF 4.7 3区工程技术 Q2 ENERGY & FUELS

Energy Reports

Pub Date : 2025-02-01 DOI: 10.1016/j.egyr.2025.01.064

Habib Benbouhenni , Ilhami Colak , Mourad Yessef , Z.M.S. Elbarbary , Nicu Bizon

An enhanced control scheme of a double-powered asynchronous generator (DPAG) integrated into a variable-speed contra-rotating wind turbine (VSCRWT) generation system is displayed in this paper. The original idea treated here is to develop a robust direct power control (DPC) using a new kind of proportional-integral (PI) regulator based on feedback command theory and genetic algorithm (GA) for the DPAG-VSCRWT system. The suggested feedback PI (FPI) controller based on the GA technique is designed to improve the performance and robustness of the DPC of the DPAG-VSCRWT system, especially the problem of low robustness. The DPC-FPI-GA strategy was applied to the machine inverter only, where the pulse width modulation (PWM) strategy was used to convert the reference voltage values generated by the FPI-GA controllers. Therefore, this strategy differs from the traditional DPC strategy in terms of principle, performance, durability, and effectiveness in improving the quality of current and energy. The DPC-FPI-GA approach with the PWM technique is applied to the VSCRWT system using a 1500 kW DPAG during various tests in MATLAB software. The characteristics of the presented DPC-FPI-GA approach with the PWM technique are verified by numerical simulations. The performances of the DPC-FPI-GA approach with the PWM technique are verified using performance indicators (such as the ripple ratio for torque, power, and current, as well as the harmonic distortion value of the current) and detailed discussions are given at the end of the paper. It was found that the proposed DPC-FPI-GA with PWM technique contributed significantly to the improvement of power quality produced by the DPAG-VSCRWT system even in the presence of internal and/or external disturbances. In addition, the designed DPC approach based on the PWM and FPI-GA techniques provides minimum harmonic distortion of current, reduces the ripples of the torque and energy, and enhances the time response of the DPAG-VSCRWT system.

{"title":"Feedback action and genetic algorithm-based proportional-integral controller to improve the performance of the direct power control of a variable-speed contra-rotating wind turbine generation system","authors":"Habib Benbouhenni , Ilhami Colak , Mourad Yessef , Z.M.S. Elbarbary , Nicu Bizon","doi":"10.1016/j.egyr.2025.01.064","DOIUrl":"10.1016/j.egyr.2025.01.064","url":null,"abstract":"<div><div>An enhanced control scheme of a double-powered asynchronous generator (DPAG) integrated into a variable-speed contra-rotating wind turbine (VSCRWT) generation system is displayed in this paper. The original idea treated here is to develop a robust direct power control (DPC) using a new kind of proportional-integral (PI) regulator based on feedback command theory and genetic algorithm (GA) for the DPAG-VSCRWT system. The suggested feedback PI (FPI) controller based on the GA technique is designed to improve the performance and robustness of the DPC of the DPAG-VSCRWT system, especially the problem of low robustness. The DPC-FPI-GA strategy was applied to the machine inverter only, where the pulse width modulation (PWM) strategy was used to convert the reference voltage values generated by the FPI-GA controllers. Therefore, this strategy differs from the traditional DPC strategy in terms of principle, performance, durability, and effectiveness in improving the quality of current and energy. The DPC-FPI-GA approach with the PWM technique is applied to the VSCRWT system using a 1500 kW DPAG during various tests in MATLAB software. The characteristics of the presented DPC-FPI-GA approach with the PWM technique are verified by numerical simulations. The performances of the DPC-FPI-GA approach with the PWM technique are verified using performance indicators (such as the ripple ratio for torque, power, and current, as well as the harmonic distortion value of the current) and detailed discussions are given at the end of the paper. It was found that the proposed DPC-FPI-GA with PWM technique contributed significantly to the improvement of power quality produced by the DPAG-VSCRWT system even in the presence of internal and/or external disturbances. In addition, the designed DPC approach based on the PWM and FPI-GA techniques provides minimum harmonic distortion of current, reduces the ripples of the torque and energy, and enhances the time response of the DPAG-VSCRWT system.</div></div>","PeriodicalId":11798,"journal":{"name":"Energy Reports","volume":"13 ","pages":"Pages 2153-2173"},"PeriodicalIF":4.7,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143154900","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}

引用次数: 0

Global information enhanced adaptive bald eagle search algorithm for photovoltaic system optimization

IF 4.7 3区工程技术 Q2 ENERGY & FUELS

Energy Reports

Pub Date : 2025-01-31 DOI: 10.1016/j.egyr.2025.01.040

Wenyan Guo, Zhuolin Hou, Fang Dai, Junfeng Wang, Shenglong Li

The parameter estimation of solar photovoltaic system (SPVS) models presents a formidable optimization challenge. The crux of resolving this issue lies in the efficacy of intelligent algorithms. By addressing the parameter optimization challenges associated with three photovoltaic models and targeting the deficiencies of the bald eagle search optimization algorithm (BES), such as its limited local search capability, inadequate diversity, and suboptimal solution performance, this article introduces a novel approach: the virtual-particle adaptive bald eagle search optimization algorithm (VABES). Incorporated into VABES is a virtual particle updating mechanism, leveraging comprehensive population information to enhance the prospects of individuals converging towards the most desired solution, while simultaneously preventing the population from becoming trapped at extreme points. To strike a balance between aggregation and dispersion within the swarm and bolster VABES's global optimization prowess, an adaptive probability-guided Levy flight correction scheme has been devised. Additionally, a dynamic mutation factor-based mutation and crossover strategy has been formulated to refine VABES's exploitation capabilities. The results of 100-dimensional tests conducted on 40 benchmark functions from CEC2017 and CEC2020, coupled with nonparametric testing, reveal that VABES outperforms at least 66 % of other competitive improved algorithms. Experiments involving 57 real-world problems demonstrate that VABES's total performance metric stands at 0.1466, ranking it first and showcasing its notable advantages in handling constrained optimization compared to BES-related improved algorithms. Furthermore, the solution processes for three photovoltaic parameter optimization models illustrate that VABES converges rapidly, reducing errors by 26 %, and exhibits certain advantages in estimating diverse photovoltaic model parameters.

{"title":"Global information enhanced adaptive bald eagle search algorithm for photovoltaic system optimization","authors":"Wenyan Guo, Zhuolin Hou, Fang Dai, Junfeng Wang, Shenglong Li","doi":"10.1016/j.egyr.2025.01.040","DOIUrl":"10.1016/j.egyr.2025.01.040","url":null,"abstract":"<div><div>The parameter estimation of solar photovoltaic system (SPVS) models presents a formidable optimization challenge. The crux of resolving this issue lies in the efficacy of intelligent algorithms. By addressing the parameter optimization challenges associated with three photovoltaic models and targeting the deficiencies of the bald eagle search optimization algorithm (BES), such as its limited local search capability, inadequate diversity, and suboptimal solution performance, this article introduces a novel approach: the virtual-particle adaptive bald eagle search optimization algorithm (VABES). Incorporated into VABES is a virtual particle updating mechanism, leveraging comprehensive population information to enhance the prospects of individuals converging towards the most desired solution, while simultaneously preventing the population from becoming trapped at extreme points. To strike a balance between aggregation and dispersion within the swarm and bolster VABES's global optimization prowess, an adaptive probability-guided Levy flight correction scheme has been devised. Additionally, a dynamic mutation factor-based mutation and crossover strategy has been formulated to refine VABES's exploitation capabilities. The results of 100-dimensional tests conducted on 40 benchmark functions from CEC2017 and CEC2020, coupled with nonparametric testing, reveal that VABES outperforms at least 66 % of other competitive improved algorithms. Experiments involving 57 real-world problems demonstrate that VABES's total performance metric stands at 0.1466, ranking it first and showcasing its notable advantages in handling constrained optimization compared to BES-related improved algorithms. Furthermore, the solution processes for three photovoltaic parameter optimization models illustrate that VABES converges rapidly, reducing errors by 26 %, and exhibits certain advantages in estimating diverse photovoltaic model parameters.</div></div>","PeriodicalId":11798,"journal":{"name":"Energy Reports","volume":"13 ","pages":"Pages 2129-2152"},"PeriodicalIF":4.7,"publicationDate":"2025-01-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143154899","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}

引用次数: 0

Promoting decarbonization in waste and energy sectors in Delhi (India) through circular economy and resource recovery: A low carbon transition towards renewable energy

IF 4.7 3区工程技术 Q2 ENERGY & FUELS

Energy Reports

Pub Date : 2025-01-31 DOI: 10.1016/j.egyr.2025.01.066

Jianzhi Bai , Xue Liang , Hui Hwang Goh , Tonni Agustiono Kurniawan , Kai Chen Goh , Xifeng Xie , Yi Peng , Lingyun Liu , Jianghong Yin

This study explores the potential of decarbonizing the waste and energy sectors in Delhi, India, through the application of Circular Economy (CE) principles and resource recovery strategies. By utilizing a low-carbon transition framework, we propose an integrated model that combines WtE technologies with renewable energy generation, contributing to sustainable urban development and climate change mitigation. A novel "Refuse, Reduce, Reuse, Repair, Recycle, and Recover" (6 R) methodolog based on system dynamics modeling is used to assess the energy potential and emission reductions from municipal solid waste (MSW) management and methane (CH₄) recovery in landfills. The study demonstrates that optimizing the CE approach, including strategies like waste recycling, resource recovery, and biogas production, can significantly reduce carbon emissions and improve energy security in Delhi. Key findings show that integrating CE principles can lead to a reduction in carbon emissions by up to 25 % over the next decade, while generating substantial renewable energy, potentially meeting 4.92 * 10⁹ kWh of electricity, equivalent to 15 % of Delhi's annual energy demand. The novel aspect of this research lies in its multi-sectoral integration, combining waste management, energy recovery, and economic modeling to quantify the environmental and energy benefits. The study underscores the importance of aligning policy, business practices, and technological innovation in promoting a CE at the urban scale. The broader implications of this work suggest that Delhi’s experience can serve as a blueprint for other cities in developing economies, highlighting how integrated resource recovery systems can drive sustainable energy transitions and climate resilience.

{"title":"Promoting decarbonization in waste and energy sectors in Delhi (India) through circular economy and resource recovery: A low carbon transition towards renewable energy","authors":"Jianzhi Bai , Xue Liang , Hui Hwang Goh , Tonni Agustiono Kurniawan , Kai Chen Goh , Xifeng Xie , Yi Peng , Lingyun Liu , Jianghong Yin","doi":"10.1016/j.egyr.2025.01.066","DOIUrl":"10.1016/j.egyr.2025.01.066","url":null,"abstract":"<div><div>This study explores the potential of decarbonizing the waste and energy sectors in Delhi, India, through the application of Circular Economy (CE) principles and resource recovery strategies. By utilizing a low-carbon transition framework, we propose an integrated model that combines WtE technologies with renewable energy generation, contributing to sustainable urban development and climate change mitigation. A novel \"Refuse, Reduce, Reuse, Repair, Recycle, and Recover\" (6 R) methodolog based on system dynamics modeling is used to assess the energy potential and emission reductions from municipal solid waste (MSW) management and methane (CH<sub>4</sub>) recovery in landfills. The study demonstrates that optimizing the CE approach, including strategies like waste recycling, resource recovery, and biogas production, can significantly reduce carbon emissions and improve energy security in Delhi. Key findings show that integrating CE principles can lead to a reduction in carbon emissions by up to 25 % over the next decade, while generating substantial renewable energy, potentially meeting 4.92 * 10<sup>9</sup> kWh of electricity, equivalent to 15 % of Delhi's annual energy demand. The novel aspect of this research lies in its multi-sectoral integration, combining waste management, energy recovery, and economic modeling to quantify the environmental and energy benefits. The study underscores the importance of aligning policy, business practices, and technological innovation in promoting a CE at the urban scale. The broader implications of this work suggest that Delhi’s experience can serve as a blueprint for other cities in developing economies, highlighting how integrated resource recovery systems can drive sustainable energy transitions and climate resilience.</div></div>","PeriodicalId":11798,"journal":{"name":"Energy Reports","volume":"13 ","pages":"Pages 2106-2128"},"PeriodicalIF":4.7,"publicationDate":"2025-01-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143154898","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}

引用次数: 0

Smart buildings: Federated learning-driven secure, transparent and smart energy management system using XAI

IF 4.7 3区工程技术 Q2 ENERGY & FUELS

Energy Reports

Pub Date : 2025-01-30 DOI: 10.1016/j.egyr.2025.01.063

Muhammad Adnan Khan , Muhammad Sajid Farooq , Muhammad Saleem , Tariq Shahzad , Munir Ahmad , Sagheer Abbas , Adnan M. Abu-Mahfouz

In modern smart grids and decentralized systems, smart buildings face several key energy management challenges, including data privacy concerns, the need for accurate real-time decisions, the complexity of managing Distributed Energy Resources (DERs), and the lack of transparency in Artificial Intelligence (AI) systems, which erodes user trust. Traditional energy management systems rely on centralized data gathering and processing, where energy data from various sources is accumulated and processed in one location. While centralization aids in decision-making regarding energy distribution, it also raises concerns about data privacy, cybersecurity, and the opaque nature of AI decisions, all of which undermine user confidence. To address these issues, Federated Learning (FL) and Explainable Artificial Intelligence (XAI) offer promising solutions. FL decentralizes model training, enhancing data privacy and security, while XAI provides clear explanations of AI decisions, fostering user trust. When combined, FL and XAI create a secure, transparent, and interpretable framework for managing energy in smart buildings. This paper proposes an FL-driven XAI model that aims to improve data privacy, accelerate real-time decision-making, enhance efficiency, and increase transparency, thereby building user trust. The proposed model demonstrates superior performance in simulations compared to previously published approaches.

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引用次数: 0

Assessing the availability and feasibility of renewable energy on the Great Barrier Reef-Australia

IF 4.7 3区工程技术 Q2 ENERGY & FUELS

Energy Reports

Pub Date : 2025-01-30 DOI: 10.1016/j.egyr.2025.01.036

Dan Virah-Sawmy , Bjorn Sturmberg , Daniel P. Harrison

The Great Barrier Reef (GBR), the world’s largest reef system and a UNESCO World Heritage site, is one of the most complex natural ecosystems on Earth. However, the GBR is at considerable risk from climate change and there is an urgent need to reduce reliance on fossil fuels and decarbonise the many activities taking place on the GBR. This study assesses the availability of renewable energy resources- solar, wind, wave, and tidal- on the GBR. Findings indicate that solar and wind energy are the most abundant natural resources on the GBR, while wave and tidal energy are only available in sparse locations and are low in magnitude. A feasibility analysis is conducted for various renewable energy technologies based on a case study for an Aerosol Radiation Interaction Experimental Laboratory system (ARIEL), an apparatus being used to investigate marine cloud brightening on the GBR. Factors used in the feasibility assessment include maturity of technology, portability, adaptability across the GBR, and ecological impacts on marine life and birds. Results suggest that solar photovoltaics, installed on a barge, would be the most suitable option for rapid near-term implementation. Not only is solar energy available throughout the whole GBR, but it is also a proven and mature technology and would have minimal impact on marine life and on birds. A proposed hybrid energy system could reduce the ARIEL’s CO₂ emissions by 44–59 %, varying by location. The findings offer a roadmap for deploying cleaner energy systems on the GBR, balancing environmental protection with technological considerations.

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引用次数: 0

Analysis of water-energy nexus considering the net zero-carbon transformation of power sector in Southern China

IF 4.7 3区工程技术 Q2 ENERGY & FUELS

Energy Reports

Pub Date : 2025-01-29 DOI: 10.1016/j.egyr.2025.01.062

Hongye Wang , Bin Su , Ye Duan

In China, the carbon peak and neutrality targets proposed in 2020 will not only reduce carbon emissions, but also improve the sustainable development level of the whole society. As a major CO₂ emitter and water-energy consumer in China, the long-term sustainable development of power sector has become an energy structure transition and water resource conservation issue considering China’s "30–60" CO₂ goals. The development of renewable energy, such as hydropower, has been important to the long-term sustainable development of power industry. However, China's current water resources policy did not consider the water consumption by hydropower in waterways, and previous research has also neglected the drawback of hydropower in the perspective of water consumption, exaggerating the advantages of hydropower in sustainable development. Therefore, to achieve long-term sustainable development of power sector and improve the current water resources policy in China, this paper initially established a long-term multi-regional water-energy optimization model for power sector under "30–60" goals, considering the interaction of policies about renewable energy promotion, instream water conservation and CO₂ emission reduction; and analysed the influence of current and enhanced water policies on power sector by taking the Southern China, which is rich in hydropower, as a case. Based on these results, this paper has provided an optimal schedule for the power sector in Southern China until 2060 from the perspectives of power generation, power trading, water consumption, and water-energy nexus. What’s more, compared with the enhanced water policy that considering the water consumption in rivers, the current water policy will neglect 92.62 hundred million m³ water every year in Southern China from 2021 to 2060. Therefore, this paper revealed that water consumed in rivers by hydropower should be considered in Southern China’s water policy to achieve the long-term sustainable development in the power sector.

{"title":"Analysis of water-energy nexus considering the net zero-carbon transformation of power sector in Southern China","authors":"Hongye Wang , Bin Su , Ye Duan","doi":"10.1016/j.egyr.2025.01.062","DOIUrl":"10.1016/j.egyr.2025.01.062","url":null,"abstract":"<div><div>In China, the carbon peak and neutrality targets proposed in 2020 will not only reduce carbon emissions, but also improve the sustainable development level of the whole society. As a major CO<sub>2</sub> emitter and water-energy consumer in China, the long-term sustainable development of power sector has become an energy structure transition and water resource conservation issue considering China’s \"30–60\" CO<sub>2</sub> goals. The development of renewable energy, such as hydropower, has been important to the long-term sustainable development of power industry. However, China's current water resources policy did not consider the water consumption by hydropower in waterways, and previous research has also neglected the drawback of hydropower in the perspective of water consumption, exaggerating the advantages of hydropower in sustainable development. Therefore, to achieve long-term sustainable development of power sector and improve the current water resources policy in China, this paper initially established a long-term multi-regional water-energy optimization model for power sector under \"30–60\" goals, considering the interaction of policies about renewable energy promotion, instream water conservation and CO<sub>2</sub> emission reduction; and analysed the influence of current and enhanced water policies on power sector by taking the Southern China, which is rich in hydropower, as a case. Based on these results, this paper has provided an optimal schedule for the power sector in Southern China until 2060 from the perspectives of power generation, power trading, water consumption, and water-energy nexus. What’s more, compared with the enhanced water policy that considering the water consumption in rivers, the current water policy will neglect 92.62 hundred million m<sup>3</sup> water every year in Southern China from 2021 to 2060. Therefore, this paper revealed that water consumed in rivers by hydropower should be considered in Southern China’s water policy to achieve the long-term sustainable development in the power sector.</div></div>","PeriodicalId":11798,"journal":{"name":"Energy Reports","volume":"13 ","pages":"Pages 2013-2020"},"PeriodicalIF":4.7,"publicationDate":"2025-01-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143154893","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}

引用次数: 0