| 1. |
- Chen, B., et al.
(författare)
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Pathways for sustainable energy transition
- 2019
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Ingår i: Journal of Cleaner Production. - : Elsevier Ltd. - 0959-6526 .- 1879-1786. ; 228, s. 1564-1571
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Tidskriftsartikel (refereegranskat)abstract
- Energy transitions are ongoing processes all over the world. While sustainable solutions are envisioned for the future, many societies are still under high-carbon and high-pollution energy regime borne by fossil fuels. How to design pathways towards sustainable energy transition has attracted worldwide concerns. Understanding the possible transition pathways of the energy system requires the integration of new energy technologies, environmental sciences, economics and management. This Special Issue of Journal of Cleaner Production targets to collect the latest research results on sustainable energy systems, discover innovative avenues and inspiring models and share knowledge on energy system modelling and management. In this paper, we identify 4 themes on sustainable energy transition pathways including: (1)Sustainable energy economics and management; (2)Renewable energy generation and consumption; (3)Environmental impacts of energy systems; and (4)Electric vehicle and energy storage. Theories, technologies, innovative models, and successful experiences are discussed accordingly. It is suggested that creative, robust and audacious strategies in governance, management and education are needed to boost sustainable energy transition across various scales and sectors.
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| 2. |
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| 3. |
- Li, W., et al.
(författare)
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Methane production through anaerobic digestion : Participation and digestion characteristics of cellulose, hemicellulose and lignin
- 2018
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Ingår i: Applied Energy. - : Elsevier Ltd. - 0306-2619 .- 1872-9118. ; 226, s. 1219-1228
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Tidskriftsartikel (refereegranskat)abstract
- Lignocellulosic biomass is the most abundant natural resource with high biomethane potential. However, complex structure of lignocellulosic biomass has hampered the efficient utilization of this bioresource. Previous studies have investigated the overall anaerobic digestion performance of lignocellulosic biomass, but the individual participation of each lignocellulosic component during anaerobic digestion remained unclear. Thus, this study investigated the methane production characteristics of cellulose, hemicellulose, lignin and their mixtures along with the microbial communities involved in anaerobic digestion. The results showed that the biomethane potential of cellulose was higher than that of hemicellulose; however, hemicellulose was hydrolysed more quickly than cellulose, while lignin was very difficult to be digested. The higher concentrations of acetic, n-butyric and n-valeric acids hydrolysed from the hemicellulose resulted in a lower pH and more severe inhibition on methane production than that of cellulose, and the methanogenesis gradually recovered after pH adjustment. The co-digestion of cellulose and hemicellulose increased the methane yield and biodegradability compared to mono-digestions. The addition of lignin to cellulose brought more significant decrease in the methane yield of cellulose than that of hemicellulose. Substrate-related bacteria such as Clostridium sensu stricto, Lutaonella, Cloacibacillus and Christensenella showed higher relative abundance in cellulose digestate, and sugar-fermenting bacteria such as Saccharofermentans, Petrimonas and Levilinea were more rich in the digestate of hemicellulose. Moreover, methanogenic Methanospirillum and Methanothrix likely contributed to the methane production of cellulose, while aciduric methanogens from Methanobrevibacter, Methanomassiliicoccus, Methanobacterium and Methanoculleus contributed to that of hemicellulose. This study provides a deeper understanding of the mechanism in the bioconversion of lignocellulosic biomass during anaerobic digestion.
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| 4. |
- Qiu, R., et al.
(författare)
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Roadmap to urban energy internet with wind electricity-natural gas nexus : Economic and environmental analysis
- 2022
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Ingår i: Energy. - : Elsevier. - 0360-5442 .- 1873-6785. ; 245
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Tidskriftsartikel (refereegranskat)abstract
- Electrolysis hydrogen generation technology is one of the feasible ways to alleviate the problem of wind electricity curtailment. One promising hydrogen value-added application is to blend hydrogen into the natural gas grid and sell it as the heat energy carrier. This paper aims to discuss the feasibility of a roadmap to urban energy internet with wind electricity-natural gas nexus. Firstly, a framework is raised to integrate wind electricity generation, electrolysis hydrogen generation, and hydrogen-natural gas blending systems. Secondly, a series of reasonable hydrogen supply profiles are provided based on annual electricity curtailment and realistic natural gas scheduling. Then, an energy optimisation model and a techno-economic model are applied to simulate the generation of electricity and hydrogen, as well as determine the most economical hydrogen supply scheme. Finally, a case study in the Beijing-Tianjin-Hebei region of China is taken to validate the benefits of the proposed roadmap. The preferred scheme is worked out with the net present value of 88.8 M$, including the economy configurations of the electricity-hydrogen hybrid generation system, as well as the hydrogen-natural gas blending plan. The results also indicate that annual electricity curtailment and annual carbon emission are decreased by 204 GWh (48.8%) and 40.2 kt (49.9%).
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| 5. |
- Xiong, R., et al.
(författare)
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A data-driven method for extracting aging features to accurately predict the battery health
- 2023
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Ingår i: Energy Storage Materials. - : Elsevier B.V.. - 2405-8289 .- 2405-8297. ; 57, s. 460-470
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Tidskriftsartikel (refereegranskat)abstract
- Data-driven methods have been widely used for estimating the state of health (SOH) of lithium-ion batteries (LiBs). The aging process can be characterized by degrading features. To achieve high accuracy, a novel method combining four algorithms, i.e. the correlation coefficient, least absolute shrinkage and selection operator regression, neighborhood component analysis, and ReliefF algorithm, is proposed to select the most important features, which are derived from the measured and calculated parameters. To demonstrate the effectiveness of the proposed method, it is adopted to estimate the SOH of two types of LiBs: i.e. NCA and LFP batteries. Compared to the case using all features, using the selected features can improve the accuracy of SOH estimation by 63.5% and 71.1% for the NCA and LFP batteries, respectively. The method can also enable the use of data obtained in partial voltage ranges, based on which the minimum root mean square errors on SOH estimation are 1.2% and 1.6% for the studied NCA and LFP batteries, respectively. It demonstrates the capability for onboard applications.
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| 6. |
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| 7. |
- Yan, Jinyue, et al.
(författare)
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Editorial
- 2016
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Ingår i: Energy Procedia. - : Elsevier BV. - 1876-6102. ; 104, s. 1-2
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Tidskriftsartikel (refereegranskat)
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| 8. |
- Zhang, Kai, et al.
(författare)
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Power generation assessment of photovoltaic noise barriers across 52 major Chinese cities
- 2024
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Ingår i: Applied Energy. - : Elsevier Ltd. - 0306-2619 .- 1872-9118. ; 361
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Tidskriftsartikel (refereegranskat)abstract
- Photovoltaic noise barriers (PVNBs) have the potential to contribute to sustainable urban development by increasing the supply of renewable energy to cities while decreasing traffic noise pollution. However, estimating the power generation of PVNBs at the city or national scale remains a challenge due to the complexities of the urban environment and the difficulties associated with collecting data on road noise barriers (RNBs) and radiation. This study used RNBs, 2.5-dimensional (2.5D) buildings, and hourly time resolution radiation data, to estimate the power generation of PVNBs in 52 of China's major cities. First, hourly building shadows were estimated for each day of the year, covering the period from sunrise to sunset, to identify areas of RNB that are shaded at any given time. Second, hourly clear-sky radiation data were collected and corrected using a radiation correction model to simulate real weather radiation. Finally, utilizing an inclined surface radiation estimation model, the photovoltaic (PV) potential both inside and outside RNBs affected by building shadows was assessed. Subsequently, the power generation of PVNB was estimated based on parameters of mainstream PV systems in the market. The results show that the RNB mileage in 52 selected cities represents 87.7% of China's total RNB mileage. Building shadows often result in a radiation loss of approximately 30% for RNBs reception. The installed capacity and annual power generation of PVNBs in all investigated cities are 2.04 GW and 690.74 GWh, respectively. This study estimates the comprehensive PV potential of potentially exploitable PVNBs in China, offering essential scientific insights to inform and facilitate the strategic development of PVNB projects at both the national and municipal levels.
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| 9. |
- Zhang, K., et al.
(författare)
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Using street view images to identify road noise barriers with ensemble classification model and geospatial analysis
- 2022
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Ingår i: Sustainable cities and society. - : Elsevier Ltd. - 2210-6707. ; 78
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Tidskriftsartikel (refereegranskat)abstract
- Road noise barriers (RNBs) are important urban infrastructures to relieve the harm of traffic noise pollution for citizens. Therefore, obtaining the spatial distribution characteristics of RNBs, such as precise positions and mileage, can be of great help for obtaining more accurate urban noise maps and assessing the quality of the urban living environment for sustainable urban development. However, an effective and efficient method for identifying RNBs and acquiring their attributes in large areas is scarce. This study constructs an ensemble classification model (ECM) to automatically identify RNBs at the city level based on Baidu Street View (BSV). Firstly, the bootstrap sampling method is proposed to build a street view image-based train set, where the effect of imbalanced categories of samples was reduced by adding confusing negative samples. Secondly, two state-of-the-art deep learning models, ResNet and DenseNet, are ensembled to construct an ECM based on the bagging framework. Finally, a post-processing method has been proposed based on geospatial analysis to eliminate street view images (SVIs) that are misclassified as RNBs. This study takes Suzhou, China as the study area to validate the proposed method. The model achieved an accuracy and F1-score of 0.98 and 0.90, respectively. The total mileage of the RNBs in Suzhou was 178,919 m. The results demonstrated the performance of the proposed RNBs identification framework. The significance of obtaining RNBs attributes for accelerating sustainable urban development has been demonstrated through the case of photovoltaic noise barriers (PVNBs).
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| 10. |
- Zhang, R., et al.
(författare)
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Pore-scale study of effects of relative humidity on reactive transport processes in catalyst layers in PEMFC
- 2022
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Ingår i: Applied Energy. - : Elsevier Ltd. - 0306-2619 .- 1872-9118. ; 323
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Tidskriftsartikel (refereegranskat)abstract
- High surface area carbon (HSC) particles can be adopted to increase the specific surface area of catalyst layer (CL) in proton exchange membrane fuel cells. Relative humidity (RH) has a significant effect on the Pt activity inside HSC particles, and the underlying mechanisms need to be further investigated. In this study, a pore-scale model considering the effects of RH on the reactive transport processes inside the CLs is developed. Two kinds of liquid water distributions affected by the RH, including capillary condensation in pores and ultra-thin liquid film on Pt surface, are considered. The liquid water distribution, Pt activity and local oxygen transport resistance (Rlocal) under different RH are studied in detail. It is found that as RH increases from 0.3 to 1.0, the condensed water in micropores of HSC particles increases, resulting in an increase in reactive surface area by about 43 %. Combined effect of the RH, Pt loading, I/C ratio and different kinds of carbon particles is investigated. It is found that due to the lack of sufficient reaction sites, compared with that under a high Pt loading, Rlocal under a low Pt loading is more sensitive to the RH. Besides, since the Pt activity inside HSC particles depends on the condensed water, the Rlocal of HSC particles is more sensitive to the RH than solid carbon particles. Finally, the Rlocal at low ionomer content is more sensitive to RH due to low ionomer coverage on Pt particles. The present study provides a pore-scale model for investigating the coupled effects of RH and CL porous structures on local transport processes, and can facilitate the optimization of CL nanoscale structures for better cell performance.
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