| Numéro |
Sci. Tech. Energ. Transition
Volume 79, 2024
Decarbonizing Energy Systems: Smart Grid and Renewable Technologies
|
|
|---|---|---|
| Numéro d'article | 43 | |
| Nombre de pages | 14 | |
| DOI | https://doi.org/10.2516/stet/2024035 | |
| Publié en ligne | 30 juillet 2024 | |
- Wang X., et al. (2022) Research progress and prospects of advanced power generation technology under the goal of carbon emission peak and carbon neutrality, Therm. Power Gen. 51, 1, 52–59. [Google Scholar]
- Chong C.T., et al. (2022) Post COVID-19 energy sustainability and carbon emissions neutrality, Energy 241, 122801. [CrossRef] [PubMed] [Google Scholar]
- Wang D., Xue X., Wang Y. (2021) Overcapacity risk of China’s coal power industry: a comprehensive assessment and driving factors, Sustainability 13, 3, 1426. [CrossRef] [Google Scholar]
- Bin O., et al. (2015) Calculation and evaluation methodology of transport energy consumption and carbon emission—the case of Jiangsu Province, Soft Sci. 29, 1, 139–144. [Google Scholar]
- Lu Y., Chen X. (2023) Digital economy, new-type urbanization, and carbon emissions: evidence from China, Environ. Prog. Sustain. Energy 42, 3, e14045. [CrossRef] [Google Scholar]
- Zhou S., et al. (2023) A data-driven method to monitor carbon dioxide emissions of coal-fired power plants, Energies 16, 4, 1646. [CrossRef] [Google Scholar]
- Wang X., et al. (2022) Evaluating the data quality of continuous emissions monitoring systems in China, J. Environ. Manag. 314, 115081. [CrossRef] [Google Scholar]
- Zhao R., et al. (2014) Carbon emission and carbon footprint of different industrial spaces in different regions of China, Singapore: Springer. [Google Scholar]
- Shang C., Zhang Z. (2010) Assessment of life-cycle carbon emission for buildings, J. Eng. Manage. 24, 1, 7–12. [Google Scholar]
- Yan X., et al. (2012) Correlation analysis of economic development and carbon footprint in Chongqing City, J. Southwest China Normal Univ. (Nat. Sci. Ed.) 37, 6, 167–173. [Google Scholar]
- Zhang N., et al. (2023) Carbon measurement method and carbon system for whole chain of power system[J], Autom. Electr. Power Syst. 47, 9, 2–12. [Google Scholar]
- Zhou C., et al. (2023) Accounting CO2 emissions of the cement industry: based on an electricity-carbon coupling analysis, Energies 16, 11, 4453. [CrossRef] [Google Scholar]
- Chamandoust H., Bahramara S., Derakhshan G. (2020) Day-ahead scheduling problem of smart micro-grid with high penetration of wind energy and demand side management strategies, Sustain. Energy Technol. Assess. 40, 100747. [Google Scholar]
- Chamandoust H., Derakhshan G., Bahramara S. (2020) Multi-objective performance of smart hybrid energy system with Multi-optimal participation of customers in day-ahead energy market, Energy Build. 216, 109964. [CrossRef] [Google Scholar]
- Chamandoust H., et al. (2020) Multi-objectives optimal scheduling in smart energy hub system with electrical and thermal responsive loads, Environ. Clim. Technol. 24, 1, 209–232. [CrossRef] [Google Scholar]
- Chamandoust H., et al. (2019) Tri-objective optimal scheduling of smart energy hub system with schedulable loads, J. Clean. Prod. 236, 117584. [CrossRef] [Google Scholar]
- Chamandoust H., et al. (2020) Tri-objective scheduling of residential smart electrical distribution grids with optimal joint of responsive loads with renewable energy sources, J. Energy Storage 27, 101112. [CrossRef] [Google Scholar]
- Xiang X., et al. (2022) Python-LMDI: a tool for index decomposition analysis of building carbon emissions, Buildings 12, 1, 83. [CrossRef] [Google Scholar]
- He Z., Zhou Y., Liu Y. (2020) System dynamics simulation on China’s energy consumption in 2050: Based on the policy scenarios of key industries, J. Nat. Resour. 35, 11, 2696–2707. [Google Scholar]
- Jiang H., Zhang H., Shi X. (2022) Refined production simulation and operation cost evaluation for power system with high proportion of renewable energy, Energy Rep. 8, 108–118. [CrossRef] [Google Scholar]
- Yuan K., et al. (2023) Exploration of low-cost green transition opportunities for China’s power system under dual carbon goals, J. Clean. Prod. 414, 137590. [CrossRef] [Google Scholar]
- Yu Y., et al. (2022) Implications of power industry marketization for sustainable generation portfolios in China, J. Clean. Prod. 378, 134541. [CrossRef] [Google Scholar]
- Li Y.-Y., Li H. (2022) China’s inter-regional embodied carbon emissions: an industrial transfer perspective, Environ. Sci. Pollut. Res. 29, 3, 4062–4075. [CrossRef] [PubMed] [Google Scholar]
- Chi Y., et al. (2022) Driving factors of CO2 emissions in China’s power industry: relative importance analysis based on spatial durbin model, Energies 15, 7, 2631. [CrossRef] [Google Scholar]
- Zhao F., Qian S., Zhao X. (2023) Collaborative governance of carbon reduction in urban agglomerations in the China Yangtze River Economic Belt based on a spatial association network, Ecol. Indic. 154, 110663. [CrossRef] [Google Scholar]
- Wang L., Li K. (2022) Research on renewable energy consumption and emission reduction in power market based on bi-level decision making in China, Energy 260, 125119. [CrossRef] [Google Scholar]
- Wu Y., et al. (2022) Research on greenhouse gas emissions accounting methods in environmental impact assessment of construction projects: a case of thermal power project, J. Environ. Eng. Technol. 12, 6, 1890–1897. [Google Scholar]
- Dong B. (2019) Study on the relationship between carbon emissions, industrial structure and economic growth, Beijing: Northeast University of Finance and Economics. [Google Scholar]
- Zhang L., et al. (2020) Minimizing energy consumption scheduling algorithm of workflows with cost budget constraint on heterogeneous cloud computing systems, IEEE Access 8, 205099–205110. [CrossRef] [Google Scholar]
- Yang Xiaoting S.H.U.J. (2021) Expansion programming of integrated energy system for large industrial user considering the CCHP, Elect. Power Constr. 42, 2, 107–115. [Google Scholar]
- Bui V.-H., et al. (2021) Optimal sizing of energy storage system for operation of wind farms considering grid-code constraints, Energies 14, 17, 5478. [CrossRef] [Google Scholar]
- Dai L., Wang M. (2020) Study on the influence of carbon emission constraints on the performance of thermal power enterprises, Environ. Sci. Pollut. Res. 27, 24, 30875–30884. [CrossRef] [PubMed] [Google Scholar]
- Tang B.-J., et al. (2019) Spatial and temporal uncertainty in the technological pathway towards a low-carbon power industry: a case study of China, J. Clean. Prod. 230, 720–733. [CrossRef] [Google Scholar]
- Yu B., et al. (2021) Research on China’s CO2 emission pathway under carbon neutral target, J. Beijing Inst. Technol. (Soc. Sci. Ed.) 23, 2, 17–24. [Google Scholar]
- Yang Z., et al. (2022) The impact of economic growth, industrial transition, and energy intensity on carbon dioxide emissions in China, Sustainability 14, 9, 4884. [CrossRef] [Google Scholar]
- Borsato B., Plastino A., Merschmann L. (2008) K-NN: estimating an adequate value for parameter K. In 10th international conference on enterprise information systems. Barcelona, Spain. [Google Scholar]
- Brzezińska A.N., Horyń C. (2021) Outliers in Covid 19 data based on rule representation – the analysis of LOF algorithm, Proc. Comput. Sci. 192, 3010–3019. [CrossRef] [Google Scholar]
- Ang B.W., Liu F.L. (2001) A new energy decomposition method: perfect in decomposition and consistent in aggregation, Energy 26, 6, 537–548. [CrossRef] [Google Scholar]
Les statistiques affichées correspondent au cumul d'une part des vues des résumés de l'article et d'autre part des vues et téléchargements de l'article plein-texte (PDF, Full-HTML, ePub... selon les formats disponibles) sur la platefome Vision4Press.
Les statistiques sont disponibles avec un délai de 48 à 96 heures et sont mises à jour quotidiennement en semaine.
Le chargement des statistiques peut être long.