The Experts below are selected from a list of 162189 Experts worldwide ranked by ideXlab platform
Pei Liu - One of the best experts on this subject based on the ideXlab platform.
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electric vehicle development in china a charging behavior and Power Sector supply balance analysis
Chemical Engineering Research & Design, 2017Co-Authors: Zhihao Chen, Pei LiuAbstract:Abstract Possession of motor vehicles in China has been rising fast, along with continuous economic growth, social development and improvements in living standards, causing severe energy and environmental stress. To relieve the stress, China is promoting electric vehicles as good alternatives to conventional vehicles. By 2020, the accumulated production and sales of electric vehicles are expected to reach five million. Large-scale connection of electric vehicles to the Power grid would inevitably bring challenges to the Power Sector. In this paper, an electric vehicle and multi-region load-dispatch grid-structure-based (EVMLG) mathematical model is presented, aiming to investigate the interaction between electric vehicles and the Power Sector. Impacts of charging behaviors are carefully considered. Through case studies, we conclude that (1) the development of electric vehicles will influence regional generation portfolio and operation pattern of the Power Sector, and increase the utilization of renewables, (2) guided charging can adapt to the Power Sector, and lead to better economic and environmental benefits, (3) electric vehicles are suitable to be deployed in resource-rich regions, and (4) the development potential of electric vehicles in China is huge from the viewpoint of Power supply capacity.
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a multi region optimization planning model for china s Power Sector
Applied Energy, 2015Co-Authors: Rui Cheng, Pei Liu, Zhe Wang, Ian JonesAbstract:Demand for electricity in China kept accelerating in recent years; moreover, there exist serious mismatches among the distribution of Power demand, energy resources, and Power generation infrastructure across different regions in China, both of which indicate a necessity of a holistic and integrated approach to the strategic planning and development of its Power industry. Material benefits could be realized by ensuring that the long term development of the Power system is optimized by taking into consideration the different regional dynamics and characteristics. This paper proposes a multi-region optimization model that can deliver insights into how planning of the long term development of China’s Power Sector could minimize the total cost of China’s Power Sector by considering regional variations in availabilities of resources and inter-region Power transmission line capacity. A case study considered how investment decisions to expand and alter the existing generation mix could be optimized across a timeframe from 2011 to 2050. By comparing results between single and multi-region optimizations, it was possible to show the likely impact on how investment decisions would differ when regional differences were taken into account. The multi-region optimization arguably better reflects and considers conditions and challenges in the real world.
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a multi period optimization model for planning of china s Power Sector with consideration of carbon dioxide mitigation the importance of continuous and stable carbon mitigation policy
Energy Policy, 2013Co-Authors: Dongjie Zhang, Pei Liu, Li ZhengAbstract:Abstract A great challenge China's Power Sector faces is to mitigate its carbon emissions whilst satisfying the ever-increasing Power demand. Optimal planning of the Power Sector with consideration of carbon mitigation for a long-term future remains a complex task, involving many technical alternatives and an infinite number of possible plants installations, retrofitting, and decommissioning over the planning horizon. Previously the authors built a multi-period optimization model for the planning of China's Power Sector during 2010–2050. Based on that model, this paper executed calculations on the optimal pathways of China's Power Sector with two typical decision-making modes, which are based on “full-information” and “limited-information” hypothesis, and analyzed the impacts on the optimal planning results by two typical types of carbon tax policies including a “continuous and stable” one and a “loose first and tight later” one. The results showed that making carbon tax policy for long-term future, and improving the continuity and stability in policy execution can effectively help reduce the accumulated total carbon emissions, and also the cost for carbon mitigation of the Power Sector. The conclusion of this study is of great significance for the policy makers to make carbon mitigation policies in China and other countries as well.
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a multi period modelling and optimization approach to the planning of china s Power Sector with consideration of carbon dioxide mitigation
Computers & Chemical Engineering, 2012Co-Authors: Dongjie Zhang, Pei LiuAbstract:Abstract A great challenge China's Power Sector faces is to mitigate its carbon dioxide emissions while satisfying the ever-increasing Power demand. Optimal planning of the Power Sector with consideration of carbon mitigation for a long-term future remains a complex task, involving many technical alternatives and an infinite number of possible plants installations, retrofitting, and decommissioning over the planning horizon. This paper presents a multi-period modelling and optimization framework for the optimal planning of China's Power Sector between 2010 and 2050. The planning horizon is divided into several time intervals, over which Power plants of all types can be installed, retrofitted, or closed. Impacts of carbon mitigation related measures, including carbon cap and price, application of carbon capture and sequestration, are explicitly represented. A case study follows, based on real-life data of existing capacity of China's Power Sector in 2009, and a year-by-year development plan for China's Power Sector is proposed.
Yiyi Zhang - One of the best experts on this subject based on the ideXlab platform.
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driving forces and clustering analysis of provincial level co2 emissions from the Power Sector in china from 2005 to 2015
Journal of Cleaner Production, 2019Co-Authors: Changyi Liao, Saige Wang, Yiyi Zhang, Dan Song, Chaohai ZhangAbstract:Abstract Understanding the drivers of provincial-level CO2 emissions from the Power Sector is critical for realizing Power Sector decarbonization and achieving national carbon reduction targets. In this study, the CO2 emissions from electricity generation in 30 provinces of China during the period of 2005–2015 are systematically inventoried. The Logarithmic Mean Divisia Index (LMDI) model is used to analyze the driving forces of changes in CO2 emissions of the Power Sector. In addition, to analyze the impact of the Chinese 11th and 12th Five-Year Plan on carbon emissions, this study divides the studied period into two sub-periods, 2005–2010 and 2010–2015. Finally, based on their CO2 emission characteristics, we divide 30 provinces into 5 clusters using the K-means clustering to further investigate the carbon reduction measures. The results show that for national CO2 emissions of the Power Sector, the economic activity effect played a key role in raising CO2 emissions in 2005–2015, while the industrial electricity intensity effect and the energy efficiency effect contributed the most to CO2 reduction during the periods of 2005–2010 and 2010–2015, respectively. During the period of 2010–2015, Inner Mongolia, Jiangsu, Shandong, and Xinjiang contributed the most to reducing CO2 emissions. In addition, for most provinces, the industrial electricity intensity effect was the main driver for reducing CO2 emissions of the Power Sector. Meanwhile, the electricity structure effect played an increasingly decisive role in declining emissions in provinces where renewable energy is blooming, such as in Yunnan and Sichuan; while for the industrial structure optimized provinces like Hebei and Jiangsu, the industry structure effect played a primary role. By investigating the driving forces of changes in CO2 emissions from the Power Sector, this study aims to provide insights for provincial decarbonization pathways of the Power Sector.
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driving forces of provincial level co2 emissions in china s Power Sector based on lmdi method
Energy Procedia, 2019Co-Authors: Changyi Liao, Saige Wang, Jiake Fang, Hanbo Zheng, Jiefeng Liu, Yiyi ZhangAbstract:Abstract As the major energy consumer and carbon emitter, the Power Sector accounts for 40% of total carbon emissions in China in 2011. Understanding provincial-level driving mechanisms of CO2 emissions in Power Sector is vital for achieving China’s national carbon emissions reduction targets in 2030. To understand the critical provinces and driving forces of CO2 emissions in Power Sector, this paper firstly derives seven different driving factors based on the logarithmic mean Divisia index (LMDI) decomposition model. The provincial-level CO2 emissions in thermal Power Sectors are calculated from 2004 to 2014. Then, we analyze the CO2 emissions growth ratio of each province, provincial-level change rate of contribution and positive or negative contributions of the emission dynamics for each driving force. The main results show that the Power Sector of Inner Mongolia and Jiangsu contribute a lot to national CO2 emissions. The change of CO2 emissions of Power Sector is bigger in developing provinces compared to that in developed provinces. Based on provincial the CO2 emissions changes and total amounts, more carbon emission reduction policy should be implanted in Inner Mongolia, Xinjiang, Anhui, Jiangsu and Ningxia. In addition, the economic scale, industrial intensity and energy intensity are the critical driving forces for total carbon emission. By investigating the critical driving forces and their contributions in critical provinces, this paper aims to provide theoretical foundations for decarbonizing Power Sector.
Jacek Kaminski - One of the best experts on this subject based on the ideXlab platform.
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coal demand and environmental regulations a case study of the polish Power Sector
Energies, 2020Co-Authors: Przemyslaw Kaszynski, Jacek KaminskiAbstract:The impact of environmental regulations implemented in the Power industry that affect the consumption of solid fuels is of key importance to coal-based Power generation systems, such as that in Poland. In this context, the main purpose of the paper was to determine the future demand for hard coal and brown coal in the Polish Power Sector by 2050 with reference to the environmental regulations implemented in the Power Sector. To achieve these goals, a mathematical model was developed using the linear programming approach, which reflected the key relationships between the hard and brown coal mining Sector and the Power Sector in the context of the environmental regulations discussed. The environmental regulations selected had a great influence on the future demand for hard and brown coal in the Power generation Sector. The scope of this influence depended on particular regulations. The prices of CO 2 emission allowances and stricter emissions standards stemming from the Industrial Emissions Directive and the BAT (Best Available Techniques) conclusions had the largest influence on the reduction of hard coal demand. In the case of brown coal, no new Power generating units would be deployed; hence, brown coal consumption would drop practically to zero in 2050 under all the scenarios considered.
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a blocked takeover in the polish Power Sector a model based analysis
Energy Policy, 2014Co-Authors: Jacek KaminskiAbstract:As the President of the Office of Competition and Consumer Protection refused to approve a government initiated takeover in the Polish Power Sector and the Court of Competition and Consumer Protection did not make a ruling on that case, the takeover was finally prohibited. In this context, the main aim of this paper is to carry out a quantitative analysis of the impact of the takeover in question on electricity prices and quantities, consumer and producer surpluses, dead weight loss and emissions.
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the prospects for hard coal as a fuel for the polish Power Sector
Energy Policy, 2010Co-Authors: Jacek Kaminski, Mariusz KudełkoAbstract:This paper presents the prospects for the development of the Polish hard coal Sector from the perspective of the Power Sector. The most important issues determining the mid- and long-term future for domestic coal production are: (1) the development of the economy, hence the demand for electricity, (2) regulations (mostly environmental) affecting the Power Sector, (3) the competitiveness of coal-based technologies, and (4) the costs of domestic coal production. Since the range of issues and relations being considered is very broad, a specific method needs to be employed for the quantitative analysis. The tool applied in this study is the partial equilibrium model Power-POL, in which both the coal and the Power Sectors are incorporated. The model focuses on energy-economy-environmental issues without capturing detailed macroeconomic links. The model was run under six scenario assumptions. The results show that the domestic coal Sector should maintain its position as a key supplier of primary energy for the Polish Power Sector. However, the environmental regulations to which the domestic Power Sector has to conform will decrease the share of coal in the fuel-mix. Since the investment processes in this Sector are usually long-term, the effects of changes will be noticeable from 2015 onwards.
Changyi Liao - One of the best experts on this subject based on the ideXlab platform.
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driving forces and clustering analysis of provincial level co2 emissions from the Power Sector in china from 2005 to 2015
Journal of Cleaner Production, 2019Co-Authors: Changyi Liao, Saige Wang, Yiyi Zhang, Dan Song, Chaohai ZhangAbstract:Abstract Understanding the drivers of provincial-level CO2 emissions from the Power Sector is critical for realizing Power Sector decarbonization and achieving national carbon reduction targets. In this study, the CO2 emissions from electricity generation in 30 provinces of China during the period of 2005–2015 are systematically inventoried. The Logarithmic Mean Divisia Index (LMDI) model is used to analyze the driving forces of changes in CO2 emissions of the Power Sector. In addition, to analyze the impact of the Chinese 11th and 12th Five-Year Plan on carbon emissions, this study divides the studied period into two sub-periods, 2005–2010 and 2010–2015. Finally, based on their CO2 emission characteristics, we divide 30 provinces into 5 clusters using the K-means clustering to further investigate the carbon reduction measures. The results show that for national CO2 emissions of the Power Sector, the economic activity effect played a key role in raising CO2 emissions in 2005–2015, while the industrial electricity intensity effect and the energy efficiency effect contributed the most to CO2 reduction during the periods of 2005–2010 and 2010–2015, respectively. During the period of 2010–2015, Inner Mongolia, Jiangsu, Shandong, and Xinjiang contributed the most to reducing CO2 emissions. In addition, for most provinces, the industrial electricity intensity effect was the main driver for reducing CO2 emissions of the Power Sector. Meanwhile, the electricity structure effect played an increasingly decisive role in declining emissions in provinces where renewable energy is blooming, such as in Yunnan and Sichuan; while for the industrial structure optimized provinces like Hebei and Jiangsu, the industry structure effect played a primary role. By investigating the driving forces of changes in CO2 emissions from the Power Sector, this study aims to provide insights for provincial decarbonization pathways of the Power Sector.
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driving forces of provincial level co2 emissions in china s Power Sector based on lmdi method
Energy Procedia, 2019Co-Authors: Changyi Liao, Saige Wang, Jiake Fang, Hanbo Zheng, Jiefeng Liu, Yiyi ZhangAbstract:Abstract As the major energy consumer and carbon emitter, the Power Sector accounts for 40% of total carbon emissions in China in 2011. Understanding provincial-level driving mechanisms of CO2 emissions in Power Sector is vital for achieving China’s national carbon emissions reduction targets in 2030. To understand the critical provinces and driving forces of CO2 emissions in Power Sector, this paper firstly derives seven different driving factors based on the logarithmic mean Divisia index (LMDI) decomposition model. The provincial-level CO2 emissions in thermal Power Sectors are calculated from 2004 to 2014. Then, we analyze the CO2 emissions growth ratio of each province, provincial-level change rate of contribution and positive or negative contributions of the emission dynamics for each driving force. The main results show that the Power Sector of Inner Mongolia and Jiangsu contribute a lot to national CO2 emissions. The change of CO2 emissions of Power Sector is bigger in developing provinces compared to that in developed provinces. Based on provincial the CO2 emissions changes and total amounts, more carbon emission reduction policy should be implanted in Inner Mongolia, Xinjiang, Anhui, Jiangsu and Ningxia. In addition, the economic scale, industrial intensity and energy intensity are the critical driving forces for total carbon emission. By investigating the critical driving forces and their contributions in critical provinces, this paper aims to provide theoretical foundations for decarbonizing Power Sector.
Stephen J Lee - One of the best experts on this subject based on the ideXlab platform.
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no covid 19 climate silver lining in the us Power Sector
Nature Communications, 2021Co-Authors: Max Luke, Priyanshi Somani, Turner Cotterman, Dhruv Suri, Stephen J LeeAbstract:Recent studies conclude that the global coronavirus (COVID-19) pandemic decreased Power Sector CO2 emissions globally and in the United States. In this paper, we analyze the statistical significance of CO2 emissions reductions in the U.S. Power Sector from March through December 2020. We use Gaussian process (GP) regression to assess whether CO2 emissions reductions would have occurred with reasonable probability in the absence of COVID-19 considering uncertainty due to factors unrelated to the pandemic and adjusting for weather, seasonality, and recent emissions trends. We find that monthly CO2 emissions reductions are only statistically significant in April and May 2020 considering hypothesis tests at 5% significance levels. Separately, we consider the potential impact of COVID-19 on coal-fired Power plant retirements through 2022. We find that only a small percentage of U.S. coal Power plants are at risk of retirement due to a possible COVID-19-related sustained reduction in electricity demand and prices. We observe and anticipate a return to pre-COVID-19 CO2 emissions in the U.S. Power Sector. COVID-19 has decreased Power Sector emissions globally and in the United States. Here the authors assess whether such reductions would have occurred in the United States in the absence of the pandemic, as well as the potential impact of COVID-19 on coal-fired Power plant retirements through 2022.
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no covid 19 climate silver lining in the us Power Sector
Research Papers in Economics, 2020Co-Authors: Max Luke, Priyanshi Somani, Turner Cotterman, Dhruv Suri, Stephen J LeeAbstract:Recent studies conclude that the global coronavirus (COVID-19) pandemic decreased Power Sector CO$_2$ emissions globally and in the United States. In this paper, we analyze the statistical significance of CO2 emissions reductions in the U.S. Power Sector from March through December 2020. We use Gaussian process (GP) regression to assess whether CO2 emissions reductions would have occurred with reasonable probability in the absence of COVID-19 considering uncertainty due to factors unrelated to the pandemic and adjusting for weather, seasonality, and recent emissions trends. We find that monthly CO2 emissions reductions are only statistically significant in April and May 2020 considering hypothesis tests at 5% significance levels. Separately, we consider the potential impact of COVID-19 on coal-fired Power plant retirements through 2022. We find that only a small percentage of U.S. coal Power plants are at risk of retirement due to a possible COVID-19-related sustained reduction in electricity demand and prices. We observe and anticipate a return to pre-COVID-19 CO2 emissions in the U.S. Power Sector.
