Based on the study of the relationship between structure and feedback of China’s natural gas demand system, this paper establishes a system dynamics model. In order to simulate the total demand and consumption struct...Based on the study of the relationship between structure and feedback of China’s natural gas demand system, this paper establishes a system dynamics model. In order to simulate the total demand and consumption structure of natural gas in China, we set up seven scenarios by changing some of the parameters of the model. The results showed that the total demand of natural gas would increase steadily year by year and reach in the range from 3600 to 4500 billion cubic meters in 2035. Furthermore, in terms of consumption structure, urban gas consumption would still be the largest term, followed by the gas consumption as industrial fuel, gas power generation and natural gas chemical industry. In addition, compared with the population growth, economic development still plays a dominant role in the natural gas demand growth, the impact of urbanization on urban gas consumption is significant, and the promotion of natural gas utilization technology can effectively reduce the total consumption of natural gas.展开更多
With the popularization of microgrid construction and the connection of renewable energy sources to the power system,the problem of source and load uncertainty faced by the coordinated operation of multi-microgrid is ...With the popularization of microgrid construction and the connection of renewable energy sources to the power system,the problem of source and load uncertainty faced by the coordinated operation of multi-microgrid is becoming increasingly prominent,and the accuracy of typical scenario predictions is low.In order to improve the accuracy of scenario prediction under source and load uncertainty,this paper proposes a typical scenario identification model based on random forests and order parameters.Firstly,a method for ordinal parameter identification and quantification is provided for the coordinated operating mode of multi-microgrids,taking into account source-load uncertainty.Secondly,the dynamic change characteristics of the order parameters of the daily load curve,wind and solar curve,and load curve of typical scenarios are statistically analyzed to identify the key order parameters that have the most significant impact on the uncertainty of the load.Then,the order parameters and seasonal distribution are used as features to train a random forest classification model to achieve efficient scenario prediction.Finally,the simulation of actual data from a provincial distribution network shows that the proposed method can accurately classify typical scenarios with an accuracy rate of 92.7%.Additionally,sensitivity analysis is conducted to assess how changes in uncertainty levels affect the importance of each order parameter,allowing for adaptive uncertainty mitigation strategies.展开更多
Against the backdrop of the dual carbon goals,the papermaking industry in China faces significant pressure to reduce emissions and lower carbon intensity.Based on historical data of energy consumption in the pulp and ...Against the backdrop of the dual carbon goals,the papermaking industry in China faces significant pressure to reduce emissions and lower carbon intensity.Based on historical data of energy consumption in the pulp and paper industry in China from 2000 to 2020,this study analyzed the current status of paper production and energy consumption in China.Two methods were employed to predict the growth trend of paper production in China,and three carbon dioxide emission accounting methods were compared.The study used an accounting method based on the industry’s overall energy consumption and predicted the carbon dioxide(CO_(2))emissions of the Chinese papermaking industry from 2021 to 2060 under three scenarios.The study identified the timing for achieving carbon peak and proposed the measures for carbon neutrality.The results indicated that:(1)the CO_(2)emissions of the Chinese papermaking industry in 2020 were 111.98 million tons.(2)Under low-demand,high-demand,and baseline scenarios,the papermaking industry is expected to achieve carbon peak during the“14th Five-Year Plan”period.(3)In 2060,under the three scenarios,CO_(2)emissions from the papermaking industry will decrease by 11%-31%compared to the baseline year.However,there will still be emissions of 72-93 million tons,requiring reductions in fossil energy consumption at the source,increasing forestry carbon sequestration and utilization of Carbon Capture,Utilization and Storage(CCUS)technology,and taking measures such as carbon trading to achieve carbon neutrality.展开更多
Promoting industrial carbon reduction is an inevitable step for achieving the Chinese carbon peak and neutrality targets.Based on the industrial energy consumption data of Shaanxi Province from 2011 to 2020,this study...Promoting industrial carbon reduction is an inevitable step for achieving the Chinese carbon peak and neutrality targets.Based on the industrial energy consumption data of Shaanxi Province from 2011 to 2020,this study uses the IPCC calculation method to calculate the industrial carbon emissions in Shaanxi Province.The prediction model for industrial carbon emissions in Shaanxi Province was constructed based on the STIRPAT model from three aspects:population,economy,and technology.By setting three scenario models,the industrial carbon emissions from 2021 to 2035 and the time to achieve peak carbon neutrality were then predicted.The results show that the industry in Shaanxi Province cannot achieve a carbon peak under the baseline scenario,although it can achieve carbon peaking in 2030 under a low-carbon scenario or in 2025 under an enhanced low-carbon scenario.The predicted carbon peak values are 209.11 million t and 188.36 million t,respectively.Based on the results of this study,four policy recommendations are proposed:(1)strengthen publicity and education efforts to increase public participation in energy conservation and emission reduction;(2)promote the green transformation of industry and develop a green economy,including the active development of energy-saving and emission reduction technologies;(3)accelerate the implementation of industrial carbon reduction;and(4)promote the development and utilization of clean energy and increase efforts to adjust the energy structure.展开更多
Intergovernmental Panel on Climate Change(IPCC)in 2001 reported that the Earth air temperature would rise by 1.4-5.8℃and 2.5℃on average by the year 2100.China re-gional climate model results also showed that the air...Intergovernmental Panel on Climate Change(IPCC)in 2001 reported that the Earth air temperature would rise by 1.4-5.8℃and 2.5℃on average by the year 2100.China re-gional climate model results also showed that the air temperature on the Qinghai-Tibet Plateau(QTP)would increase by 2.2-2.6℃in the next 50 years.A numerical permafrost model was developed to predict the changes of permafrost distribution on the QTP over the next 50 and 100 years under the two climatic warming scenarios,i.e.0.02℃/a,the lower value of IPCC’s estima-tion,and 0.052℃/a,the higher value predicted by Qin et al.Simulation results show that(i)in the case of 0.02℃/a air-temperature rise,permafrost area on the QTP will shrink about 8.8%in the next 50 years,and high temperature permafrost with mean annual ground temperature(MAGT)higher than?0.11℃may turn into seasonal frozen soils.In the next 100 years,perma-frost with MAGT higher than?0.5℃will disappear and the permafrost area will shrink up to 13.4%.(ii)In the case of 0.052℃/a air-temperature rise,permafrost area on the QTP will reduce about 13.5%after 50 years.More remarkable degradation will take place after 100 years,and permafrost area will reduce about 46%.Permafrost with MAGT higher than?2℃will turn into seasonal frozen soils and even unfrozen soils.展开更多
基金financially supported by the National Natural Science Foundation of China (Grant Nos. 71273021 and 7167030506)
文摘Based on the study of the relationship between structure and feedback of China’s natural gas demand system, this paper establishes a system dynamics model. In order to simulate the total demand and consumption structure of natural gas in China, we set up seven scenarios by changing some of the parameters of the model. The results showed that the total demand of natural gas would increase steadily year by year and reach in the range from 3600 to 4500 billion cubic meters in 2035. Furthermore, in terms of consumption structure, urban gas consumption would still be the largest term, followed by the gas consumption as industrial fuel, gas power generation and natural gas chemical industry. In addition, compared with the population growth, economic development still plays a dominant role in the natural gas demand growth, the impact of urbanization on urban gas consumption is significant, and the promotion of natural gas utilization technology can effectively reduce the total consumption of natural gas.
基金supported by Science and Technology Project Managed by the State Grid Jiangsu Electric Power Co.,Ltd.(No.J2024163).
文摘With the popularization of microgrid construction and the connection of renewable energy sources to the power system,the problem of source and load uncertainty faced by the coordinated operation of multi-microgrid is becoming increasingly prominent,and the accuracy of typical scenario predictions is low.In order to improve the accuracy of scenario prediction under source and load uncertainty,this paper proposes a typical scenario identification model based on random forests and order parameters.Firstly,a method for ordinal parameter identification and quantification is provided for the coordinated operating mode of multi-microgrids,taking into account source-load uncertainty.Secondly,the dynamic change characteristics of the order parameters of the daily load curve,wind and solar curve,and load curve of typical scenarios are statistically analyzed to identify the key order parameters that have the most significant impact on the uncertainty of the load.Then,the order parameters and seasonal distribution are used as features to train a random forest classification model to achieve efficient scenario prediction.Finally,the simulation of actual data from a provincial distribution network shows that the proposed method can accurately classify typical scenarios with an accuracy rate of 92.7%.Additionally,sensitivity analysis is conducted to assess how changes in uncertainty levels affect the importance of each order parameter,allowing for adaptive uncertainty mitigation strategies.
文摘Against the backdrop of the dual carbon goals,the papermaking industry in China faces significant pressure to reduce emissions and lower carbon intensity.Based on historical data of energy consumption in the pulp and paper industry in China from 2000 to 2020,this study analyzed the current status of paper production and energy consumption in China.Two methods were employed to predict the growth trend of paper production in China,and three carbon dioxide emission accounting methods were compared.The study used an accounting method based on the industry’s overall energy consumption and predicted the carbon dioxide(CO_(2))emissions of the Chinese papermaking industry from 2021 to 2060 under three scenarios.The study identified the timing for achieving carbon peak and proposed the measures for carbon neutrality.The results indicated that:(1)the CO_(2)emissions of the Chinese papermaking industry in 2020 were 111.98 million tons.(2)Under low-demand,high-demand,and baseline scenarios,the papermaking industry is expected to achieve carbon peak during the“14th Five-Year Plan”period.(3)In 2060,under the three scenarios,CO_(2)emissions from the papermaking industry will decrease by 11%-31%compared to the baseline year.However,there will still be emissions of 72-93 million tons,requiring reductions in fossil energy consumption at the source,increasing forestry carbon sequestration and utilization of Carbon Capture,Utilization and Storage(CCUS)technology,and taking measures such as carbon trading to achieve carbon neutrality.
基金The Shaanxi Social Science Federation Foundation Project(2021HZ1118)The Shaanxi Normal University Graduate Student InnovationTeam Project(TD2020006Y).
文摘Promoting industrial carbon reduction is an inevitable step for achieving the Chinese carbon peak and neutrality targets.Based on the industrial energy consumption data of Shaanxi Province from 2011 to 2020,this study uses the IPCC calculation method to calculate the industrial carbon emissions in Shaanxi Province.The prediction model for industrial carbon emissions in Shaanxi Province was constructed based on the STIRPAT model from three aspects:population,economy,and technology.By setting three scenario models,the industrial carbon emissions from 2021 to 2035 and the time to achieve peak carbon neutrality were then predicted.The results show that the industry in Shaanxi Province cannot achieve a carbon peak under the baseline scenario,although it can achieve carbon peaking in 2030 under a low-carbon scenario or in 2025 under an enhanced low-carbon scenario.The predicted carbon peak values are 209.11 million t and 188.36 million t,respectively.Based on the results of this study,four policy recommendations are proposed:(1)strengthen publicity and education efforts to increase public participation in energy conservation and emission reduction;(2)promote the green transformation of industry and develop a green economy,including the active development of energy-saving and emission reduction technologies;(3)accelerate the implementation of industrial carbon reduction;and(4)promote the development and utilization of clean energy and increase efforts to adjust the energy structure.
基金the Knowledge Innovation Project of Chinese Academy of Sciences(CAS)(Grant No.KZCX1-SW-04)the Knowledge Innovation Project of CAREERI,CAS(Grant No.CACX200009)the Project of Ministry of Science and Technology of China(Grant No.G1998040812).
文摘Intergovernmental Panel on Climate Change(IPCC)in 2001 reported that the Earth air temperature would rise by 1.4-5.8℃and 2.5℃on average by the year 2100.China re-gional climate model results also showed that the air temperature on the Qinghai-Tibet Plateau(QTP)would increase by 2.2-2.6℃in the next 50 years.A numerical permafrost model was developed to predict the changes of permafrost distribution on the QTP over the next 50 and 100 years under the two climatic warming scenarios,i.e.0.02℃/a,the lower value of IPCC’s estima-tion,and 0.052℃/a,the higher value predicted by Qin et al.Simulation results show that(i)in the case of 0.02℃/a air-temperature rise,permafrost area on the QTP will shrink about 8.8%in the next 50 years,and high temperature permafrost with mean annual ground temperature(MAGT)higher than?0.11℃may turn into seasonal frozen soils.In the next 100 years,perma-frost with MAGT higher than?0.5℃will disappear and the permafrost area will shrink up to 13.4%.(ii)In the case of 0.052℃/a air-temperature rise,permafrost area on the QTP will reduce about 13.5%after 50 years.More remarkable degradation will take place after 100 years,and permafrost area will reduce about 46%.Permafrost with MAGT higher than?2℃will turn into seasonal frozen soils and even unfrozen soils.
