With the development of distributed photovoltaic energy in mining areas,the increasing proportion of new energy integration will gradually drive the structural transformation of coal mine parks into industrial active ...With the development of distributed photovoltaic energy in mining areas,the increasing proportion of new energy integration will gradually drive the structural transformation of coal mine parks into industrial active distribution networks.This paper takes a coal mine in Shaanxi Province as an empirical research subject,employing a multi-spatial hierarchical analysis method to systematically analyze the electricity usage characteristics across different spatial levels.It innovatively proposes a power line loss correction method for multi-level electrical equipment,effectively balancing the metering deviations of line losses between levels.Based on two types of carbon emission factors,it achieves precise evaluation of indirect carbon emissions from electricity usage in different levels of equipment or energy units.When calculating indirect carbon emissions from electricity using static carbon emission factors,the measured values show a positive correlation with peak electricity load.As the proportion of renewable photovoltaic power integration in industrial active distribution networks increases,the system’s indirect carbon emission factors exhibit a periodic decreasing trend.After adopting dynamic indirect carbon emission factors for accounting,the indirect carbon emissions from electricity in the first consumption level can be reduced by 31%-55%,while the overall plant-wide indirect carbon emissions decrease by 29068.94 kgCO_(2)/d,a reduction of approximately 40%.For the second consumption level in industrial production areas,indirect carbon emissions from electricity can be reduced by 5%-83%,with overall industrial park-wide indirect carbon emissions decreasing by 7376.48 kgCO_(2)/d,a reduction of about 31%.It is recommended to use advanced equipment and energy-saving technologies to suppress technical line losses in coal mine power supply systems and improve energy efficiency.Promoting the coordinated application of renewable energy and energy storage technologies can expand the scale of stable and reliable renewable energy supply,effectively reducing indirect carbon emissions from electricity.展开更多
Traditional demand response(DR)programs for energy-intensive industries(EIIs)primarily rely on electricity price signals and often overlook carbon emission factors,limiting their effectiveness in supporting lowcarbon ...Traditional demand response(DR)programs for energy-intensive industries(EIIs)primarily rely on electricity price signals and often overlook carbon emission factors,limiting their effectiveness in supporting lowcarbon transitions.To address this challenge,this paper proposes an electricity–carbon integratedDR strategy based on a bi-level collaborative optimization framework that coordinates the interaction between the grid and EIIs.At the upper level,the grid operatorminimizes generation and curtailment costs by optimizing unit commitment while determining real-time electricity prices and dynamic carbon emission factors.At the lower level,EIIs respond to these dual signals by minimizing their combined electricity and carbon trading costs,considering their participation in medium-and long-term electricity markets,day-ahead spot markets,and carbon emissions trading schemes.The model accounts for direct and indirect carbon emissions,distributed photovoltaic(PV)generation,and battery energy storage systems.This interaction is structured as a Stackelberg game,where the grid acts as the leader and EIIs as followers,enabling dynamic feedback between pricing signals and load response.Simulation studies on an improved IEEE 30-bus system,with a cement plant as a representative user form EIIs,show that the proposed strategy reduces user-side carbon emissions by 7.95% and grid-side generation cost by 4.66%,though the user’s energy cost increases by 7.80% due to carbon trading.Theresults confirmthat the joint guidance of electricity and carbon prices effectively reshapes user load profiles,encourages peak shaving,and improves PV utilization.This coordinated approach not only achieves emission reduction and cost efficiency but also offers a theoretical and practical foundation for integrating carbon pricing into demand-side energy management in future low-carbon power systems.展开更多
Context:East Asia is a crucial region in the global methane(CH4)budget,with significant contributions from the livestock sector.However,the long-term trend and spatial pattern of CH4 emissions from livestock in this r...Context:East Asia is a crucial region in the global methane(CH4)budget,with significant contributions from the livestock sector.However,the long-term trend and spatial pattern of CH4 emissions from livestock in this region have not been fully assessed.Methods:Here,we estimate CH4 emissions from 10 categories of livestock in East Asia during 1961-2019 following the Tier 2 approaches suggested by the 2019 Refinement to the IPCC 2006 Guidelines.Results:livestock-sourced CH4 emission in 2019 was 13.22[11.42-15.01](mean[minimum%maximum of 95-confidence interval]Tg CH4 yr-1,accounting for an increase of 231%since 1961.The contribution of slaughtered populations to total emissions increased from 3%in 1961 to 24%in 2019.Spatially,the emission hotspots were mostly distributed in eastern China,South Korea,and parts of Japan,but they tend to shift northward after 2000.Conclusion:It is necessary to use dynamic emission factors and include slaughtered populations in the estimation of livestock CH4 emissions.Regions including Northern China,Mongolia,and South Korea deserve more attention in future CH4 mitigation efforts.展开更多
Context:East Asia is a crucial region in the global methane(CH4)budget,with significant contributions from the livestock sector.However,the long-term trend and spatial pattern of CH4 emissions from livestock in this r...Context:East Asia is a crucial region in the global methane(CH4)budget,with significant contributions from the livestock sector.However,the long-term trend and spatial pattern of CH4 emissions from livestock in this region have not been fully assessed.Methods:Here,we estimate CH4 emissions from 10 categories of livestock in East Asia during1961-2019 following the Tier 2 approaches suggested by the 2019 Refinement to the IPCC2006 Guidelines.Results:livestock-sourced CH4 emission in 2019 was 13.22[11,42-15.01](mean[minimum%maximum of 95-confidence interval]Tg CH4 yr-1,accounting for an increase of 231%since1961.The contribution of slaughtered populations to total emissions increased from 3%in1961 to 24%in 2019.Spatially,the emission hotspots were mostly distributed in eastern China,South Korea,and parts of Japan,but they tend to shift northward after 2000.Conclusion:It is necessary to use dynamic emission factors and include slaughtered populations in the estimatio n of livestock CH4 emissions.Regions including Northern China,Mongolia,and South Korea deserve more attention in future CH4 mitigation efforts.展开更多
基金supported by CHN Energy Investment Group(GJNY-23-138)。
文摘With the development of distributed photovoltaic energy in mining areas,the increasing proportion of new energy integration will gradually drive the structural transformation of coal mine parks into industrial active distribution networks.This paper takes a coal mine in Shaanxi Province as an empirical research subject,employing a multi-spatial hierarchical analysis method to systematically analyze the electricity usage characteristics across different spatial levels.It innovatively proposes a power line loss correction method for multi-level electrical equipment,effectively balancing the metering deviations of line losses between levels.Based on two types of carbon emission factors,it achieves precise evaluation of indirect carbon emissions from electricity usage in different levels of equipment or energy units.When calculating indirect carbon emissions from electricity using static carbon emission factors,the measured values show a positive correlation with peak electricity load.As the proportion of renewable photovoltaic power integration in industrial active distribution networks increases,the system’s indirect carbon emission factors exhibit a periodic decreasing trend.After adopting dynamic indirect carbon emission factors for accounting,the indirect carbon emissions from electricity in the first consumption level can be reduced by 31%-55%,while the overall plant-wide indirect carbon emissions decrease by 29068.94 kgCO_(2)/d,a reduction of approximately 40%.For the second consumption level in industrial production areas,indirect carbon emissions from electricity can be reduced by 5%-83%,with overall industrial park-wide indirect carbon emissions decreasing by 7376.48 kgCO_(2)/d,a reduction of about 31%.It is recommended to use advanced equipment and energy-saving technologies to suppress technical line losses in coal mine power supply systems and improve energy efficiency.Promoting the coordinated application of renewable energy and energy storage technologies can expand the scale of stable and reliable renewable energy supply,effectively reducing indirect carbon emissions from electricity.
基金supported by the Science and Technology Project of Yunnan Power Grid Co.,Ltd.under Grant No.YNKJXM20222410.
文摘Traditional demand response(DR)programs for energy-intensive industries(EIIs)primarily rely on electricity price signals and often overlook carbon emission factors,limiting their effectiveness in supporting lowcarbon transitions.To address this challenge,this paper proposes an electricity–carbon integratedDR strategy based on a bi-level collaborative optimization framework that coordinates the interaction between the grid and EIIs.At the upper level,the grid operatorminimizes generation and curtailment costs by optimizing unit commitment while determining real-time electricity prices and dynamic carbon emission factors.At the lower level,EIIs respond to these dual signals by minimizing their combined electricity and carbon trading costs,considering their participation in medium-and long-term electricity markets,day-ahead spot markets,and carbon emissions trading schemes.The model accounts for direct and indirect carbon emissions,distributed photovoltaic(PV)generation,and battery energy storage systems.This interaction is structured as a Stackelberg game,where the grid acts as the leader and EIIs as followers,enabling dynamic feedback between pricing signals and load response.Simulation studies on an improved IEEE 30-bus system,with a cement plant as a representative user form EIIs,show that the proposed strategy reduces user-side carbon emissions by 7.95% and grid-side generation cost by 4.66%,though the user’s energy cost increases by 7.80% due to carbon trading.Theresults confirmthat the joint guidance of electricity and carbon prices effectively reshapes user load profiles,encourages peak shaving,and improves PV utilization.This coordinated approach not only achieves emission reduction and cost efficiency but also offers a theoretical and practical foundation for integrating carbon pricing into demand-side energy management in future low-carbon power systems.
基金This research was supported in part by the National Key R&D Program of China(2017YFA0604702)CAS STS Program(KFJ-STS-ZDTP-010-05)+3 种基金SKLURE Grant(SKLURE 2017-1-6)China Scholarship Council(201904910499)H.T.and S.P.were supported by the US National Science Foundation(1903722)Andrew Carnegie Fellowship(G-F-19-56910).
文摘Context:East Asia is a crucial region in the global methane(CH4)budget,with significant contributions from the livestock sector.However,the long-term trend and spatial pattern of CH4 emissions from livestock in this region have not been fully assessed.Methods:Here,we estimate CH4 emissions from 10 categories of livestock in East Asia during 1961-2019 following the Tier 2 approaches suggested by the 2019 Refinement to the IPCC 2006 Guidelines.Results:livestock-sourced CH4 emission in 2019 was 13.22[11.42-15.01](mean[minimum%maximum of 95-confidence interval]Tg CH4 yr-1,accounting for an increase of 231%since 1961.The contribution of slaughtered populations to total emissions increased from 3%in 1961 to 24%in 2019.Spatially,the emission hotspots were mostly distributed in eastern China,South Korea,and parts of Japan,but they tend to shift northward after 2000.Conclusion:It is necessary to use dynamic emission factors and include slaughtered populations in the estimation of livestock CH4 emissions.Regions including Northern China,Mongolia,and South Korea deserve more attention in future CH4 mitigation efforts.
基金supported in part by the National Key R&D Program of China(2017YFA0604702)CAS STS Program(KFJ-STS-ZDTP-010-05)+3 种基金SKLURE Grant(SKLURE 2017-1-6)China Scholarship Council(201904910499)supported by the US National Science Foundation(1903722)Andrew Carnegie Fellowship(G-F-19-56910)
文摘Context:East Asia is a crucial region in the global methane(CH4)budget,with significant contributions from the livestock sector.However,the long-term trend and spatial pattern of CH4 emissions from livestock in this region have not been fully assessed.Methods:Here,we estimate CH4 emissions from 10 categories of livestock in East Asia during1961-2019 following the Tier 2 approaches suggested by the 2019 Refinement to the IPCC2006 Guidelines.Results:livestock-sourced CH4 emission in 2019 was 13.22[11,42-15.01](mean[minimum%maximum of 95-confidence interval]Tg CH4 yr-1,accounting for an increase of 231%since1961.The contribution of slaughtered populations to total emissions increased from 3%in1961 to 24%in 2019.Spatially,the emission hotspots were mostly distributed in eastern China,South Korea,and parts of Japan,but they tend to shift northward after 2000.Conclusion:It is necessary to use dynamic emission factors and include slaughtered populations in the estimatio n of livestock CH4 emissions.Regions including Northern China,Mongolia,and South Korea deserve more attention in future CH4 mitigation efforts.
