The treatment of domestic and industrial wastewater is one of the major sources of CH_4 in the Chinese waste sector. On the basis of statistical data and country-specific emission factors, using IPCC methodology, the ...The treatment of domestic and industrial wastewater is one of the major sources of CH_4 in the Chinese waste sector. On the basis of statistical data and country-specific emission factors, using IPCC methodology, the characteristics of CH_4 emissions from wastewater treatment in China were analyzed. The driving factors of CH_4 emissions were studied, and the emission trend and reduction potential were predicted and analyzed according to the current situation. Results show that in 2010, CH_4 emissions from the treatment of domestic and industrial wastewater were0.6110 Mt and 1.6237 Mt, respectively. Eight major industries account for more than 92% of emissions, and CH_4 emissions gradually increased from 2005 to 2010. From the controlling management scenario, we predict that in 2020, CH_4 emissions from the treatment of domestic and industrial wastewater will be 1.0136 Mt and 2.3393 Mt, respectively, and the reduction potential will be 0.0763 Mt and 0.2599 Mt, respectively.From 2010 to 2020, CH_4 emissions from the treatment of domestic and industrial wastewater will increase by 66% and 44%, respectively.展开更多
As an effective carrier of integrated clean energy,the microgrid has attracted wide attention.The randomness of renewable energies such as wind and solar power output brings a significant cost and impact on the econom...As an effective carrier of integrated clean energy,the microgrid has attracted wide attention.The randomness of renewable energies such as wind and solar power output brings a significant cost and impact on the economics and reliability of microgrids.This paper proposes an optimization scheme based on the distributionally robust optimization(DRO)model for a microgrid considering solar-wind correlation.Firstly,scenarios of wind and solar power output scenarios are generated based on non-parametric kernel density estimation and the Frank-Copula function;then the generated scenario results are reduced by K-means clustering;finally,the probability confidence interval of scenario distribution is constrained by 1-norm and∞-norm.The model is solved by a column-and-constraint generation algorithm.Experimental studies are conducted on a microgrid system in Jiangsu,China and the obtained scheduling solution turned out to be superior under wind and solar power uncertainties,which verifies the effectiveness of the proposed DRO model.展开更多
基金supported by the National Natural Science Foundation of China (41175137)the Climate Change Working Program of MEP in 2015 (CC(2015)-9-3)the Climate Change Project of Beijing in 2014 (ZHCKT4)
文摘The treatment of domestic and industrial wastewater is one of the major sources of CH_4 in the Chinese waste sector. On the basis of statistical data and country-specific emission factors, using IPCC methodology, the characteristics of CH_4 emissions from wastewater treatment in China were analyzed. The driving factors of CH_4 emissions were studied, and the emission trend and reduction potential were predicted and analyzed according to the current situation. Results show that in 2010, CH_4 emissions from the treatment of domestic and industrial wastewater were0.6110 Mt and 1.6237 Mt, respectively. Eight major industries account for more than 92% of emissions, and CH_4 emissions gradually increased from 2005 to 2010. From the controlling management scenario, we predict that in 2020, CH_4 emissions from the treatment of domestic and industrial wastewater will be 1.0136 Mt and 2.3393 Mt, respectively, and the reduction potential will be 0.0763 Mt and 0.2599 Mt, respectively.From 2010 to 2020, CH_4 emissions from the treatment of domestic and industrial wastewater will increase by 66% and 44%, respectively.
基金supported in part by the National Natural Science Foundation of China(51977127)in part by the ShanghaiMunicipal Science and in part by the Technology Commission(19020500800)“Shuguang Program”(20SG52)Shanghai Education Development Foundation and Shanghai Municipal Education Commission.
文摘As an effective carrier of integrated clean energy,the microgrid has attracted wide attention.The randomness of renewable energies such as wind and solar power output brings a significant cost and impact on the economics and reliability of microgrids.This paper proposes an optimization scheme based on the distributionally robust optimization(DRO)model for a microgrid considering solar-wind correlation.Firstly,scenarios of wind and solar power output scenarios are generated based on non-parametric kernel density estimation and the Frank-Copula function;then the generated scenario results are reduced by K-means clustering;finally,the probability confidence interval of scenario distribution is constrained by 1-norm and∞-norm.The model is solved by a column-and-constraint generation algorithm.Experimental studies are conducted on a microgrid system in Jiangsu,China and the obtained scheduling solution turned out to be superior under wind and solar power uncertainties,which verifies the effectiveness of the proposed DRO model.
