The Yangtze River Delta（YRD） region is one of the most prosperous and densely populated regions in China and is facing tremendous pressure to mitigate vehicle emissions and improve air quality.Our assessment has rev...The Yangtze River Delta（YRD） region is one of the most prosperous and densely populated regions in China and is facing tremendous pressure to mitigate vehicle emissions and improve air quality.Our assessment has revealed that mitigating vehicle emissions of NOx would be more difficult than reducing the emissions of other major vehicular pollutants（e.g.,CO,HC and PM_（2.5）） in the YRD region.Even in Shanghai,where the emission control implemented are more stringent than in Jiangsu and Zhejiang,we observed little to no reduction in NOx emissions from 2000 to 2010.Emission-reduction targets for HC,NOx and PM_（2.5） are determined using a response surface modeling tool for better air quality.We design city-specific emission control strategies for three vehicle-populated cities in the YRD region：Shanghai and Nanjing and Wuxi in Jiangsu.Our results indicate that even if stringent emission control consisting of the Euro 6/VI standards,the limitation of vehicle population and usage,and the scrappage of older vehicles is applied,Nanjing and Wuxi will not be able to meet the NOx emissions target by 2020.Therefore,additional control measures are proposed for Nanjing and Wuxi to further mitigate NOx emissions from heavy-duty diesel vehicles.展开更多
【目的】为提升混合储能系统(hybrid energy storage system,HESS)辅助火电机组响应自动发电控制(automatic generation control,AGC)指令时的调节性能,提出一种基于随机模型预测控制(stochastic model predictive control,SMPC)的火储...【目的】为提升混合储能系统(hybrid energy storage system,HESS)辅助火电机组响应自动发电控制(automatic generation control,AGC)指令时的调节性能,提出一种基于随机模型预测控制(stochastic model predictive control,SMPC)的火储联合功率分配策略。【方法】首先,针对包括功率型储能钛酸锂电池与能量型储能磷酸铁锂电池构成的HESS系统,提出基于马尔科夫概率矩阵构建未来时段火电机组响应AGC指令的HESS功率需求模型,并引入自适应机制实时动态修正状态转移概率,以提升AGC指令波动下的预测精度;其次,提出一种基于概率阈值与分层抽样相结合的场景树生成方法用于将自适应马尔科夫模型输出的概率分布转化为可用于优化的有限场景集合,描述多场景下功率需求预测的不确定性;最后,在上述框架基础上构建随机预测控制器,实现火电机组和HESS的功率最优分配。【结果】仿真实验表明,所提策略在调节性能上优于不考虑功率预测的传统联合调频策略以及未引入动态修正的由静态转移概率矩阵构建的SMPC策略,其性能指标Kp分别提升14.1%和7.5%。【结论】该策略有效提升了火电机组与HESS的协同调节性能,具有较强的应用潜力。未来可以进一步优化模型,提升其在实际应用中的鲁棒性和适应性,推动该技术的实际落地。展开更多
To improve flood control efficiency and increase urban resilience to flooding,the impacts of forest type change on flood control in the upper reach of the Tingjiang River(URTR) were evaluated by a modified model based...To improve flood control efficiency and increase urban resilience to flooding,the impacts of forest type change on flood control in the upper reach of the Tingjiang River(URTR) were evaluated by a modified model based on the Soil Conservation Service curve number(SCS-CN) method. Parameters of the model were selected and determined according to the comprehensive analysis of model evaluation indexes. The first simulation of forest reconstruction scenario,namely a coniferous forest covering 59.35km^2 is replaced by a broad-leaved forest showed no significant impact on the flood reduction in the URTR. The second simulation was added with 61.75km^2 bamboo forest replaced by broad-leaved forest,the reduction of flood peak discharge and flood volume could be improved significantly. Specifically,flood peak discharge of 10-year return period event was reduced to 7-year event,and the reduction rate of small flood was 21%-28%. Moreover,the flood volume was reduced by 9%-14% and 18%-35% for moderate floods and small floods,respectively. The resultssuggest that the bamboo forest reconstruction is an effective control solution for small to moderate flood in the URTR,the effect of forest conversion on flood volume is increasingly reduced as the rainfall amount increases to more extreme magnitude. Using a hydrological model with scenarios analysis is an effective simulation approach in investigating the relationship between forest type change and flood control. This method would provide reliable support for flood control and disaster mitigation in mountainous cities.展开更多
基金sponsored by the National Science&Technology Pillar Program of China(No.2013BAC13B03)the National Natural Science Foundation of China(Nos.51322804 and 91544222)
文摘The Yangtze River Delta（YRD） region is one of the most prosperous and densely populated regions in China and is facing tremendous pressure to mitigate vehicle emissions and improve air quality.Our assessment has revealed that mitigating vehicle emissions of NOx would be more difficult than reducing the emissions of other major vehicular pollutants（e.g.,CO,HC and PM_（2.5）） in the YRD region.Even in Shanghai,where the emission control implemented are more stringent than in Jiangsu and Zhejiang,we observed little to no reduction in NOx emissions from 2000 to 2010.Emission-reduction targets for HC,NOx and PM_（2.5） are determined using a response surface modeling tool for better air quality.We design city-specific emission control strategies for three vehicle-populated cities in the YRD region：Shanghai and Nanjing and Wuxi in Jiangsu.Our results indicate that even if stringent emission control consisting of the Euro 6/VI standards,the limitation of vehicle population and usage,and the scrappage of older vehicles is applied,Nanjing and Wuxi will not be able to meet the NOx emissions target by 2020.Therefore,additional control measures are proposed for Nanjing and Wuxi to further mitigate NOx emissions from heavy-duty diesel vehicles.
文摘【目的】为提升混合储能系统(hybrid energy storage system,HESS)辅助火电机组响应自动发电控制(automatic generation control,AGC)指令时的调节性能,提出一种基于随机模型预测控制(stochastic model predictive control,SMPC)的火储联合功率分配策略。【方法】首先,针对包括功率型储能钛酸锂电池与能量型储能磷酸铁锂电池构成的HESS系统,提出基于马尔科夫概率矩阵构建未来时段火电机组响应AGC指令的HESS功率需求模型,并引入自适应机制实时动态修正状态转移概率,以提升AGC指令波动下的预测精度;其次,提出一种基于概率阈值与分层抽样相结合的场景树生成方法用于将自适应马尔科夫模型输出的概率分布转化为可用于优化的有限场景集合,描述多场景下功率需求预测的不确定性;最后,在上述框架基础上构建随机预测控制器,实现火电机组和HESS的功率最优分配。【结果】仿真实验表明,所提策略在调节性能上优于不考虑功率预测的传统联合调频策略以及未引入动态修正的由静态转移概率矩阵构建的SMPC策略,其性能指标Kp分别提升14.1%和7.5%。【结论】该策略有效提升了火电机组与HESS的协同调节性能,具有较强的应用潜力。未来可以进一步优化模型,提升其在实际应用中的鲁棒性和适应性,推动该技术的实际落地。
基金funded by the National Natural Science Foundation of China (Grants No.51278239)
文摘To improve flood control efficiency and increase urban resilience to flooding,the impacts of forest type change on flood control in the upper reach of the Tingjiang River(URTR) were evaluated by a modified model based on the Soil Conservation Service curve number(SCS-CN) method. Parameters of the model were selected and determined according to the comprehensive analysis of model evaluation indexes. The first simulation of forest reconstruction scenario,namely a coniferous forest covering 59.35km^2 is replaced by a broad-leaved forest showed no significant impact on the flood reduction in the URTR. The second simulation was added with 61.75km^2 bamboo forest replaced by broad-leaved forest,the reduction of flood peak discharge and flood volume could be improved significantly. Specifically,flood peak discharge of 10-year return period event was reduced to 7-year event,and the reduction rate of small flood was 21%-28%. Moreover,the flood volume was reduced by 9%-14% and 18%-35% for moderate floods and small floods,respectively. The resultssuggest that the bamboo forest reconstruction is an effective control solution for small to moderate flood in the URTR,the effect of forest conversion on flood volume is increasingly reduced as the rainfall amount increases to more extreme magnitude. Using a hydrological model with scenarios analysis is an effective simulation approach in investigating the relationship between forest type change and flood control. This method would provide reliable support for flood control and disaster mitigation in mountainous cities.
