In the field of rail transit,the UK Department of Transport stated that it will realize a comprehensive transformation of UK railways by 2050,abandoning traditional diesel trains and upgrading them to new environmenta...In the field of rail transit,the UK Department of Transport stated that it will realize a comprehensive transformation of UK railways by 2050,abandoning traditional diesel trains and upgrading them to new environmentally friendly trains.The current mainstream upgrade methods are electrification and hydrogen fuel cells.Comprehensive upgrades are costly,and choosing the optimal upgrade method for trams and mainline railways is critical.Without a sensitivity analysis,it is difficult for us to determine the influence relationship between each parameter and cost,resulting in a waste of cost when choosing a line reconstruction method.In addition,by analyzing the sensitivity of different parameters to the cost,the primary optimization direction can be determined to reduce the cost.Global higher-order sensitivity analysis enables quantification of parameter interactions,showing non-additive effects between parameters.This paper selects the main parameters that affect the retrofit cost and analyzes the retrofit cost of the two upgrade methods in the case of trams and mainline railways through local and global sensitivity analysis methods.The results of the analysis show that,given the current UK rail system,it is more economical to choose electric trams and hydrogen mainline trains.For trams,the speed at which the train travels has the greatest impact on the final cost.Through the sensitivity analysis,this paper provides an effective data reference for the current railway upgrading and reconstruction plan and provides a theoretical basis for the next step of train parameter optimization.展开更多
Achieving a low or zero carbon target is to reduce energy demand and improve energy efficiency of electricity consumers.One of the main electricity consumers in power systems is heating,ventilation,and air conditionin...Achieving a low or zero carbon target is to reduce energy demand and improve energy efficiency of electricity consumers.One of the main electricity consumers in power systems is heating,ventilation,and air conditioning systems(HVACs),which cost around 30%of the total usage in commercial buildings.This paper investigates the scheduling problem of HVAC energy consumption taking into account two uncertainties:outdoor temperature and human activities.The distributionally robust optimization approach(DROA)is extended to deal with these two uncertainties which are modeled by the proposed disjointed layered ambiguity sets according to historical data.Based on the proposed DROA method,the distributionally robust chance constraints(DRCCs)will be formulated as a nonlinear optimization problem,converted into a linear optimization problem using duality theorem and solved using SeDuMi solver.Simulation results are used to compare with existing methods,which shows the proposed DROA can decrease 2.81%and 0.14%of the electricity cost in comparison with traditional RO method and DROA based on a nest layered ambiguity set,respectively.Also,the proposed DROA decreases the number and maximum of violations from the comfort level of users.The multi-zone HVAC system model is used in the case study to verify the proposed DROA with the disjointed ambiguity set.The consecutive simulation results illustrate the proposed DROA approach can provide stable performance in a three-day scheduling period.展开更多
文摘In the field of rail transit,the UK Department of Transport stated that it will realize a comprehensive transformation of UK railways by 2050,abandoning traditional diesel trains and upgrading them to new environmentally friendly trains.The current mainstream upgrade methods are electrification and hydrogen fuel cells.Comprehensive upgrades are costly,and choosing the optimal upgrade method for trams and mainline railways is critical.Without a sensitivity analysis,it is difficult for us to determine the influence relationship between each parameter and cost,resulting in a waste of cost when choosing a line reconstruction method.In addition,by analyzing the sensitivity of different parameters to the cost,the primary optimization direction can be determined to reduce the cost.Global higher-order sensitivity analysis enables quantification of parameter interactions,showing non-additive effects between parameters.This paper selects the main parameters that affect the retrofit cost and analyzes the retrofit cost of the two upgrade methods in the case of trams and mainline railways through local and global sensitivity analysis methods.The results of the analysis show that,given the current UK rail system,it is more economical to choose electric trams and hydrogen mainline trains.For trams,the speed at which the train travels has the greatest impact on the final cost.Through the sensitivity analysis,this paper provides an effective data reference for the current railway upgrading and reconstruction plan and provides a theoretical basis for the next step of train parameter optimization.
文摘Achieving a low or zero carbon target is to reduce energy demand and improve energy efficiency of electricity consumers.One of the main electricity consumers in power systems is heating,ventilation,and air conditioning systems(HVACs),which cost around 30%of the total usage in commercial buildings.This paper investigates the scheduling problem of HVAC energy consumption taking into account two uncertainties:outdoor temperature and human activities.The distributionally robust optimization approach(DROA)is extended to deal with these two uncertainties which are modeled by the proposed disjointed layered ambiguity sets according to historical data.Based on the proposed DROA method,the distributionally robust chance constraints(DRCCs)will be formulated as a nonlinear optimization problem,converted into a linear optimization problem using duality theorem and solved using SeDuMi solver.Simulation results are used to compare with existing methods,which shows the proposed DROA can decrease 2.81%and 0.14%of the electricity cost in comparison with traditional RO method and DROA based on a nest layered ambiguity set,respectively.Also,the proposed DROA decreases the number and maximum of violations from the comfort level of users.The multi-zone HVAC system model is used in the case study to verify the proposed DROA with the disjointed ambiguity set.The consecutive simulation results illustrate the proposed DROA approach can provide stable performance in a three-day scheduling period.
