Optimization On Cooperative Control For Metro Trains For Energy Saving

The power consumption in metro systems is growing rapidly in response to the increment of operation mileage in the major cities of China.More than half of the total power consumption of metro systems is used for train operation.Therefore,reducing energy consumption of train operation is crucial for the metro energy conservation.In daily operations,regenerative energy by braking is remarkable due to train headway is small and trains start and stop frequently as the inter-station distances are relatively short.Therefore,improving the utilization of regenerative energy becomes a hot topic in recent years.Previous researches on the utilization of regenerative energy mostly focus on timetable optimization.However,metro train operations are often disturbed by external factors.In such cases,train movements would deviate from the original timetable,which would deteriorate the utilization of regenerative energy.Therefore,this paper establishes an online rolling optimization model on multiple-train cooperative control for energy saving.Case studies are conducted to verify the effectiveness of the proposed model.Main contents of this study are as follows:(1)Two typical strategies on energy-saving control for metro trains under fixed time are analyzed.The first one is the Four-phase Control Strategy proven by the optimal control theory,where the energy-efficient train movements consist of four phases:full motoring,constant speed control,coasting and full braking.The other one is to use Coasting Control instead of braking for energy reduction.Then,this paper analyzes these two control strategies in different lines with varied schedule time.Case studies indicates that the energy consumption of train traction and the recoverable regenerative energy under the Four-phase Control Strategy is less than that of Coasting Control Strategy,and computing efficiency of the Four-phase Control Strategy is higher than that of the Coast Control Strategy.(2)This paper proposes a coordinated control model on multiple train control,aiming at minimize the total energy consumption of train movements.A co-evolutionary algorithm combining genetic algorithm and simulated annealing is designed to solve the proposed model.Case studies indicate that,the energy can be reduced by 5.09%in comparison with separately control without disruptions.In the case of perturbations,the energy consumption can be reduced by adjusting the dwell time and choosing the control scheme so that the optimal rate can reach 34.36%.(3)Due to the use of regenerative energy,minimizing the energy consumption of a single train does not necessarily lead to the minimization of system energy consumption across all trains.On the basis of the traditional Four-Phase Control Strategy,this paper proposes a promoted control scheme on optimizing the traction rate and braking rate in the corresponding phases,which in order to extend the overlapping time of traction and braking of different trains in the same power supply interval.Case studies show that the energy can be reduced by 5.94%,comparing to the traditional Four-Phase Control Strategy.