Researh On Optimal Configuration And Dispatching Strategy Of Dual Application Energy Storage And Double Layer In Electrified Railway

Electrified railroads have become an essential mode of travel for people,and China has become the first operating country of electrified railroads.In the electrified railroad,the problems of excessive peak power of traction load and incomplete regenerative braking energy recovery have been of great concern,both of which have an important impact on the electrified railroad economically and technically.In this paper,we introduce super capacitor energy storage and battery energy storage devices in the traction power supply system to address the problems of large peak power of traction load and incomplete regenerative braking energy recovery."peak shaving + valley filling + regenerative braking energy recovery" two different dual applications,give full play to the charging and discharging characteristics of energy storage,while reducing the maximum demand of the traction load and improve the capacity utilization of the traction transformer,thereby improving the economy of the electrified railroad.In order to better achieve the above objectives,this paper focuses on the capacity optimization configuration and scheduling strategy for energy storage devices under dual applications.The details of the study are as follows:In the "peak shaving + valley filling + energy storage arbitrage" battery capacity optimization allocation,a coordinated operation strategy for energy storage in dual applications and multiple scenarios is proposed to address the competing functional needs of energy storage devices,and a two-tier planning model is established to consider the configuration of energy storage devices and operation scheduling optimization.On the basis of the capacity configuration of the upper layer,the lower layer takes the maximum arbitrage value of energy storage as the target,and proposes a coordinated operation strategy for energy storage in dual applications and multiple scenarios,considering the time-sharing tariff policy,and the lower layer completes the optimization of energy storage charging and discharging under the guidance of this strategy,and gets the optimal charging and discharging power to feed back to the upper layer.The upper and lower layers interact with each other.Particle swarm algorithm is used to solve the model,which also solves the competing demand of energy storage for this dual application function.Finally,the proposed two-layer planning optimization model and the coordinated operation strategy of dual-application multi-scene energy storage are validated by comparison and simulation based on the measured historical traction load data,and the necessity of adding dual-application energy storage devices is verified by the analysis of the economic indexes of the comparison experiment.On the basis of the completed energy storage capacity allocation,a dual application scheduling strategy based on multiple time scales is proposed to further improve the economy of the electrified railroad.The day-ahead optimization scheduling section completes the dual application for the traction load and reports the results to the power supply company to obtain lower electricity costs.The intra-day rolling correction section establishes an objective function to minimize the error between the intra-day real-time load and the results obtained from the day-ahead optimization scheduling,so as to ensure that the intra-day real-time load can track the day-ahead optimization scheduling results.Finally,experiments are conducted to verify the effectiveness of the strategy proposed in this paper by using the measured traction load data and comparing the results with those obtained without the intra-day rolling correction.