Energy Storage Capacity Allocation And Optimal Dispatch Of Urban Rail Transit Considering Renewable Energy Power Supply

With the continuous improvement of my country’s energy exploration technology,the increasing demand for primary energy,and the serious shortage of fossil energy,countries around the world call for the development of renewable energy.As a representative of new energy,wind and solar power generation has the advantages of easy access and no pollution,and has become a clean energy that my country’s key research.my country actively promotes the reform of energy structure and proposes renewable energy legislative policies.For new energy power generation technology,certain achievements have been made.results.my country’s urban rail transit has developed rapidly in recent years.As of 2021,the operating mileage has reached nearly 8,000 kilometers.At the same time,the annual increase in mileage data continues to increase,with an annual growth rate of 11.6%.Power demand is large.Therefore,it is very meaningful to study the power supply of renewable energy for urban rail transit.On the one hand,it can reduce grid load and power consumption,and on the other hand,it can reduce resource waste and achieve green environmental protection.The forecast of renewable energy is conducive to the reasonable dispatch and allocation of the power generation department.The relevant departments can analyze and compare the predicted power generation data and demand,adjust the power dispatch plan,optimize the system reserve capacity and reduce operating costs.In this paper,renewable energy power generation models represented by wind and photovoltaics are established respectively,the power quality of renewable energy power generation is analyzed,and the main influencing factors of renewable energy power generation are screened by principal component analysis method and correlation test method;For photovoltaic and wind power,establish a classification model for different weather conditions and a similarity classification model for wind farm areas,and conduct prediction and comparison analysis through BP neural network prediction,time series prediction,and their corresponding improved and optimized BP prediction methods.Each method has its own advantages and disadvantages,and the prediction error distribution curve is analyzed to lay the foundation for the hybrid energy storage capacity configuration and multi-time-scale scheduling optimization in the following.The realization of stable power supply to rail transit trains by intelligent power grid and renewable energy is inseparable from the development of energy storage technology.This paper analyzes the relationship between the output characteristics of "source-load-storage" and the energy flow between transmission lines.Through energy storage,the power fluctuation difference between supply and demand is stabilized,and the stable interaction of electric energy with the large power grid is realized.Secondly,based on the rainflow counting method and the variational mode decomposition method,the reasonable charge and discharge control of the hybrid energy storage is realized,and the service life of the energy storage is improved.Then,a multi-objective economic optimization model is established under four typical scenarios,and the improved intelligent optimization algorithm is used to solve it.Finally,by comparing the capacity configuration in typical scenarios and the results of economic benefit examples,suggestions are given for changing the frequency of departures and increasing or decreasing the scale of generator sets in different scenarios,indicating that the improved intelligent optimization algorithm can increase the energy consumption of renewable energy.Economic benefits in traction power supply for urban rail transit.In order to solve the problems of the huge amount of braking feedback energy in urban rail transit,the uncertainty of renewable energy,the complex energy interaction between supply and demand side and the non-uniform time scale,this paper proposes a multi-timescale hybrid energy storage energy scheduling based on train braking feedback.plan.In the day-ahead stage,the goal is to optimize the energy storage and electric energy economy,and the demand factors of time-of-use electricity prices are considered to obtain the day-ahead scheduling results;in the intraday stage,based on the model predictive control rolling optimization model,the multi-scenario simulation technology is used to take into account the inconvenience of renewable energy.Deterministic,get the optimization result feedback to correct the rolling optimization intraday scheduling model.In the real-time stage,considering the optimal scheduling mode of urban rail transit train operation,and taking into account the constraints of the charging and discharging characteristics of hybrid energy storage,a realtime train scheduling energy optimization model is established to realize the multi-time scale scheduling scheme of wind energy-grid energy-traction power supply energy.An example analysis is carried out to verify the effectiveness,economy and robustness of the method in this paper.