DESHI KONG

This paper addresses the challenge of optimizing the capacity and energy management of energy storage system (ESS) in rail transit systems, with a focus on the utilization of regenerative braking energy (RBE) generated by train braking. The system utilizes a hybrid energy storage system (HESS) consisting of superconducting magnetic energy storage (SMES) and battery to exploit the advantages of both ESS. Traditional methods have limitations in solving capacity redundancy problem. To address this issue, a cooperative optimization approach based on non-dominated sorting genetic algorithm-II (NSGAII) and mixed-integer linear programming (MILP) is proposed in this paper. By optimizing the capacity of the HESS via NSGA-II, the dual-objective optimization targeting expenditure and RBE utilization rate is achieved. MILP optimizes the input and output power of the HESS to meet various energy balance requirements. Simulation results demonstrate that the proposed approach effectively balanced system operating expenditure and RBE utilization, exploring the optimal configuration of HESS and ensuring power system stability and reliability at the same time.

Urban railways and electric vehicles will be critical in achieving city sustainability. EV shows great potential for improving railway energy efficiency. At the same time, the integration of a Photovoltaic (PV) system and an Electric Vehicle (EV) charging system is a common method of utilizing renewable resources on-the-spot. An energy storage system (ESS) can work as a shared infrastructure to combine railway, PV, and EV into a DC micro-grid. In this paper, an energy dispatch model based on the structure of the DC micro-grid and the function of each component is built and solved with Mixed-integer linear programming (MILP). To investigate the model's rationality and the effects of each part on the overall cost and operation pattern, three specific cases are tested. The global cost minimization that can be obtained by using EV and ESS to absorb the energy from PV and railway has been assessed. The utilization of ESS capacity can be promoted by the integration of EV charging demand and renewable energy.

In recent years, the introduction of Energy Storage System (ESS) into rail transit has increased the ratio of regenerative energy recovery. However, the investment of energy storage devices and ratio of energy saving varies due to different types of ESS. To overcome the problem, hybrid energy storage system (HESS) is an effective solution to balance cost, output power, and capacity. Besides, to optimize two objectives, minimization of investment and energy consumption, multi-objective programming is of great significance.This paper proposes to apply HESS to railway systems by combining superconducting magnetic energy storage (SMES) with batteries. SMES holds high power density, low energy density. On the contrary, battery has low power density, high energy density. These two ESSs can take advantage of their own strength, cover each other's shortcomings by combination, and achieve energy balance in railway transit.In this paper, energy management strategy(EMS) and capacity management is proposed taking characteristics of SMES, battery and DCDC converter into account. Furthermore, SMES, battery, DCDC converter, train and substation are modeled and programmed regarding a timetable. Finally, Nondominated Sorting Genetic Algorithm-II(NSGA-II) is introduced to balance energy consumption and cost achieving multi objective optimization.

Recent urban rail vehicles use regenerative braking that lead to high energy efficiency. However, the intermittency and random nature of regenerative power causes limitation of regenerative energy recycling rate in DC electrification. To overcome the problem, energy storage system (ESS) plays an important role. Many applications of ESS to railway systems have been seen by using batteries, supercapacitors, and flywheels.This paper proposes to apply the superconducting magnetic energy storage (SMES) to railway systems as ESS. SMES holds bright application prospects due to its quick response, high power density and high energy storage efficiency. One of the major differences from other storage devices is that SMES has characteristics of a DC current source. It is inevitable to consider the converter configuration and energy and power management in the combination of SMES and DC electrified feeders.In this paper, energy and power management is proposed taking characteristics of SMES and its converter into account. Besides, the converter topology and specification of SMES will be also investigated. Finally, it will be demonstrated that SMES system for railway ESS will work to smooth the fluctuation of regenerative power.