Energy-Efficient Train Control with Onboard Energy Storage Systems considering Stochastic Regenerative Braking Energy

With the rapid development of energy storage technology, onboard energy storage systems(OESS) have been applied in modern railway systems to help reduce energy consumption. In addition, regenerative braking energy utilization is becoming increasingly important to avoid energy waste in the railway systems, undermining the sustainability of urban railway transportation. However, the intelligent energy management of the trains equipped with OESSs considering regenerative braking energy utilization is still rare in the field. This paper considers the stochastic characteristics of the regenerative braking power distributed in railway power networks. It concurrently optimizes the train trajectory with OESS and regenerative braking energy utilization. The expected regenerative braking power distribution can be obtained based on the Monte-Carlo simulation of the train timetable. Then, the integrated optimization using mixed integer linear programming (MILP) can be conducted and combined with the expected available regenerative braking energy. A generic four-station railway system powered by one traction substation is modeled and simulated for the study. The results show that by applying the proposed method, 68.8% of the expected regenerative braking energy in the environment will be further utilized. The expected amount of energy from the traction substation is reduced by 22.0% using the proposed train control method to recover more regenerative braking energy from improved energy interactions between trains and OESSs

Energy-Efficient Train Control with Onboard Energy Storage Systems considering Stochastic Regenerative Braking Energy

With the rapid development of energy storage technology, onboard energy storage systems(OESS) have been applied in modern railway systems to help reduce energy consumption. In addition, regenerative braking energy utilization is becoming increasingly important to avoid energy waste in the railway systems, undermining the sustainability of urban railway transportation. However, the intelligent energy management of the trains equipped with OESSs considering regenerative braking energy utilization is still rare in the field. This paper considers the stochastic characteristics of the regenerative braking power distributed in railway power networks. It concurrently optimizes the train trajectory with OESS and regenerative braking energy utilization. The expected regenerative braking power distribution can be obtained based on the Monte-Carlo simulation of the train timetable. Then, the integrated optimization using mixed integer linear programming (MILP) can be conducted and combined with the expected available regenerative braking energy. A generic four-station railway system powered by one traction substation is modeled and simulated for the study. The results show that by applying the proposed method, 68.8% of the expected regenerative braking energy in the environment will be further utilized. The expected amount of energy from the traction substation is reduced by 22.0% using the proposed train control method to recover more regenerative braking energy from improved energy interactions between trains and OESSs

Coordinated Energy Management of the Electric Railway Traction System: Croatian Railways Case Study

A railway energy management system based on hierarchical coordination of electric traction substation energy flows and on-route trains energy consumption is presented in the paper. The railway system is divided into energy-efficient individual trains energy consumption management as a lower level, and the energy-cost-efficient electric traction substation energy flows management as a higher level. The levels are coordinated through parametric hierarchical model predictive control with the main goal of additionally decreasing the operational costs of the overall system. Through interactions with the power grid at the higher level, the system can provide ancillary services and respond to various grid requests. At the same time, lower level trains driving profiles are adjusted to attain the minimum cost of system operation with timetables and on-route constraints respected. The developed algorithm is verified against a detailed real case study scenario with the presented results showing significant cost and energy consumption reduction

Bi-level Optimization of Sizing and Control Strategy of Hybrid Energy Storage System in Urban Rail Transit Considering Substation Operation Stability

The hybrid energy storage system (HESS) which consists of battery and ultracapacitor can efficiently reduce the substation energy cost from grid and achieve the peak shaving function, due to its characteristics of high-power density and high-energy density. The sizing of HESS affects the operation cost of whole system. Besides, operation stability (like substation peak power and voltage fluctuations) is rarely considered in urban rail transit (URT) when sizing optimization of HESS is considered. Thus, this research proposes a sizing and control strategy optimization of HESS in URT. First, the mathematic model of URT with HESS is established, which is used to simulate URT and HESS operation state by power flow analysis method. Then, based on the proposed HESS control principle, a bi-level optimization of HESS in URT is proposed. The master level aims to optimize the rated capacity and power of HESS, reducing total operational cost. Then, the HESS control strategy is optimized at slave level, reducing substation peak power and voltage fluctuations of URT. The case study is conducted based on the data of Merseyrail line in Liverpool. A comparison is also conducted, which shows that the proposed method can reduce daily operation cost by 12.68% of the substation, while the grid energy cost is decreased by 57.26%

Design and verification of novel powertrain management for multi-geared battery electric vehicles

University of Technology Sydney. Faculty of Engineering and Information Technology.Despite the long-term benefit of battery electric vehicles (BEVs) to customers and the environment, the initial cost and limited driving range present the significant barriers for wide spread commercialization. The integration of multi-speed transmission to BEVs’ powertrain systems, which is in place of fixed ratio reduction transmission, is considered as a feasible method to improve powertrain efficiency and extend limited driving range for a fixed battery size. Additionally, regenerative braking also extends the mileage by recapturing the vehicle’s kinetic energy during braking, rather than dissipating it as heat. Both of these two methods reduce the requirement of battery pack capacity of BEVs without loss of performance. However, the motor-supplied braking torque is applied to the wheels in an entirely different way compared to the hydraulic friction braking systems. Drag torque and response delay may be introduced by transmitting the braking torque from the motor through a multi-speed transmission, axles and differential to the wheels. Furthermore, because the motor is usually only connected to one axle and the available torque is limited, the traditional friction brake is still necessary for supplementary braking, creating a blended braking system. Complicated effects such as wheel slip and locking, vehicle body bounce and braking distance variation, will inevitability impact on the performance and safety of braking. The aim of this thesis is to estimate if the multi-speed transmission and the mechanic-electric blended braking system are worthwhile for the customers, in terms of the price/performance relationship of others’ design solutions; To do so a generic battery electric vehicle is modelled in Matlab/Simulink® to predict motor efficiency, braking performance of different strategies, energy consumption and recovery for single reduction, two-speed Dual Clutch Transmission (DCT) and simplified Continuous Variable Transmission (CVT) equipped BEVs. Braking strategies for different purposes are proposed to achieve a balance between braking performance, driving comfort and energy recovery rate. Special measures are taken to avoid any effects of motor failure. All strategies are analysed in detail for various braking events. Advanced driver assistance systems (ADAS), such as Anti-Lock Brake System (ABS) and Electro Control Brake Distribution (EBD), are properly integrated to work harmoniously with the regenerative braking system (RBS). Different switching plans during braking are discussed. The braking energy recovery rates and brake force distribution details for different driving cycles are simulated. A credible conclusion is gained, through experimental validation of single speed and two-speed DCT scenarios and reasonable assumptions to support the CVT scenario, that both two-speed DCT and simplified CVT improve the overall powertrain efficiency, save battery energy and reduce customer costs, although each of the configurations has unique cost and energy consumption related trade-offs. Results for two of the cycles in an ‘Eco’ mode are measured on a drive train testing rig and found to agree with the simulated results to within approximately 10%. Reliable conclusions can thus be gained on the economic and dynamic braking performance. The strategies proposed in this thesis are shown to not only achieve comfortable and safe driving during all conditions but also to significantly reduce cost in both the short and long terms

Energy-Efficient Train Control with Onboard Energy Storage Systems considering Stochastic Regenerative Braking Energy

With the rapid development of energy storage technology, onboard energy storage systems(OESS) have been applied in modern railway systems to help reduce energy consumption. In addition, regenerative braking energy utilization is becoming increasingly important to avoid energy waste in the railway systems, undermining the sustainability of urban railway transportation. However, the intelligent energy management of the trains equipped with OESSs considering regenerative braking energy utilization is still rare in the field. This paper considers the stochastic characteristics of the regenerative braking power distributed in railway power networks. It concurrently optimizes the train trajectory with OESS and regenerative braking energy utilization. The expected regenerative braking power distribution can be obtained based on the Monte-Carlo simulation of the train timetable. Then, the integrated optimization using mixed integer linear programming (MILP) can be conducted and combined with the expected available regenerative braking energy. A generic four-station railway system powered by one traction substation is modeled and simulated for the study. The results show that by applying the proposed method, 68.8% of the expected regenerative braking energy in the environment will be further utilized. The expected amount of energy from the traction substation is reduced by 22.0% using the proposed train control method to recover more regenerative braking energy from improved energy interactions between trains and OESSs

Integrating renewable energy resources into the smart grid: recent developments in information and communication technologies

Rising energy costs, losses in the present-day electricity grid, risks from nuclear power generation, and global environmental changes are motivating a transformation of the conventional ways of generating electricity. Globally, there is a desire to rely more on renewable energy resources (RERs) for electricity generation. RERs reduce green house gas emissions and may have economic benefits, e.g., through applying demand side management with dynamic pricing so as to shift loads from fossil fuel-based generators to RERs. The electricity grid is presently evolving towards an intelligent grid, the so-called smart grid (SG). One of the major goals of the future SG is to move towards 100% electricity generation from RERs, i.e., towards a 100% renewable grid. However, the disparate, intermittent, and typically widely geographically distributed nature of RERs complicates the integration of RERs into the SG. Moreover, individual RERs have generally lower capacity than conventional fossil-fuel plants, and these RERs are based on a wide spectrum of different technologies. In this article, we give an overview of recent efforts that aim to integrate RERs into the SG. We outline the integration of RERs into the SG along with their supporting communication networks. We also discuss ongoing projects that seek to integrate RERs into the SG around the globe. Finally, we outline future research directions on integrating RERs into the SG