Control strategy of hybrid energy storage in regenerative braking energy of high-speed railway

Zhao, Shanpeng; Feng, Qiang; Yang, Hongwei; Zhang, Youpeng

doi:10.1016/j.egyr.2021.11.230

Cited by 10 publications

(5 citation statements)

References 3 publications

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“…The operation modes of the ERSMS are classified according to the operating experience and relevant published review [3,25]. As shown in Figure 2, different operation modes of the ERSMS can be classified based on the state of the traction load P L , which is defined as the total power of the trains and the traction network loss of both section a and section b.…”

Section: Operation Modesmentioning

confidence: 99%

“…developed a bi-level model of a railway traction substation energy management system for attaining the optimal power reference and HESS size [24]. Zhao et al proposed a control strategy clarifying the energy distribution relationship between the HESS and traction power supply system under different operation modes [25]. An EMS for ERSMS including PV and ESS has been proposed in [6,26], which enhances the overall economic efficiency of system operations.…”

Section: Introductionmentioning

confidence: 99%

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An Energy Management Strategy for an Electrified Railway Smart Microgrid System Based on Integrated Empirical Mode Decomposition

Ye,

Sun,

Song

2024

Energies

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The integration of a renewable energy and hybrid energy storage system (HESS) into electrified railways to build an electric railway smart microgrid system (ERSMS) is beneficial for reducing fossil fuel consumption and minimizing energy waste. However, the fluctuations of renewable energy generation and traction load challenge the effectiveness of the energy management for such a complex system. In this work, an energy management strategy is proposed which firstly decomposes the renewable energy into low-frequency and high-frequency components by an integrated empirical mode decomposition (IEMD). Then, a two-stage energy distribution approach is utilized to appropriately distribute the energy flow in the ERSMS. Finally, the feasibility and effectiveness of the proposed solution are validated through case study.

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Section: Operation Modesmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

An Energy Management Strategy for an Electrified Railway Smart Microgrid System Based on Integrated Empirical Mode Decomposition

Ye,

Sun,

Song

2024

Energies

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“…Huang et al [14] synthetically tuned speed profiles and running times over each inter-station sector with on-board energy storage devices to maximize the use of regenerative energy. Zhao et al [15] developed a plan for storing energy and utilizing the regenerative energy of high-speed trains based on the HESS of a supercapacitor and a battery, which has an excellent regenerative energy utilization impact. Studies on energy devices usually focus on their installation on vehicles or along railroad tracks as an outstanding and alternative energy-saving scheme.…”

Section: Optimization Of Regenerative Braking Energy Utilizationmentioning

confidence: 99%

“…Zhao et al. [15] developed a plan for storing energy and utilizing the regenerative energy of high‐speed trains based on the HESS of a supercapacitor and a battery, which has an excellent regenerative energy utilization impact. Studies on energy devices usually focus on their installation on vehicles or along railroad tracks as an outstanding and alternative energy‐saving scheme.…”

Section: Introductionmentioning

confidence: 99%

Integrated energy‐efficient optimization for urban rail transit timetable

Deng

Chen

Duan

et al. 2023

IET Intelligent Trans Sys

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The energy‐efficient optimization of the train timetable should be carried out on the basis of meeting passenger demand and determining the train operation plan. This paper proposes an integrated energy‐efficient optimization framework for the train timetable. Firstly, two energy‐efficient optimization strategies for this problem are proposed: inter‐station running time allocation and regenerative braking energy utilization. The first strategy aims to reduce the traction energy consumption, realized by selecting the profile based on a given set of speed profiles for each inter‐station sector when ensuring a stable travel time of train routing. The second strategy is intended to fully utilize the regenerative energy feedback from braking trains, realized by setting the departure time of trains based on a small‐range headway adjustment. Then, an integrated energy‐efficient optimization model of the timetable is developed and solved using the genetic algorithm. Finally, a case study of the Guangzhou Metro Line 8 is presented to verify the effectiveness of the method. The results show that the utilization rate of regenerative braking energy in the optimized timetable increases by 8.60%, and the total energy consumption decreases by 9.52%. Regenerative energy utilized roughly doubles during peak hours and increases more than twice as much during off‐peak hours.

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“…While maintaining the existing timetable, the possibility of using up to 35% of regenerative braking energy is demonstrated. The paper in [10] shows a system with two types of energy storage devices that allow the exchange and storage of energy between two high-speed trains powered by two different power sectors, together with the compensation of unwanted distortions in the waveform of the three-phase power supply network. The result is a reduction in THD of up to 92% and a reduction in negative sequence current of almost 98%.…”

Section: Introductionmentioning

confidence: 99%

An Energy Flow Control Algorithm of Regenerative Braking for Trams Based on Pontryagin’s Minimum Principle

Župan,

Šunde,

Ban

et al. 2023

Energies

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Energy savings in electric rail transport are important in order to increase energy efficiency and reduce its carbon footprint. This can be achieved by storing and using the energy generated during regenerative braking. The system described in this paper consists of a supercapacitor energy storage system (SC ESS), a bidirectional DC/DC converter, and an algorithm to control the energy flow. The proper design of the algorithm is critical for maximizing energy savings and stabilizing the power grid, and it affects the lifetime of the SC ESS. This paper presents an energy flow control algorithm based on Pontryagin’s minimum principle that balances maximum energy savings with maximum SC ESS lifetime. The algorithm also performs SC ESS recharging while the rail vehicle stops on inclines to reduce the impact of its next acceleration on the power grid. To validate the algorithm, offline simulations are performed using real tram speed measurements. The results are then verified with a real-time laboratory emulation setup with HIL simulation. The tram and power grid are emulated with LiFePO4 batteries, while the SC ESS is emulated with a supercapacitor. The proposed algorithm controls a three-phase converter that enables energy exchange between the batteries and the supercapacitor. The results show that the proposed algorithm is feasible in real time and that it can be used under real operating conditions.

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Control strategy of hybrid energy storage in regenerative braking energy of high-speed railway

Cited by 10 publications

References 3 publications

An Energy Management Strategy for an Electrified Railway Smart Microgrid System Based on Integrated Empirical Mode Decomposition

An Energy Management Strategy for an Electrified Railway Smart Microgrid System Based on Integrated Empirical Mode Decomposition

Integrated energy‐efficient optimization for urban rail transit timetable

An Energy Flow Control Algorithm of Regenerative Braking for Trams Based on Pontryagin’s Minimum Principle

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