Xing, Chen (2023) Advanced Modelling, Control and Energy Optimization of Railway Traction Power Supply Systems. PhD thesis, University of Leeds.
Abstract
As part of the effort to achieve the Paris agreement climate goals, in June 2019, the UK government passed the legislation and set a stringent target aiming for net zero greenhouse gas (GHG) emissions by 2050, becoming the first major economy to take concrete steps to tackle the issue of climate change. It is gradually acknowledged that greenhouse gas removal (GGR) is an essential measure for the UK to meet its objectives of carbon emission reduction.
As reported, the total emissions of the UK in 2021 reached 447, where the surface transport sector accounted to 23%, which became the largest source of emissions in the UK. Amongst, personal road transport means emitted more carbon dioxide on average than other land transport modes, therefore shifting towards a higher share of public and mass transit will be essential. Railways are recognised as one of the most energy-efficient modes of transportation for both passengers and freight. However, in the UK, only 38% of the existing railway network has been electrified by year 2021.
In this context, on the one hand, the electrification of the railway sector needs to be further promoted. On the other hand, there are still great potentials to enhance the energy efficiency for the existing electrified AC railway traction power supply system. Meanwhile, with significant penetration of renewable energy and integration of energy storage systems (ESS), it brings great opportunities to achieve railway net-zero, but also more challenges to the design, control, stability and reliability, and energy management of the railway power supply system. The trend moving from traditional railway power supply system to more efficient smart one has become predominant.
The primary objective of this thesis is to explore various techniques that can be used to optimize energy efficiency in AC railway traction power supply systems. This research begins with a comprehensive review of the scope of railway traction power supply system and energy optimization in Chapter 2. Then, targeting at the raised challenges, in Chapter 3, a multi-objective optimization power compensation strategy based on the NSGA-II algorithm has been proposed for the railway co-phase power supply system with renewable energy integration, to reduce the system operation capacity while addressing the power quality issues. In Chapter 4, continuing to focus on the railway co-phase power supply system with ESS integration, a DQN-based thermal constrained energy management strategy has been proposed to achieve the peak load shaving and constrain the temperature increase for both the power electronics modules and ESS so as to enhance their reliability. In Chapter 5, for the train operation side, a bi-objective robust optimization model for the train speed trajectories has been formulated to minimize both the energy consumption and journey time, in which the robustness against the uncertain train mass is also considered and viewed as a decision maker (DM) preference. A novel multi-objective optimization
algorithm namely p-NSGA-II has been proposed to handle the formulated problem, incorporating the original NSGA-II and a proposed preference dominance criterion. The energy optimization for the AC railway traction power supply system is investigated from both railway power supply side and train operation side. This includes the development of advanced optimization algorithms and techniques, the use of regenerative braking power, renewable energy and energy storage systems, and the optimization of train trajectory planning. The research also addresses the challenges associated with complex system modelling of the railway traction power supply system with renewable and ESS integration, system reliability and robustness enhancement, and power quality improvement.
Overall, this research presents a comprehensive framework on the modeling, control and energy optimization to support the development of efficient smart railway traction power supply systems with a transition from the legacy systems, and provides valuable insights into various key issues relating to the construction of sustainable railway transportation systems.
Metadata
Supervisors: | Li, Kang and Zhang, Li |
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Awarding institution: | University of Leeds |
Academic Units: | The University of Leeds > Faculty of Engineering (Leeds) > School of Electronic & Electrical Engineering (Leeds) |
Depositing User: | Mr Chen Xing |
Date Deposited: | 17 Jul 2023 14:06 |
Last Modified: | 17 Jul 2023 14:06 |
Open Archives Initiative ID (OAI ID): | oai:etheses.whiterose.ac.uk:32969 |
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