Sustainable urban power supply through intelligent control and enhanced restoration of AC/DC networks

通过智能控制和加强交直流网络恢复实现可持续城市供电

• 批准号: EP/T021985/1
• 负责人: Jun Liang
• 金额: $ 77.03万
• 依托单位: CARDIFF UNIVERSITY
• 依托单位国家: 英国
• 项目类别: Research Grant
• 财政年份: 2020
• 资助国家: 英国
• 起止时间: 2020 至 无数据
• 项目状态: 已结题
• 来源: https://gtr.ukri.org/projects?ref=EP%2FT021985%2F1
• 关键词: Sustainable; urban; power; supply; through

China remains the world's largest electric car market, and the UK is leading deployment of electric vehicles (EVs) to meet the new net-zero 2050 emission target. Both nations will face challenges in connecting EVs in urban areas due to limited land space, constraints on carrying additional power over traditional transmission lines and challenges in providing reliable power to critical load centres. This proposal identifies areas of common technical challenges and lays out a joint programme to analyse the issues and assess possible solutions.Urban areas are the significant location of critical loads such as hospitals, airports, public transport network and data centres. Fully exploiting the potential transfer capacity and resilience of the urban electricity network with a minimum capital investment is important to citizens and governments as 60% of Chinese population and 83% of UK population live in urban areas. To release the capacity of existing AC lines and to increase the reliability, a combined AC/DC configuration is proposed, and contribution of power electronic materials and converters are considered. Coordinated control of EVs, hybrid AC/DC networks and dispersed generation are investigated to optimise transfer capacity and enhance fault-tolerant operation with the support of Internet-of-Things (IoT) tools to enable an efficient decision-making. Two specific aspects will be investigated: the ability of IoT based data-driven modelling method to enable response services by coordinating dispersed resources in an urban power network and the headroom provided by power converters to accommodate this service. The contribution of IoT in providing useful data that enable the efficient management of urban power network is an emerging paradigm for the realisation of smart cities. As an essential part of daily life, optimal utilisation and reliability of electric energy becomes paramount. However, blackouts affecting the security and stability of the power system is an important issue. EVs storage capacity and optimal scheduling through power converters will be explored and quantified to provide grid support services in the event of an emergency situation. Protection schemes that can achieve fast and reliable identification and isolation with the aids of IoT, EVs and power converters are analysed in detail and re-engineering solutions proposed. Technical challenges from widespread use of dispersed resources connected to urban energy networks will be studied. Data-driven modelling will be applied to urban power systems to characterise the capacity of EVs and distributed generations that will allow two-way communication that transforms conventional networks into more secure networks. Traditional network topologies with the inclusion of power converters will be reassessed to eliminate potentially wasteful energy conversion stages and support flexibility services. Coordinated control of converters and distributed resources with spatial-temporary coupling and edge-cloud collaboration will be developed to make cost-effective, sustainable, resilient and fault-tolerant urban power system operation.The key outputs will be the data-driven modelling and analysis methods that can assess the spatial-temporary relation between distributed resources and urban electricity network (useful to system operators and equipment vendors); engineering solutions to map the capability of vehicle to grid services; optimal scheduling using power converters in the event of an emergency situation (useful to system operators, equipment vendors and EV owners); and verification through real-time simulation and scaled laboratory test systems. The main work programme will be conducted through international partnership with 1 China research institute, 2 China universities and 2 UK universities. Researchers involved in the project will benefit from the unique international collaboration and training.

中国仍然是世界上最大的电动汽车市场，英国正在引领电动汽车（EV）的部署，以实现新的2050年净零排放目标。由于土地空间有限，传统输电线路承载额外电力的限制以及为关键负荷中心提供可靠电力的挑战，这两个国家在城市地区连接电动汽车方面将面临挑战。该提案确定了共同的技术挑战领域，并制定了一项联合方案，以分析问题并评估可能的解决方案。城市地区是医院、机场、公共交通网络和数据中心等关键负载的重要位置。以最低的资本投资充分利用城市电网的潜在传输能力和弹性对公民和政府来说非常重要，因为60%的中国人口和83%的英国人口居住在城市地区。为了释放现有交流线路的容量，提高系统的可靠性，提出了一种交直流混合结构，并考虑了电力电子材料和变流器的贡献。研究电动汽车，混合AC/DC网络和分散发电的协调控制，以优化传输容量并在物联网（IoT）工具的支持下增强容错操作，从而实现有效的决策。将研究两个具体方面：基于物联网的数据驱动建模方法通过协调城市电网中的分散资源来实现响应服务的能力，以及电力转换器提供的用于适应此服务的净空。物联网在提供有用数据方面的贡献，使城市电网的有效管理成为实现智慧城市的新兴范例。作为日常生活的重要组成部分，电能的最佳利用和可靠性变得至关重要。然而，停电事故是影响电力系统安全稳定运行的重要问题。电动汽车的存储容量和通过电力转换器的优化调度将被探索和量化，以在紧急情况下提供电网支持服务。详细分析了可以在物联网，电动汽车和电源转换器的帮助下实现快速可靠识别和隔离的保护方案，并提出了重新设计的解决方案。将研究广泛使用与城市能源网络相连的分散资源所带来的技术挑战。数据驱动的建模将应用于城市电力系统，以提高电动汽车和分布式发电的容量，从而实现双向通信，将传统网络转变为更安全的网络。包含功率转换器的传统网络拓扑将被重新评估，以消除潜在的浪费能源转换阶段并支持灵活性服务。将开发具有时空耦合和边缘云协作的变流器和分布式资源的协调控制，以实现经济高效、可持续、弹性和容错的城市电力系统运行。关键成果将是数据驱动的建模和分析方法，可以评估分布式资源与城市电网之间的时空关系（对系统运营商和设备供应商有用）;将车辆的能力映射到电网服务的工程解决方案;在紧急情况下使用电力转换器的最佳调度（对系统运营商、设备供应商和电动汽车所有者有用）;以及通过实时模拟和缩放实验室测试系统进行验证。主要工作计划将通过与1家中国研究机构、2所中国大学和2所英国大学的国际合作伙伴关系进行。参与该项目的研究人员将受益于独特的国际合作和培训。

项目成果

Analytical Model for Availability Assessment of Large-Scale Offshore Wind Farms Including Their Collector System

• DOI: 10.1109/tste.2021.3075182
• 发表时间: 2021-04
• 期刊: IEEE Transactions on Sustainable Energy
• 影响因子: 8.8
• 作者: Gayan Abeynayake;T. Van Acker;D. Hertem;Jun Liang

Reliability and Cost-Oriented Analysis, Comparison and Selection of Multi-Level MVdc Converters

• DOI: 10.1109/tpwrd.2021.3051531
• 发表时间: 2021-01
• 期刊: IEEE Transactions on Power Delivery
• 影响因子: 4.4
• 作者: Gayan Abeynayake;Gen Li;T. Joseph;Jun Liang;Wenlong Ming

Power Control Strategy for Cascaded 3L-NPC Converters Considering Thermal Conditions

• DOI: 10.1109/ieses53571.2023.10253741
• 发表时间: 2023-07
• 期刊: 2023 IEEE 3rd International Conference on Industrial Electronics for Sustainable Energy Systems (IESES)
• 作者: Jinlei Chen;Wenlong Ming;Sheng Wang;Jun Liang;I. Lüdtke

IoTSim-Osmosis: A framework for modeling and simulating IoT applications over an edge-cloud continuum

• DOI: 10.1016/j.sysarc.2020.101956
• 发表时间: 2021-05-14
• 期刊: JOURNAL OF SYSTEMS ARCHITECTURE
• 影响因子: 4.5
• 作者: Alwasel, Khaled;Jha, Devki Nandan;Ranjan, Rajiv
• 通讯作者: Ranjan, Rajiv

Decentralized Control for Multi-Terminal Cascaded Medium-Voltage Converters Considering Multiple Crossovers

• DOI: 10.1109/tpwrd.2023.3268829
• 发表时间: 2024-02
• 期刊: IEEE Transactions on Power Delivery
• 影响因子: 4.4
• 作者: Jinlei Chen;Sheng Wang;Jun Liang;R. Navaratne;Wenlong Ming