Intelligent Grid Interfaced Vehicle Eco-charging (iGIVE)

智能电网接口车辆生态充电 (iGIVE)

• 批准号: EP/L001063/1
• 负责人: Kang Li
• 金额: $ 108.96万
• 依托单位: Queen's University Belfast
• 依托单位国家: 英国
• 项目类别: Research Grant
• 财政年份: 2013
• 资助国家: 英国
• 起止时间: 2013 至 无数据
• 项目状态: 已结题
• 来源: https://gtr.ukri.org/projects?ref=EP%2FL001063%2F1
• 关键词: Intelligent; Grid; Interfaced; Vehicle; Eco

The UK government is determined to address the challenges of tackling climate change and maintaining energy security in a way that minimises costs and maximises benefits to the economy. Among all sources of CO2 emissions in the UK, the energy supply accounts for about 40%, followed by the transport for over 25%. To meet the target of cutting greenhouse gas emissions by 80% by 2050, large proportion of electricity generated from low carbon sources integrated with mass adoption of electric vehicles (EV) offer a great potential. Likewise, the Chinese 12th National Economic and Social Development Five-Year Plan has set the target of 3.5% reduction per unit of GDP in both energy use and carbon dioxide emissions, and identified new energy and clean energy vehicles among the seven priority industries in the next five years from 2012. It is clear that both countries are fully committed to a planned 'decarbonisation' of their respective energy systems. However, both face the challenges of planning and building the suitable infrastructure, and of managing the resources to ensure future power systems operate more reliably, more flexibly, and more economically, by integrating and coordinating the actions of all actors. It has been widely recognized that electric vehicles could both benefit from and help to drive forward the development of smart grids where renewable resources are widely and substantially employed. However, a number of technical challenges are still open for further exploitation. The proposed collaborative interdisciplinary research will investigate and develop an intelligent grid interfaced vehicle eco-charging (iGIVE) system for more reliable, more flexible and efficient, and more environmental friendly smart gird solutions for seamless integration of distributed low-carbon intermittent power generation and large number of EVs. To achieve this, a multilayer hierarchical power and information flow framework for monitoring and optimal control of the EV charging while minimising the volume of information passed to the utility control centers will be investigated first. Within this framework, a variable rate bi-directional high performance EV battery charging unit based on a patented technology will be developed, and battery management and optimal EV charging and discharging dispatching strategies will be investigated. Other issues associated to the charging stations, such as electromagnetic interference and harmonics generation and their impact on environment and electricity grid will also be studied. Finally, simulation platform will be built to investigate the interactions of EV-related different participants and their impact on the grid operations. A test bed to verify the design will be developed and a joint UK-China joint laboratory on smart grid and EV integration will be established, bringing together key academic and industry partners in smart grid and EV from UK and China.Both system operators and EV industry in the UK, China and other parts of the world will benefit considerably from the development of intelligent EV eco-charging systems when a large number of EVs are adopted by the public and greater amounts of renewable power are utilized, as they provide an adaptive and intelligent framework and EV charging systems to economically, efficiently and environment-friendly accommodate charging requirements as well as providing ancillary service to the grid integrated with larger amounts of intermittent renewable energy sources and thereby enable the decarbonisation of the electricity supply industry and the transport sector.

英国政府决心解决应对气候变化和维持能源安全的挑战，以最大程度地降低成本并最大程度地利用对经济的收益。在英国的所有二氧化碳排放源中，能源供应量约为40％，其次是运输量超过25％。为了满足到2050年将温室气体排放量减少80％的目标，由低碳源和大量采用电动汽车（EV）产生的电力很大一部分具有巨大的潜力。同样，中国第12个国家经济和社会发展五年计划的目标是在能源使用和二氧化碳排放中的GDP降低3.5％，并确定了2012年的七个优先行业之间的新能源和清洁能源。但是，两者都面临着计划和建立合适的基础设施的挑战，以及管理资源以确保未来的电力系统通过整合和协调所有参与者的行动来确保未来的电力系统更加可靠，更灵活，更经济地运作。人们广泛认识到，电动汽车既可以从中受益，也可以帮助推动可再生资源广泛且基本利用的智能电网的发展。但是，许多技术挑战仍在开放以进行进一步开发。拟议的协作跨学科研究将调查和开发智能网格接口的车辆生态充电（IGIVE）系统，以实现更可靠，更灵活，更有效的效率，并且更具环保友好的智能GIRD SYTERTE，以无缝整合分布式低碳间歇间间歇性发电和大量电动汽车。为此，将首先研究一个多层层次结构功率和信息流框架，以监视和最佳控制EV充电，同时最大程度地减少传递给公用事业控制中心的信息量。在此框架内，将开发基于专利技术的可变速率双向高性能电动电动电动电池充电单元，并将研究电池管理以及最佳电动汽车充电和排放调度策略。还将研究与充电站相关的其他问题，例如电磁干扰和谐波产生及其对环境和电网的影响。最后，将构建仿真平台，以调查与电动汽车相关的不同参与者的相互作用及其对电网操作的影响。将建立一个用于验证设计的测试床，并建立一个联合英国 - 中国联合实验室，将英国和中国的智能电网和电动汽车的重要学术和行业合作伙伴汇集在一起​​。英国，中国和世界各地的系统运营商和EV行业都可以从智能的EV EV EV EVE-EVE-EVEL INSER中受益于EV的智能电力系统的发展，而EV的大量收益将受益匪浅由于它们提供了一个自适应，智能的框架和电动汽车充电系统，以在经济，高效和环境友好的情况下满足充电要求，并为与大量间歇性可再生能源集成的电网提供辅助服务，从而使电力供应行业和运输部门的脱碳化。

项目成果

Future Energy Markets - An Examination of Thermal Generation in an ideally Interconnected Europe in 2050

未来能源市场 - 2050 年理想互联欧洲的火力发电考察

• 发表时间: 2017
• 作者: A. Foley

Impact of unit commitment on the optimal operation of hybrid microgrids

机组组合对混合微电网优化运行的影响

• 发表时间: 2016
• 作者: []

An Open Source Analogue to Digital Converter for Power System Measurements with Time Synchronisation

用于具有时间同步功能的电力系统测量的开源模数转换器

• 发表时间: 2017
• 作者: David M. Laverty

Procedural simulation method for aggregating charging load model of private electric vehicle cluster

私人电动汽车集群聚合充电负荷模型的程序仿真方法

• DOI: 10.1007/s40565-015-0125-z
• 发表时间: 2015
• 期刊: Journal of Modern Power Systems and Clean Energy
• 影响因子: 6.3
• 作者: BAN M

Deep Reinforcement Learning-Based Energy Storage Arbitrage With Accurate Lithium-Ion Battery Degradation Model

• DOI: 10.1109/tsg.2020.2986333
• 发表时间: 2020-04
• 期刊: IEEE Transactions on Smart Grid
• 影响因子: 9.6
• 作者: Jun Cao;Daniel J. B. Harrold;Zhong Fan;Thomas Morstyn;David Healey;Kang Li