Grid Economics, Planning and Business Models for Smart Electric Mobility

智能电动汽车的电网经济、规划和商业模式

• 批准号: EP/L001039/1
• 负责人: Goran Strbac
• 金额: $ 128.16万
• 依托单位: Imperial College London
• 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%2FL001039%2F1
• 关键词: Grid; Economics; Planning; Business; Models

The project will provide strategic insights regarding the integration of the transport sector into future low carbon electricity grids, and is inspired by limitations in current grid investment, operation and control practices as well as regulation and market operation, which may prevent an economically and environmentally effective transition to electric mobility. Although various individual aspects of the operation of electricity systems within an integrated transport sector have received some research attention, integrated planning of the grid, EV charging infrastructure and ICT (information and communication technologies) infrastructure design have not been addressed yet. In this proposal we propose to tackle these challenges in an integrated manner. At the heart of our proposal is a whole systems approach. It recognises the need to consider: EV demand and flexibility, electricity network operation and design, charging infrastructure operation and investment, ICT requirements and business models for electric mobility. This is essential when considering constraints imposed by the network on EV charging, and in return the requirements imposed by EVs on the system design and operation. This research will place emphasis on future energy scenarios relevant to the UK and China, but the tools, methods and technologies we develop will have wider applications. Specifically, a number of infrastructure planning related challenges for the massive rollout of EV have yet to be comprehensively investigated. First, traditional models of the travel of vehicles are based on the statistical prediction of aggregate-level travel demand without capturing the behavioural characterisation of users' driving requirements and preferences. Hence, this project will investigate new alternative activity-based travel demand models capturing in a bottom-up approach the behavioural basis of individual users' decisions regarding participation in activities yielding driving needs, behavioural aspects related to EV adoption and alternative EV charging strategies, as well as the characteristics of EV and the charging infrastructure. Unlike the existing models that analyse the EV impacts on isolated sectors of the power system, this project will assess economic effects on generation, transmission and distribution sectors simultaneously and subsequently reveal trade-offs between the cost and benefit streams of different EV charging strategies for different actors in the electricity chain. Furthermore, the closely related problem of EV charging infrastructure and ICT infrastructure planning -which has a central role in the massive EV rollout- has been almost completely neglected. This research project will examine novel risk-constrained stochastic optimization approaches in order to address the challenge of strategically investing in EV recharging and ICT infrastructures ahead of need, and will analytically investigate the interdependence between the power systems and EV enabling infrastructure planning. This project will also investigate alternative business models for the EV market integration and will propose a framework providing the opportunity for EVs to simultaneously support more efficient system operation and investment in assets across the entire electricity system chain. This research will formulate a new decentralised, market-based planning mechanism appropriate for deregulated power system environment and enable the investigation of the impact of alternative market designs and arrangements on the cost effectiveness of EV integration. Finally, a set of comprehensive use cases employing tools and methodologies developed in the project will be employed to understand the role and the importance of electric mobility in future UK and China low carbon systems and produce a suitable commercial and regulatory framework and a set of policy recommendations on ways of supporting the optimal deployment of EV infrastructure.

该项目将提供关于将运输部门融入未来低碳电网的战略见解，并受到当前电网投资、运营和控制做法以及监管和市场运作的限制，这些限制可能会阻碍经济和环境有效地过渡到电力机动性。尽管综合运输部门内电力系统运作的各个方面已得到一些研究关注，但尚未涉及电网、电动汽车充电基础设施和信息和通信技术基础设施设计的综合规划。在这项提案中，我们提议以综合方式应对这些挑战。我们提案的核心是一套完整的系统方法。它认识到需要考虑以下因素：电动汽车的需求和灵活性、电网运营和设计、充电基础设施运营和投资、信息和通信技术要求以及电力移动性的商业模式。当考虑到网络对电动汽车充电的限制，以及电动汽车对系统设计和操作的要求时，这是必要的。这项研究将重点放在未来与英国和中国相关的能源情景上，但我们开发的工具、方法和技术将有更广泛的应用。具体地说，电动汽车大规模铺设带来的一些与基础设施规划相关的挑战尚未得到全面调查。首先，传统的车辆出行模型是基于对总体出行需求的统计预测，而没有捕捉到用户驾驶要求和偏好的行为特征。因此，该项目将研究新的替代活动出行需求模型，以自下而上的方法捕捉个人用户关于参与产生驾驶需求的活动的行为基础、与电动汽车采用和替代电动汽车充电策略相关的行为方面，以及电动汽车和充电基础设施的特点。与分析电动汽车对电力系统孤立部门的影响的现有模型不同，该项目将同时评估对发电、输电和配电部门的经济影响，并随后揭示不同电动汽车充电策略对电力链中不同参与者的成本和收益流之间的权衡。此外，与电动汽车充电基础设施和ICT基础设施规划密切相关的问题--在大规模电动汽车推广中发挥核心作用--几乎完全被忽视了。该研究项目将研究新的风险约束随机优化方法，以应对在需要之前对电动汽车充电和ICT基础设施进行战略投资的挑战，并将分析调查电力系统和电动汽车基础设施规划之间的相互依存关系。该项目还将研究电动汽车市场整合的替代商业模式，并将提出一个框架，为电动汽车同时支持更高效的系统运营和整个电力系统链上的资产投资提供机会。这项研究将制定一种新的分散的、以市场为基础的规划机制，适合于放松管制的电力系统环境，并能够调查替代市场设计和安排对电动汽车整合成本效益的影响。最后，将使用项目中开发的工具和方法开发一套全面的使用案例，以了解电力移动性在未来英国和中国低碳系统中的作用和重要性，并就如何支持电动汽车基础设施的最佳部署提出合适的商业和监管框架和一套政策建议。

项目成果

Characteristic Demand Profiles of Residential and Commercial EV Users and Opportunities for Smart Charging

住宅和商业电动汽车用户的特征需求概况以及智能充电的机会

• 发表时间: 2015
• 作者: Aunedi M

Network Pricing for Multienergy Systems Under Long-Term Load Growth Uncertainty

长期负荷增长不确定性下多能源系统的网络定价

• DOI: 10.1109/tsg.2022.3159647
• 发表时间: 2022
• 期刊: IEEE Transactions on Smart Grid
• 影响因子: 9.6
• 作者: Cheng S

Whole-system Benefits of Vehicle-to-Grid Services from Electric Vehicle Fleets

电动车队车到电网服务的全系统优势

• DOI: 10.1109/ever48776.2020.9243032
• 发表时间: 2020
• 作者: Aunedi M

Economic value of inertia in low-carbon power systems

• DOI: 10.1109/isgteurope.2017.8260153
• 发表时间: 2017-09
• 期刊: 2017 IEEE PES Innovative Smart Grid Technologies Conference Europe (ISGT-Europe)
• 作者: Luis Badesa;Fei Teng;G. Strbac

Real option-based network investment assessment considering energy storage systems under long-term demand uncertainties

长期需求不确定性下考虑储能系统的基于实物期权的网络投资评估

• DOI: 10.1049/rpg2.12532
• 发表时间: 2022
• 期刊: IET Renewable Power Generation
• 影响因子: 2.6
• 作者: Cheng S