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.
|Effective start/end date||31/12/13 → 30/12/16|
- Engineering and Physical Sciences Research Council
Explore the research topics touched on by this project. These labels are generated based on the underlying awards/grants. Together they form a unique fingerprint.