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Reference Number EP/R001456/2
Title Electricity Satnav - Electricity Smart Availability Topology of Network for Abundant electric Vehicles
Status Completed
Energy Categories ENERGY EFFICIENCY(Transport) 10%;
RENEWABLE ENERGY SOURCES(Solar Energy, Photovoltaics) 10%;
OTHER POWER and STORAGE TECHNOLOGIES(Electricity transmission and distribution) 70%;
OTHER CROSS-CUTTING TECHNOLOGIES or RESEARCH(Environmental, social and economic impacts) 5%;
Research Types Basic and strategic applied research 100%
Science and Technology Fields SOCIAL SCIENCES (Economics and Econometrics) 10%;
ENGINEERING AND TECHNOLOGY (Electrical and Electronic Engineering) 50%;
UKERC Cross Cutting Characterisation Systems Analysis related to energy R&D (Energy modelling) 50%;
Systems Analysis related to energy R&D (Other Systems Analysis) 50%;
Principal Investigator Dr J Yang
No email address given
Sch of Engineering and Applied Science
Aston University
Award Type Standard
Funding Source EPSRC
Start Date 15 October 2019
End Date 30 June 2020
Duration 8 months
Total Grant Value £26,139
Industrial Sectors Energy
Region West Midlands
Programme Energy : Energy
Investigators Principal Investigator Dr J Yang , Sch of Engineering and Applied Science, Aston University (99.998%)
  Other Investigator Prof JL (Jillian ) Anable , Institute for Transport Studies, University of Leeds (0.001%)
Dr VV Grinevich , Southampton Business Schoo, University of Southampton (0.001%)
  Industrial Collaborator Project Contact , University of Nottingham (0.000%)
Project Contact , Ove Arup & Partners Ltd (0.000%)
Web Site
Abstract The infrastructure of our electricity transmission and distribution is undergoing a substantial transformation to facilitate the realisation of a low-carbon economy. One important aspect is that, in low-voltage distribution networks, growing numbers of micro/small-scale distributed energy resources such as wind turbines and solar photovoltaic (PV) panels are being installed and commissioned. There are also pressing demands for new approaches to intelligently control appliances as a consequence of demand-side management or electrified transportation e.g., electric vehicles (EVs).Public EV charging points are being installed all over the UK. However, the resources are still very limited in terms of both the number installed and the perceived availability of charging amongst drivers. Meanwhile, distributed renewable sources generate fluctuating power which is not suited to expected patterns of EV charging. For instance, an EV owner may prefer to charge their car at night while the power generated from their rooftop PV panel only provides electricity during daytime. Energy storage is often viewed as the solution to this but it is difficult to justify its costs particularly in the context of domestic usage. Alternatively one can sell PV power to the grid and then purchase power when needed. For example, the feed-in-tariff encourages dispersed power being back-fed into the grid. These options can either cause waste of renewable resources (depending on the energy storage device on-site and efficiency), increase of physical stresses and losses (by increasing currents) in the distribution networks, and potentially be uneconomical for customers due to the price difference.Speculatively if all houses/vehicles can be used as EV charging resources, apart from charging points owned by network companies, the power imbalance issue and the frustration of EV drivers struggling to find a working charging point could be resolved. This research will investigate the feasibility of such a system which will provide real-time electricity availability information to foster the development of a peer-to-peer decentralised electricity market between micro/small-scale distributed energy generators (e.g. households with PV systems) and EV owners. This opens up the possibility of using the mobility of EV as energy storage for end users and excess electricity generated by households as a source to service the energy demand of EV owners. The proposed system will provide an open price bidding environment based on real-time electricity availability information of surplus power from distributed resources. To realise this a background programme needs to be running in real-time to model low-voltage electricity distribution networks from the distribution network operators (DNO). In this project, detailed network modelling (in both space and time domains) will be generated via graphical auto-identification techniques based on the existing DNO geographic information systems (GIS) and network design manuals. The social feasibility will also be assessed through qualitative and quantitative work to assess potential acceptability and behavioural responses. This idea can provide more flexible EV charging/discharging practices by options of H2V (House-to-Vehicle), W2V (Wind-to-Vehicle), and V2V (Vehicle-to-Vehicle) scenarios. Such a system could lead to a more efficient and flexible way of utilising distributed renewable energy sources and improving EV charging practices. From the DNO's point of view, such a system would also make it easier to manage dispersed renewable generation, mitigate network stresses and reduce the need for network reinforcement.
Publications (none)
Final Report (none)
Added to Database 18/08/21