Join the research team at the University of Reading on an exciting smart-energy project. Working with industrial partners at the forefront of smart energy systems, you will take a leading role in developing a virtual power meter that can estimate the power flow in the electricity grid using voltage readings from electricity meters, electrical vehicle chargers, and other sensors around the grid. The project will deliver low-cost, real-time data on the state of the network and support the rapid growth of low-carbon smart-energy technologies.
The role is a 1-year, full-time, Post-Doctoral Research Associate (PDRA) position to develop mathematical models to estimate the power flow at low-voltage substations based on voltage readings from within the network fed by the substation. Whether through smart meters, solar installations, or electric vehicle chargers, there are a growing number of voltage sensors appearing on the network. Our project will use readings from these sensors to provide network companies and other stakeholders with crucial real-time information about the state of the network enabling better utilization and greater uptake of smart and low-carbon technologies.
The post is based at the School of the Built Environment, University of Reading as is funded by Innovate as part of the ADVENT (Advanced Data-driven Virtual Electricity Network Tracking) project. The candidate will benefit from being part of a wider research community within the Energy and Environmental Engineering Research Group at the University of Reading with strong connections to other research projects including the CREDS (Centre for Research into Energy Demand Solutions) consortium. The candidate will also benefit from collaborating with industrial partners working at the forefront of smart energy systems.
The core work will involve developing mathematical models that can represent the connected nodes of parts of the low-voltage electricity network, and then using statistical techniques to estimate the power flow through the network based on measurements at only some of the nodes. This role will focus more on statistical techniques and estimation rather than electrical engineering.
You will have:
- Excellent mathematical modelling skills
- Ability to carry out advanced data analytics on large data sets
- In-depth knowledge of a variety of mathematical modelling techniques
- Ability to develop research case studies
- Excellent communication skills
- Willingness to engage with industry and public for data collection and dissemination
- Postgraduate research experience in a relevant area
- Doctorate in a relevant subject
- Ability to work both independently and as part of a team
- Record of publications commensurate with career stage
Applications will be reviewed periodically before the closing date and interviews conducted thereafter as appropriate.
Informal contact details
Dr Ben Potter
Interviews will be held 11 November 2020
The University is committed to having a diverse and inclusive workforce, supports the gender equality Athena SWAN Charter and the Race Equality Charter, and is a Diversity Champion for Stonewall, the leading LGBT+ rights organisation. Applications for job-share, part-time and flexible working arrangements are welcomed and will be considered in line with business needs.