The future potential of critical energy infrastructure is the integration of smart local energy systems (SLES). SLES will be tailored to the needs of the community in order to optimise the cost, resilience and low carbon attributes the climate emergency demands. This PhD will develop new computational modelling techniques to capture the dynamics between SLES and national infrastructure, as well as the specific relationships within these multi-vector systems.
This PhD studentship is based within the Smart Systems Group (https://smartsystems.hw.ac.uk/about/staff/
) at Heriot-Watt University. Heriot-Watt University is the academic lead of the Responsive Flexibility Demonstrator project studying the Orkney energy community/living lab (£28.5M), Community scale Energy Demand Reduction in India (£1.5M) and a co-founder of the UK National Centre for Energy System Integration (£25M).
Global society depends on continuity of service of critical systems. Critical systems that deliver vital services such as energy, transportation, telecommunications, food and water, the built environment and healthcare. The systems within these sectors are increasingly complex and interdependent, interacting at a global scale, thereby making them susceptible to catastrophic and cascading failure under stress.
Along with this increasing connectivity, there are significant challenges in the financial and carbon cost of these services. Decentralisation of our energy infrastructure is one route to address these challenges. However, in order to deliver a fair and reliable energy system future Smart Local Energy Systems, have to be design and modelled to optimise the multi-vector nature of the system. In this PhD the student will explore and develop new models for SLES, based on data from real communities to create models that demonstrate the risks and benefits of integrated services and energy vectors.
A wide range of computational modelling techniques are relevant for this problem and explored in our research group, including those from power systems (monitoring resilience and state of health of large scale complex assets), artificial intelligence (in particular multi-agent modelling and machine learning), mathematical and stochastic models, complex systems analysis etc. Some example challenges to be addressed include: how to accommodate the local impact of the decarbonisation of transport on the electrical network, and how to secure a local (regional) and national energy infrastructure within increasing renewables and distributed storage.
Primary areas of thematic research will include:
- Exploring how different vectors can be aggregated to optimise carbon, cost and energy demand needs of a community.
- Modeling energy communities, such as multi-agent models of individual and community energy demand/micro-generation and storage
- Modelling the resilience of the SLES when providing local and national services e.g. utilising distributed storage for demand-side and fast frequency response.
- Developing autonomous management architectures for these systems e.g. self-healing.
The student will benefit from involvement with academics, researchers, industrialists and regulators involved in the CESI, ReFLEX and CEDRI projects.
All applicants must have or expect to have a 1st class MChem, MPhys, MSci, MEng or equivalent degree by Autumn 2020. Selection will be based on academic excellence and research potential, and all short-listed applicants will be interviewed (in person or by Skype). Our scholarships are usually only open to UK/EU applicants who meet residency requirements set out by EPSRC, however some scholarships are available for exceptional overseas candidates.
All applications must be received by 28th February 2020. All successful candidates should usually expect to start in September/October 2020.
How to Apply
Apply Online - https://hwacuk.elluciancrmrecruit.com/Admissions/Pages/Login.aspx
When applying through the Heriot-Watt on-line system please ensure you provide the following information:
(a) in ‘Study Option’
You will need to select ‘Edinburgh’ and ‘Postgraduate Research’. ‘Programme’ presents you with a drop-down menu. Choose Electrical Engineering PhD and select September 2020 for study option (this can be updated at a later date if required)
(b) in ‘Research Project Information’
You will be provided with a free text box for details of your research project. Enter Title and Reference number of the project for which you are applying and also enter the supervisor’s name.
This information will greatly assist us in tracking your application.
Please note that once you have submitted your application, it will not be considered until you have uploaded your CV and transcripts.