PhD Studentship: Machine learning sustainable electricity markets (ML-SEM)

Supervisory Team:

Hector Calvo-Pardo; Vahid Yazdanpanah; Tiago Alves (Solar Americas); Enrico Gerding

PhD Supervisor: Hector Calvo-Pardo

Project description:

Machine learning (ML) holds immense potential in shaping sustainable electricity markets by optimizing resource allocation, enhancing grid stability, and facilitating the integration of renewable energy sources. ML algorithms can analyze vast datasets, including energy consumption patterns, weather forecasts, and market dynamics, to inform decision-making processes and improve efficiency in electricity generation, transmission, and distribution. One key application of ML in sustainable electricity markets is demand forecasting, where algorithms can predict electricity consumption patterns with high accuracy. This enables utilities to optimize their generation and distribution strategies, reducing wastage and carbon emissions. ML algorithms also play a crucial role in grid management by predicting and mitigating potential grid disturbances, such as voltage fluctuations or equipment failures, thereby enhancing grid stability and reliability. This research project will focus on deploying ML techniques to study the effective integration of renewable energy sources, such as solar and wind power, into the grid by forecasting optimal geographical areas (e.g. location) as well as optimizing their output and utilization alongside traditional sources delivering energy to the grid. This facilitates the transition towards a more sustainable energy mix while ensuring grid stability and minimizing costs.

The ML-SEM PhD project offers a unique opportunity to contribute to the forefront of sustainable circular economies and operations through AI innovation.  This is a 4-year integrated PhD (iPhD) programme and is part of the UKRI AI Centre for Doctoral Training in AI for Sustainability (SustAI). At SustAI, we highly value diversity and actively encourage applications from women, Black, Asian and minority ethnic (BAME), LGBT+, and disabled candidates for this studentship. Committed to Equality, Diversity, and Inclusion. For more information about SustAI, please see: https://sustai.info/

If you wish to discuss any details of the project informally, please contact Professor Enrico Gerding, Director of the SustAI CDT, Email: sustai@soton.ac.uk.

Entry Requirements

A very good undergraduate degree (at least a UK 2:1 honours degree, or its international equivalent).

Closing date: 31 May 2024.

Later admissions may be considered depending on funds remaining.

Funding: Funding includes tuition fees, a tax-free living stipend of £21.5k per year for 4 years, and £4.8k for travel and equipment. Funding is available for citizens from UK, EU and Horizon associated countries. For more information, see: https://sustai.info/apply

How To Apply

Apply online: Search for a Postgraduate Programme of Study (soton.ac.uk).

Select programme type Research, Full or Part time, choose the 2024-2025 Academic year, and in the Search text enter “sust”.

On the next page, select Apply Online for the “iPhD AI for Sustainability”.

In Section 2 of the application form you should include the name of the project in the Area of Research.

Applications should include:

• Research Proposal
• Curriculum Vitae
• Two reference letters
• Degree Transcripts/Certificates to date

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