About the project
The Machine learning sustainable electricity markets PhD project offers a unique opportunity to contribute to the forefront of sustainable circular economies and operations through AI innovation.
This 4-year integrated PhD programme is part of the UKRI AI Centre for Doctoral Training in AI for Sustainability (SustAI).
Machine learning (ML) holds immense potential in shaping sustainable electricity markets by optimising resource allocation, enhancing grid stability, and facilitating the integration of renewable energy sources.
ML algorithms can analyse 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. This will involve forecasting optimal geographical areas, as well as optimising their output and utilisation 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.
At SustAI, we highly value diversity and actively encourage applications from women, Black, Asian and minority ethnic, LGBT+, and disabled candidates for this studentship. We are committed to equality, diversity, and inclusion.
Visit SustAI website for more information.
