AI-driven Trustworthy Energy Advice for End Users

Investing in cleaner renewable energy generation in domestic settings is highly challenging for end users. Installing solar PV, battery storage and/or switching to EVs is expensive and requires reasoning about long-term costs, high uncertainty and behaviour will affect both the return on investment and the environmental sustainability of the installation.

 The main research problem in this project will be to explore how AI tools can help domestic end users in their switch to renewable energy, and to do so in a trustworthy manner.

 This project will focus on several different aspects including:

 – Optimisation of a renewable energy installation given the properties of a user’s home and historical consumption data.

– Lifetime monitoring and optimisation of the system, including automatic energy management (through heating, car charging and import/export of energy).

 – Suggestion of behaviour interventions based on consumption data and limited interactions with the end user.

Trust is a key aspect of this – the project will therefore explore techniques for quantifying and uncertainty, explaining calculations and assumptions clearly to users. To enable this, it will involve running focus groups, surveys and field trials with users. Another aspect is to consider possible incentive schemes to encourage behaviour modifications or demand response. In terms of methodology, the project will combine the use of optimisation, machine learning (for demand / behaviour predictions, including under incentives) and aspects of explainable AI.

 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). For more information about SustAI, please see: https://sustai.info/

Entry Requirements

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

Closing date: 8 April 2024. Later applications may be considered depending on funds remaining.

Funding: We offer a range of funding opportunities for both UK and international students, including Bursaries and Scholarships. For more information please visit PhD Scholarships Doctoral College University of Southampton Funding will be awarded on a rolling basis, so apply early for the best opportunity to be considered.

How To Apply

Apply online:  HERE Select programme type (Research), 2024/25, Faculty of Engineering and Physical Sciences, next page select “iPhD in Sustainable AI (Full time)”. In Section 2 of the application form you should insert the name of the supervisor Vahid Yazdanpanah.

Applications should include:

Research Proposal

Curriculum Vitae

Two reference letters

Degree Transcripts/Certificates to date

For further information please contact: feps-pgr-apply@soton.ac.uk