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Real-World Performance of Domestic Photovoltaics (RP-PV): Self consumption, flexibility, storage and long-term performance

Project ID: 2531ad1484

(You will need this ID for your application)

Research Theme: Energy and Decarbonisation

UCL Lead department: Bartlett School of Environment, Energy and Resources (BSEER)

Department Website

Lead Supervisor: Tadj Oreszczyn

Project Summary:

PhD Studentship in Solar Energy Performance at UCL

Are you passionate about renewable energy and keen to contribute to a sustainable future? Join our team at the Smart Energy Research Group (SERG) at UCL’s Energy Institute (https://www.ucl.ac.uk/bartlett/energy/research/smart-energy-research-group). Supervised by Dr. Martin Pullinger and Professor Tadj Oreszczyn, this fully funded PhD studentship will dive into the real-world performance of domestic solar photovoltaic (PV) systems in the UK.

About the Research

With only 5% of UK homes currently equipped with PV systems but projections of rapid growth, there is a pressing need to understand their impact on household energy demand, grid dependence, and sustainability over time. This project will investigate four key questions:

•	What is the long-term efficiency of PV systems in UK homes?
•	How much do PV systems reduce household energy demand and peak grid loads?
•	Do PV installations lead to increased energy use overall (rebound effect)?
•	How does battery ownership affect PV performance and occupant behavior?
•	How do household characteristics and other factors influence those patterns of demand, behaviours and PV performance?

What You Will Do

You’ll work with a rich dataset from over 13,000 UK homes, analyzing half-hourly smart meter data to compare PV and non-PV households. Using advanced statistical and machine learning techniques, you will assess the effects of factors such as energy storage, self-consumption, and PV flexibility.

Ideal Skills

We’re looking for a candidate with:

•	A background in energy systems, data science, or engineering.
•	Quantitative analysis skills, including familiarity with machine learning.
•	An interest in energy sustainability and practical solutions for the UK’s energy transition.

This is a unique opportunity to contribute to the future of the UK’s energy landscape, informing policies on energy pricing and national energy models. Join us in shaping sustainable energy solutions for tomorrow!