Integrating climate change mitigation and adaptation: DUAL-service heat pumps for FLEXible low-carbon heating and cooling (DUAL-FLEX)
Project ID: 2531bd1608
(You will need this ID for your application)
Research Theme: Energy and Decarbonisation
Research Area(s): Engineering
UCL Lead department: Bartlett School of Environment, Energy and Resources (BSEER)
Lead Supervisor: David Shipworth
Project Summary:
Why this research is important
Heating and cooling are the largest end-uses of energy in buildings, yet research and policy typically address them in isolation. With climate change increasing the importance of cooling, and heat pumps emerging as the key technology to deliver both heating and cooling, their dual role remains underexplored. Treating heating and cooling separately risks lock-ins, missed synergies, and sub-optimal grid integration, potentially increasing infrastructure costs. This project quantifies joint heating–cooling impacts of heat pumps, embedding equity and flexibility into system modelling to guide strategies that reduce costs, enhance resilience, and maximise household and system benefits.
Who you will be working with
The project is hosted at the Energy Institute, which holds an extensive database of household energy demand measurements, including heat pump operation, collected over several years. The project may involve collaborations with industry, such as a heat pump manufacturer. The supervision team brings expertise in building decarbonisation, heat pump demand modelling, and energy flexibility: Prof. David Shipworth, Dr. Christine Gschwendtner, and Dr. Jenny Crawley.
What you will be doing
You will:
- Quantify joint system-level impacts of heating and cooling with heat pumps, including grid and infrastructure needs, using high-resolution AI-informed demand simulations.
- Embed distributional outcomes into energy modelling by introducing equitable flexibility, assessing both system-level benefits and household-level impacts.
- Evaluate adoption pathways to reveal how uptake for heating expands sustainable cooling capacity, and vice versa, using empirical data combined with advanced scenario analysis.
Who we are looking for
We are seeking a candidate with a strong interest in energy demand, system modelling, and building decarbonization. You should have quantitative skills, and enthusiasm for learning methods that combine machine learning with physics-based modelling. This project offers excellent preparation for careers in academia, industry, or policy, contributing directly to the UK’s net-zero transition.