Home Energy Optimisation: Enhancing Heat Pump Efficiency through Data-Driven Insights

Title

Home Energy Optimisation: Enhancing Heat Pump Efficiency through Data-Driven Insights

Subject

Engineering

Creator

Ujair Abdullah

Date

2024

Contributor

Dr Peter Brommer

Abstract

The Department for Energy Security and Net Zero (DESNZ) has launched the "Electrification of Heat" project to decarbonise domestic heating through air source heat pumps (ASHPs). This study uses DESNZ and Energy Systems Catapult datasets and Python scientific computing methodologies to develop machine-learning models that predict ASHP energy consumption, efficiency, and cost savings. The goal is to support informed decisions by policymakers, consumers, and energy providers, ultimately reducing electricity costs and carbon emissions in UK households.

Meta Tags

predictive-modelling, scientific-computing, machine-learning, ai, engineering, physics, computer-science, sustainability, energy, efficiency, heating, household, cost-of-living

Files

Citation

Ujair Abdullah, “Home Energy Optimisation: Enhancing Heat Pump Efficiency through Data-Driven Insights,” URSS SHOWCASE, accessed November 22, 2024, https://urss.warwick.ac.uk/items/show/711.