Toggle Main Menu Toggle Search

Open Access padlockePrints

Quantifying Peak Heat Demand in Neighbourhoods: A UBEM Approach and Its Implications for Residential Heating Electrification in the UK—A Case Study of Newcastle upon Tyne

Lookup NU author(s): Dr Carlos CalderonORCiD

Downloads


Licence

This work is licensed under a Creative Commons Attribution 4.0 International License (CC BY 4.0).


Abstract

Developing Urban Building Energy Models (UBEM) to manage heat decarbonisation at the neighbourhood level is both crucial and challenging. Our study addresses key research challenges: quantifying peak heat energy demand and developing reliable and replicable urban energy demand microsimulations. We applied our UBEM approach to a case study area of 228 houses served by the Ridgeway New Low Voltage (LV) electrical substation in Newcastle upon Tyne, to estimate the difference between existing peak heat and electricity demand at this scale. Results show that peak heat demand is 5 to 14 times greater than peak electricity demand, significantly exceeding estimates from national studies. Furthermore, our work follows a comprehensive validation framework, comparing our simulation results against all relevant and available UK datasets. This comparison demonstrates that our model is an overall good fit at the declared Level of Detail. However, our paper identifies significant challenges, particularly in validation, that need to be addressed to improve the reliability and usability of future UBEMs. Finally, we reflect on all our findings and make policy recommendations, as we believe addressing the issues raised in this paper is vital for enabling area-based planning of residential heating electrification, particularly in the UK.


Publication metadata

Author(s): Calderon C, Aguilar Cardenas M, Aoun J

Publication type: Article

Publication status: Published

Journal: Energy and Buildings

Year: 2024

Volume: 321

Print publication date: 15/10/2024

Online publication date: 30/07/2024

Acceptance date: 25/07/2024

Date deposited: 05/08/2024

ISSN (print): 0378-7788

ISSN (electronic): 1872-6178

Publisher: Elsevier BV

URL: https://doi.org/10.1016/j.enbuild.2024.114609

DOI: 10.1016/j.enbuild.2024.114609

Data Access Statement: Data will be made available on request.


Altmetrics

Altmetrics provided by Altmetric


Share