Ten questions concerning data-driven modelling and forecasting of operational energy demand at building and urban scale

H Kazmi, C Fu, C Miller - Building and Environment, 2023 - Elsevier
Buildings account for over a third of end energy demand in many countries worldwide.
Modelling this demand accurately marks the first step in producing forecasts that can help …

Triz method for urban building energy optimization: Gwo-sarima-lstm forecasting model

S Zheng, S Liu, Z Zhang, D Gu, C **a, H Pang… - arxiv preprint arxiv …, 2024 - arxiv.org
With the advancement of global climate change and sustainable development goals, urban
building energy consumption optimization and carbon emission reduction have become the …

Creating synthetic energy meter data using conditional diffusion and building metadata

C Fu, H Kazmi, M Quintana, C Miller - Energy and Buildings, 2024 - Elsevier
Advances in machine learning and increased computational power have driven progress in
energy-related research. However, limited access to private energy data from buildings …

What-if: A causal machine learning approach to control-oriented modelling for building thermal dynamics

F Jiang, H Kazmi - Applied Energy, 2025 - Elsevier
Operational optimization of buildings can improve efficiency, and reduce costs and
emissions. This optimization typically relies on a model of the building thermal dynamics …

Forecasting price spikes in day-ahead electricity markets: techniques, challenges, and the road ahead

S Sheybanivaziri, J Le Dréau, H Kazmi - 2024 - openaccess.nhh.no
Due to the increase in renewable energy production and global socioeconomic turmoil, the
volatility in electricity prices has considerably increased in recent years, leading to extreme …

Introducing the Cool, Quiet City Competition: Predicting Smartwatch-Reported Heat and Noise with Digital Twin Metrics

C Miller, M Quintana, M Frei, YX Chua, C Fu… - Proceedings of the 10th …, 2023 - dl.acm.org
The productivity and satisfaction of humans in the built environment is impacted significantly
by their exposure to high temperature and various noise sources. This paper outlines the city …

Data science skills for the built environment: Lessons learned from a massive open online Python course for construction, architecture, and engineering

C Miller, C Tan - E3S Web of Conferences, 2024 - e3s-conferences.org
It's not just the models, techniques, or technologies that improve building performance; the
digital skills of built environment professionals also play a significant part. The deluge of …

Building energy load profile prediction

A Milá Murillo - 2024 - upcommons.upc.edu
The rising demand for sustainable energy management necessitates precise planning and
modeling of building energy consumption. This thesis develops a comprehensive machine …

Event-Based Energy Impact Tracking and Forecasting with Limited Measurements for Rooftop Units

MR Brambley - 2024 - search.proquest.com
Packaged air conditioning units and heat pumps, also known as rooftop units (RTUs), are
responsible for almost 133 billion kWh of electricity usage annually on site for space cooling …

[LIVRE][B] Metamodeling of Energy and Operational Carbon in Detached Accessory Dwelling Units

P Pape - 2022 - search.proquest.com
The rapidly escalating cost of housing has created a crisis in the United States that stems
from a lack of housing supply, which is exacerbated by single-family zoning. While revising …