Ten questions concerning data-driven modelling and forecasting of operational energy demand at building and urban scale
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 …
Modelling this demand accurately marks the first step in producing forecasts that can help …
Filling time-series gaps using image techniques: Multidimensional context autoencoder approach for building energy data imputation
Building energy prediction and management has become increasingly important in recent
decades, driven by the growth of Internet of Things (IoT) devices and the availability of more …
decades, driven by the growth of Internet of Things (IoT) devices and the availability of more …
The Building Data Genome Directory–An open, comprehensive data sharing platform for building performance research
The building sector plays a crucial role in the worldwide decarbonization effort, accounting
for significant portions of energy consumption and environmental effects. However, the …
for significant portions of energy consumption and environmental effects. However, the …
Introducing the Cool, Quiet City Competition: Predicting Smartwatch-Reported Heat and Noise with Digital Twin Metrics
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 …
by their exposure to high temperature and various noise sources. This paper outlines the city …
Enhancing classification of energy meters with limited labels using a semi-supervised generative model
In the energy domain, the classification of power meters has become an increasingly
significant area of interest, such as appliance identification and characteristics prediction …
significant area of interest, such as appliance identification and characteristics prediction …
Toward Unsupervised Energy Consumption Anomaly Detection
Abstract Existing high-performance Machine Learning models typically rely on large training
datasets with high-quality manual annotations, which are difficult to obtain in the case of …
datasets with high-quality manual annotations, which are difficult to obtain in the case of …
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 …
digital skills of built environment professionals also play a significant part. The deluge of …
[PDF][PDF] Detecting and Analyzing Agent Communication Anomalies in Distributed Energy System Control.
In Cyber-Physical Energy Systems (CPES), multi-agent systems are expected to perform a
variety of tasks. The increase in digital interconnections and distributed structures in CPES …
variety of tasks. The increase in digital interconnections and distributed structures in CPES …
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 …
modeling of building energy consumption. This thesis develops a comprehensive machine …