In an increasingly digital world, there are fast-paced developments in fields such as Artificial
Intelligence, Machine Learning, Data Mining, Digital Twins, Cyber-Physical Systems and the …

Buildings consume a significant amount of energy throughout their lifecycle; Thus,
sustainable energy management is crucial for all buildings, and controlling energy …

Buildings in cities consume 30 to 70% of the cities' total primary energy. Retrofitting the
existing building stock to improve energy efficiency and reduce energy use is a key strategy …

As an unsupervised-learning data-driven model, Generative Adversarial Networks (GANs)
have recently attracted a lot of attention for various applications. There is potential to apply …

Small and medium-sized commercial buildings can be retrofitted to significantly reduce their
energy use, however it is a huge challenge as owners usually lack of the expertise and …

US commercial buildings consumed around 18% of total primary energy in 2017 and a 2.23
EJ increase is expected by 2050. Energy-related data for commercial buildings can be used …

This work describes the development of a community-scale energy model for a mixed-use
low-income community located in Huntington Beach, CA. An accurate community-scale …

Measurement uncertainty is a key component in the overall uncertainty calculation for
Measurement and Verification (M&V) projects. However, in some cases, it is reduced to …

Over the past decade, the building energy research community has increasingly focused on
urban-scale models. The shortcomings of analyzing isolated buildings in an urban context …

In this paper, an efficient Bayesian-Emulator approach is developed and applied to identify
unknown input parameters for detailed energy models for existing buildings. The new …