Fueled by big data, powerful and affordable computing resources, and advanced algorithms,
machine learning has been explored and applied to buildings research for the past decades …

Increasing the energy efficiency of the built environment has become a priority worldwide
and especially in Europe. Because of the relatively low turnover rate of the existing built …

Accurate building energy prediction plays an important role in improving the energy
efficiency of buildings. This paper proposes a homogeneous ensemble approach, ie, use of …

Accurate savings estimations are important to promote energy efficiency projects and
demonstrate their cost-effectiveness. The increasing presence of advanced metering …

In late 2019, ASHRAE hosted the Great Energy Predictor III (GEPIII) machine learning
competition on the Kaggle platform. This launch marked the third energy prediction …

A significant portion of energy consumption occurs in buildings today. Accurate and easy-to-
implement methods are needed to calculate building energy consumption for a wide range …

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 …

The complexity of occupant behavior is one of the major contributors to uncertainty in
building performance simulation. Agent-based modeling (ABM), a computational simulation …

Methods to obtain accurate estimations of the savings generated by building energy
efficiency interventions are a topic of great importance, and considered to be one of the keys …

This paper describes an open data set of 3,053 energy meters from 1,636 non-residential
buildings with a range of two full years (2016 and 2017) at an hourly frequency (17,544 …