In developed countries, buildings are involved in almost 50% of total energy use and 30% of
global green-house gas emissions. Buildings' operational energy is highly dependent on …

Buildings have a significant impact on global sustainability. During the past decades, a wide
variety of studies have been conducted throughout the building lifecycle for improving the …

In order to meet the ambitious emission-reduction targets of the Paris Agreement, energy
efficient transition of the building sector requires building retrofit methodologies as a critical …

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 …

Statistical models can be used as surrogates of detailed simulation models. Their key
advantage is that they are evaluated at low computational cost which can remove …

In most of the countries, buildings are often one of the major energy consumers, leading to
the necessity of achieving sustainable building designs, and to the mandatory use of …

The utilization of machine learning (ML) techniques is increasingly prevalent in the domain
of building performance evaluation. This trend is primarily driven by ML's capacity to capture …

Within the residential building sector, the air-conditioning (AC) load is the main target for
peak load shifting and reduction since it is the largest contributor to peak demand. By …

The design of renewable energy systems for Nearly Zero Energy Buildings (NZEB) is a
complex optimization problem. In recent years, simulation-based optimization has …

Surrogate models can emulate physics-based building energy simulation with a machine
learning model trained on simulation input and output data. The trained model is extremely …