Smart buildings play a crucial role toward decarbonizing society, as globally buildings emit
about one-third of greenhouse gases. In the last few years, machine learning has achieved …

With building electric demand becoming increasingly dynamic, and a growing percentage of
intermittent renewable power generation from solar photovoltaics and wind turbines, the …

Recent advances toward sustainable cities have promoted the concept of near-zero energy
consumption. A Positive Energy Building (PEB) model has been developed by the European …

Smart cities attempt to reach net-zero emissions goals by reducing wasted energy while
improving grid stability and meeting service demand. This is possible by adopting next …

Implementing an efficient control strategy for heating, ventilation, and air conditioning
(HVAC) systems can lead to improvements in both energy efficiency and thermal …

In recent years, digitalisation has rendered machine learning a key tool for improving
processes in several sectors, as in the case of electrical power systems. Machine learning …

A multi-stage mechanism for flexibility-oriented energy management (FOEM) of the
distribution system is developed in this article, which main novelty is providing the flexibility …

Accurate building energy consumption prediction plays an important role in building energy
management and energy policy. However, traditional prediction methods of building energy …

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 …

Determining a proper trade-off between energy consumption and indoor thermal comfort is
important for HVAC system control. Deep Q-learning (DQN) based multi-objective optimal …