The current trend indicates that energy demand and supply will eventually be controlled by
autonomous software that optimizes decision-making and energy distribution operations …

Abstract Machine learning (ML) and deep learning (DL) have enabled algorithms to
autonomously acquire knowledge from data, facilitating predictive and decision-making …

The efficiency, flexibility, and resilience of building-integrated energy systems are
challenged by unpredicted changes in operational environments due to climate change and …

Electric vehicles (EVs) are playing an important role in power systems due to their significant
mobility and flexibility features. Nowadays, the increasing penetration of renewable energy …

Advanced controls have attracted increasing interests due to the high requirement on smart
and energy-efficient (SEE) buildings and decarbonization in the building industry with …

With population increases and a vital need for energy, energy systems play an important
and decisive role in all of the sectors of society. To accelerate the process and improve the …

This article presents a review of current advances and prospects in the field of forecasting
renewable energy generation using machine learning (ML) and deep learning (DL) …

Artificial intelligence techniques lead to data-driven energy services in distribution power
systems by extracting value from the data generated by the deployed metering and sensing …

With a rapid growth of Integrated Energy System (IES) in various scenarios, researches on
IES have attracted extensive attention in the last few decades. Inspired by the ever …

Reducing CO 2 emissions using biomass is gaining popularity as an environmentally
friendly strategy. Due to high growth rates, low production costs, and ability to withstand …