Increasing energy efficiency in wastewater treatment plants (WWTPs) is becoming more
important. An emerging approach to addressing this issue is to exploit development in data …

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 …

A critical review of the existing Internal Combustion Engine (ICE) modeling, optimization,
diagnosis, and control challenges and the promising state-of-the-art Machine Learning (ML) …

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

It has been proven that advanced building control, like model predictive control (MPC), can
notably reduce the energy use and mitigate greenhouse gas emissions. However, despite …

The energy consumption of major equipment in residential and industrial facilities can be
minimized through a variety of cost-effective energy-saving measures. Most saving …

Demand Response (DR) has gained popularity in recent years as a practical strategy to
increase the sustainability of energy systems while reducing associated costs. Despite this …

A model predictive control system with adaptive machine-learning-based building models
for building automation and control applications is proposed. The system features an …

Managing supply and demand in the electricity grid is becoming more challenging due to
the increasing penetration of variable renewable energy sources. As significant end-use …

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 …