Internet usage has grown exponentially, with individuals and companies performing multiple
daily transactions in cyberspace rather than in the real world. The coronavirus (COVID-19) …

The use of machine learning and data-driven methods for predictive analysis of power
systems offers the potential to accurately predict and manage the behavior of these systems …

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 …

Automation in the power consumption system could be applied to conserve a large amount
of power. This chapter discusses the applications for the generation, transmission …

Smart grid integrates computer, communication, and sensing technologies into existing
power grid networks to achieve significant informatization-related advantages. It will provide …

Due to the widespread use of the Internet of Things (IoT), organizations should concentrate
their efforts on system security. Any vulnerability could lead to a system failure or …

As the world continues to seek sustainable and efficient energy solutions, the integration of
advanced technologies into smart energy grid management (SEGM) becomes a paramount …

Artificial neural networks are successfully used to solve a wide variety of scientific and
technical problems. The purpose of the study is to increase the efficiency of distributed …

The smart grid merges cyber-physical systems (CPS) infrastructure with information and
communication technologies (ICT) to ensure efficient power generation, smart energy …

The energy industry worldwide is today confronted with several challenges, including
heightened levels of consumption and inefficiency, volatile patterns in demand and supply …