The paper's state-of-the-art review focuses on an in-depth evaluation of smart home energy
management systems which employ reinforcement learning-based methods to integrate …

Energy theft poses a significant challenge for all parties involved in energy distribution, and
its detection is crucial for maintaining stable and financially sustainable energy grids. One …

Predictions about solar power will have a significant impact on large-scale renewable
energy plants. Photovoltaic (PV) power generation forecasting is particularly sensitive to …

The advent of the sixth generation of mobile communications (6G) ushers in an era of
heightened demand for advanced network intelligence to tackle the challenges of an …

The rapid popularization of advanced metering infrastructure (AMI) smart meters produces
customer high-frequency energy consumption data. These data provide diverse options for …

As the use of deep learning models is increased in smart grid systems, especially in load
forecasting, supply-demand response, vulnerability detection, and finding abnormal …

A metaverse is composed of a physical-space and virtual-space, with the aim of having
users in both the virtual reality and the real world experience. Prioritization is essential, but it …

The users of home energy management systems schedule their real-time energy
consumption thanks to advancements in communication technology and smart metering …

Electricity theft comes with various disadvantages for power utilities, governments,
businesses, and the general public. This continues despite the various solutions employed …

There is an increasing demand for electricity on a global level. Thus, the utility companies
are looking for the effective implementation of demand response management (DRM). For …