This paper describes a generic methodology to develop mathematical and computational
models of different components of the smart grid architecture model (SGAM). The SGAM …

As the deployment of Internet of Things (IoT) is experiencing an exponential growth, it is no
surprise that many recent cyber attacks are IoT-enabled: the attacker initially exploits some …

Federated learning (FL) is a kind of privacy-awaremachine learning, in which the machine
learning models are trained on the users' side and then the model updates are transmitted to …

The smart grid is arguably one of the most complex cyber‐physical systems (CPS). Complex
security challenges have been revealed in both the physical and the cyber parts of the smart …

Residential short-term energy consumption forecasting plays an essential role in modern
decentralized power systems. The rise of innovative prediction methods able to handle the …

In the coming years, cities face an urban transition in order to manage their resources, public
administration, safety, regional economics, education, innovation, health, culture, and …

This paper presents an energy management strategy for day-ahead scheduling of
networked microgrids and is named as nested energy management system. In the proposed …

Forecasting short-term residential energy consumption is critical in modern decentralized
power systems. Deep learning-based prediction methods that can handle the high variability …

The purpose of this survey is to present a critical overview of smart grid concepts, with a
special focus on the role that communication, networking and middleware technologies will …

Smart grid has emerged as the next-generation power grid via the convergence of power
system engineering and information and communication technology. In this article, we …