The Kalman filter (KF) is a popular state estimation technique that is utilized in a variety of
applications, including positioning and navigation, sensor networks, battery management …

In today's era, transition of the conventional power grid towards smart grid is taking place by
Wide Area Measurement system's real time monitoring protection and control …

Cyber-physical attacks are the main substantial threats facing the utilization and
development of the various smart grid technologies. Among these attacks, false data …

This paper introduces for the first time, to our knowledge, a framework for physics-informed
neural networks in power system applications. Exploiting the underlying physical laws …

Power system dynamic state estimation (DSE) remains an active research area. This is
driven by the absence of accurate models, the increasing availability of fast-sampled, time …

Dynamic state estimation (DSE) accurately tracks the dynamics of a power system and
provides the evolution of the system state in real-time. This paper focuses on the control and …

In this paper, the state estimation problem is investigated for a kind of time-delayed artificial
neural networks subject to gain perturbations under the adaptive event-triggering scheme …

This paper is concerned with the issues of finite-time distributed resilient state estimation
subject to hybrid cyber-attacks. The information exchanges among estimators are governed …

Next-generation wireless communication and networking technologies, such as sixth-
generation (6G) networks and software-defined Internet of Things (SDIoT), make cyber …

Parameter Identification plays an important role in electric power transmission systems.
Existing approaches for parameter identification tasks typically have two limitations:(1) They …