State Estimation and Fault Diagnosis of Energy Systems Based on Artificial Intelligence

Introduction

Artificial Intelligence (AI) techniques in the domain of state estimation and fault diagnosis within energy systems has emerged as a pivotal area of research with broad-reaching implications. This special issue seeks to provide a comprehensive platform for exploring the application of AI methodologies in enhancing the accuracy, resilience, and efficiency of state estimation and fault diagnosis processes across diverse scenarios within the realm of energy systems. By gathering innovative research contributions, the focus of this issue is to catalyze advancements that underpin the resilience and efficacy of energy system operations in the face of evolving technological landscapes and operational demands.

Keywords

State Estimation, Fault Diagnosis, Energy Systems, Artificial Intelligence, Energy Generation, Distribution Networks, Renewable Energy, Smart Grids, Energy Storage Systems

Sub-topics

AI-based state estimation techniques for energy generation systems

Application of AI algorithms in fault diagnosis of distribution networks

Data-driven modeling for state estimation in renewable energy systems

AI-enabled fault detection in smart grid infrastructure

 Integration of AI algorithms for state estimation and fault diagnosis in energy storage systems

Case studies and real-world applications of AI in enhancing the performance of energy systems

Challenges and future directions in leveraging AI for state estimation and fault diagnosis in energy systems