Distributed Architecture of Power Grid Asset Management and Future Research Directions

Abstract

With the continuous expansion of the power system scale, the requirements of the power system intelligence are getting higher and higher and the power grid fault diagnosis has been made to become the focus of the power system research. In this paper, the research field of power grid fault diagnosis is reviewed, and the data sources and characteristics and data preprocessing are analyzed. Moreover, the diagnosis mechanism, characteristics and deficiencies of various fault diagnosis methods, the improvement results and future research direction are reviewed in recent years, and the design of online diagnosis system architecture mode are established. A new type of power system fault monitoring and networking method is proposed which is more concise and reliable than the traditional scheme. The power system fault diagnosis strategy based on knowledge representation and the fault diagnosis model with distributed architecture are structured which showed the efficiency is effectively improved. Finally, the problems faced by the power system fault diagnosis under the background of regulatory big data are discussed, and the development direction of the power grid fault diagnosis under this new situation is deeply analyzed.

The Future of Electrical Power Grids: A Direction Rooted in Power Electronics

“…A review on multilevel power management systems for future power grids is presented in [4], wherein benefits, drawbacks, challenges, and limitations are discussed. A forthcoming concept of power grids that includes a large-scale integration of distributed energy resources, ensuring autonomy and controllability in the production and consumption stages, is analyzed in [5]. The importance of blockchains, machine learning, and deep learning technologies for future power grids is presented in [6][7][8], demonstrating the importance of subjects such as security, cyber-physical attacks, and defense approaches.…”

A Novel Reduced-Order Analytical Fault Diagnosis Model for Power Grid

“…When a fault event occurs in a power grid, rapid and accurate fault diagnosis is important for efficient fault processing and ensuring reliable operation of the power grid. Generally, the existing methods for power grid fault diagnosis include expert systems, artificial neural networks, Petri nets, and analytical models [1][2][3][4][5]. The advantages and disadvantages of these methods are as follows.…”