Network Reconfiguration for Searching Maximum Loading Capacity Radial Network: An Efficient Graph Theory-Based Machine Learning Approach

Abstract

This study presents a unique method for network reconfiguration for Searching Maximum Loading Capacity Radial Network from an interconnected meshed network using continuation power flow. The network reconfiguration outcomes are also evaluated for various graph theory approaches presented in the literature. The combined graph theory and machine learning methods are used to determine the best sectional switch position. The system’s radiality is verified using graph theory. The recommended technique is tested on a 30-node mesh network with 41 sectional switches. The results demonstrate that the distribution system can manage a higher connected load using the suggested Bayesian-Ridge approach while lowering total active and reactive power losses.

Keywords:

• Bayesian ridge model
• Distribution system
• Graph theory
• Machine learning
• Maximum loadability
• Network reconfiguration

DISCLOSURE STATEMENT

No potential conflict of interest was reported by the author(s).

Additional information

Notes on contributors

Sravan Kumar Gunturi

Sravan Kumar Gunturi received his BTech degree from Sasi Institute of Technology and Engineering Tadepalligudem, Andhra Pradesh, India in electronics and communication engineering in 2009. He received the MTech degree with specialization in embedded systems from BVC Engineering College, Odalarevu, India, in 2012 and PhD from the Department of Electronics and Instrumentation Engineering, National Institute of Technology, Nagaland, India. His areas of interest are machine learning, deep learning, and the internet of things. Email: [email protected]

Dipu Sarkar

Dipu Sarkar received his BTech in electrical engineering in 2003 from University of Kalyani, WB, India. He received MTech with specialization of electrical power systems from University of Calcutta, India, in 2007 and PhD from the Department of Electrical Engineering, Bengal Engineering and Science University, Shibpur, India (presently known as Indian Institute of Engineering Science and Technology [IIEST]) in 2013. Currently, he is an associate professor in the Department of Electrical and Electronics Engineering of National Institute of Technology, Nagaland, India. His fields of interest are power systems operation and control, power systems stability, soft computational applications in power systems and smart grids, grid integrated renewable energy, service restoration and protective relay coordination. Corresponding author. Email: [email protected]