Abstract
This paper proposes a new method to assess the reliability of closed-ring grids by combining the total loss of continuity approach and the classical Monte Carlo simulation. The proposed method is called the Modified Monte Carlo Simulation (MMCS). The MMCS method is tested by Roy Billinton Test System (RBTS) Bus-2 and Bus-4 in three different scenarios: radial, open-ring, and closed-ring. Besides, the method proposed is applied to a real 6-bus closed-ring distribution system. The sensitivity analysis based on fuzzy logic is applied to determine the uncertainties associated with the reliability input data. It is shown that the MMCS method is appropriate to assess the reliability of both open-ring and closed-ring systems, and the sensitivity analysis is crucial to draw the real picture of reliability assessment, and an essential tool for power utilities to determine the most risk parameters that significantly deteriorate system reliability.
Disclosure statement
The authors declare that they have no conflicts of interest. In addition, all authors are involved in developing the concept to make the article error free technical outcome for the set investigation work.
Additional information
Notes on contributors
Mohammed Wadi
Mohammed Wadi received the BSc and MSc in Electrical Engineering degrees from The Islamic University of Gaza, Palestine, in 2006 and 2012, respectively. He received his Ph.D. degree from Yildiz Technical University, Istanbul, Turkey, in 2017. In 2006, he worked as a lecturer at the University College of Science and Technology, Palestine. In 2007, he worked as an Electrical Engineer at the Ministry of Higher Education, Palestine. In 2008-2012, he worked as a Director of Control & Operation Dept. at Gaza 220/20 kV Power Plant, Palestine. He is now working as an Assistant Professor at the Department of Electrical & Electronics Engineering, Istanbul Sabahattin Zaim University, Istanbul in Turkey. His main field of interest is in the reliability assessment of power systems. In addition, his areas of research interest are applications of machine learning in power systems, distributed generation, smart grids, renewable energy, optimal control, fuzzy control, and Monte Carlo.
Mustafa Baysal
Mustafa Baysal received the BSc, MSc, and Ph.D. degrees from Yildiz Technical University, Department of Electrical Engineering, 1998, 2001, and 2008, respectively. From 2009 to 2011, he was a visiting researcher at UW, Madison, USA. Currently, he is an Assistant Professor in the Electrical Engineering Department of Yildiz Technical University. His current research interests include microgrids, smart grids, distributed generation, power quality, and machine learning applications for power systems.
Abdulfetah Shobole
Abdulfetah Shobole received the B.Sc. degree in Electrical and Computer Engineering from Jimma University, Jimma, Ethiopia in 2009, the M.Sc. degree in Electrical Power Engineering from Addis Ababa Institute of Technology, Addis Ababa, Ethiopia in 2011, and the Ph.D. degree in Electrical Power Plants from Yildiz Technical University, Istanbul, Turkey in 2017. He is currently an Assistant Professor in the Electrical and Electronic Engineering Department in Istanbul Sabahattin Zaim University, Istanbul, Turkey. His research interests are smart grid, renewable energy resources, power system protection, and automation.