An Outage Risk Oriented Dynamic Distribution Network Reconfiguration Methodology Considering the Effects of Weather Conditions on Power Line Failure Rate

Abstract

A dynamic network reconfiguration methodology considering time-varying weather conditions is proposed. The aim of the proposed methodology is to minimize outage risk. To fully reflect actual weather severity, a classification method for weather states based on weather variables analysis is presented. Considering time-varying nature of weather, an approach to determine the optimal time for reconfiguration by comparing reliability change between adjacent intervals is provided. Then, applying the Quantum Genetic Algorithm to solve reconfiguration optimization problem is introduced. Simulation results on the IEEE 33-node test systems show that the proposed dynamic reconfiguration method can reduce distribution network's outage risk. In addition, weather conditions have impacts on outage risk of distribution network and should be considered in reconfirmation problems.

Keywords:

• dynamic reconfiguration
• distribution network
• weather conditions
• time-varying
• failure rate
• restoration time

Additional information

Notes on contributors

Yingjun Wu

Yingjun Wu received his B.S. from Nanchang University, Nanchang, China, in 2007, his M.S. from Southeast University, Nanjing, China, in 2009, and his Ph.D. from Politecnico di Torino, Torino, Italy, in 2013, all in electrical engineering. He is currently an Associate Professor with Nanjing University of Posts and Telecommunications, Nanjing, China. His fields of interest are power system operation and optimization in the context of multi-infrastructure systems.

Ciwei Gao

Ciwei Gao received his B.S. from the North China Electrical Power University, Beijing, China, in 1999, his M.S. from Wuhan University, Wuhan, China, in 2002, his Ph.D. from the Politecnico di Torino, Torino, Italy, in 2006, and his Ph.D. from Shanghai Jiaotong University, Shanghai, China, in 2007. He is currently a Professor with the School of Electrical Engineering, Southeast University, Nanjing, China. His current research interests include V2G, DSM, power market, and power system planning.

Yi Tang

Yi Tang received his Ph.D. in electrical engineering from Harbin Institute of Technology, Harbin, China, in 2006. He is currently an Associate Professor with Southeast University, Nanjing, China. His current research interests include power and communication composited system power system stability analysis and control, and renewable energy generation.

Tao Huang

Tao Huang received his Master's from Shanghai Jiao Tong University, Shanghai, China, in 2007, his Ph.D. from Politecnico di Torino, Torino, Italy, in 2011, both in electrical engineering. He is currently a Senior Research Fellow with the Department of Energy, Politecnico di Torino. His current research interests include global system science and complex system science and their applications to energy security and policy decision-making.