Enhancing and evaluating smart power distribution system reliability: a distributed sensor monitoring network approach

Abstract

Reliability standards are followed in power system industries as a series of requirement from planning to operation and this necessitates evaluating, improving and reporting reliability indices of the power systems to the regulators on a regular basis. Eighty percent of the power system outages happen due to disturbances caused in the distribution power system. Recent developments in smart grid technologies demonstrate how communication technologies can be used to improve the reliability of the distribution power system. In this research, a distributed sensor network architecture is projected for monitoring the distribution system. A dedicated communication protocol “ALARM” for distributed sensor monitoring network communication is briefly discussed. Furthermore, a Hidden Markov Model (HMM) based local event detection mechanism is proposed to improve the reliability of the distribution power system. The proposed system has the capability of detecting faults locally with a minimum delay time. It is shown that such a local event detection system can improve the reliability of the distribution power system in many aspects. Further, a novel methodology to evaluate the reliability of cyber physical power system is proposed in this research. This work incorporates power component failure, automation component failure, communication failure, communication delay and cyber-attacks to develop a comprehensive equipment level reliability model. From the 36 possible states, a 12-state model is derived to aid the component level reliability analysis. Furthermore, for large network level reliability evaluation purpose, a reduced 2 state model is also obtained. Depending on the application in the power system, smart component categorized into three groups and corresponding 2 state models are obtained for each category. Finally, sensitivity analysis is carried out to evaluate the impact of cyber-failure and cyber-attacks on the reliability of the smart component.