4.7 Article

Critical Components for Maintenance Outage Scheduling Considering Weather Conditions and Common Mode Outages in Reconfigurable Distribution Systems

Journal

IEEE TRANSACTIONS ON SMART GRID
Volume 7, Issue 6, Pages 2807-2816

Publisher

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TSG.2016.2551641

Keywords

Critical components; outage scheduling; reconfigurable distribution systems; severe weather; proportional hazard model

Funding

  1. Natural Science Foundation Key Program of China [51537010]

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This paper proposes a model for identifying critical components that affect the maintenance outage scheduling in reconfigurable distribution systems. The model considers critical factors such as prevailing severe weather conditions and component aging conditions, common mode outages, and repair rates in distribution systems. The effects of critical factors on forced outage rates of distribution system components are quantified by the proportional hazard model. A recursive sampling method is proposed to generate Monte Carlo scenarios with the given forced outage rate. In each scenario, the distribution system reconfiguration is optimized efficiently using a standard mixed-integer second-order cone program. Then absolute and relative criticality indices are calculated to describe the criticality of components. A new scenario is generated subsequently and the process is continued in the following iteration until the convergence condition is satisfied. The overall convergence of multiple scenarios is quantified by the coefficient of variation of criticality index. The final absolute and relative criticality indices are the average over multiple scenarios. The influence of component aging condition and forced outage characteristics, weather condition, and the system reconfiguration on component criticality for the maintenance outage scheduling is distinguished and exhibited in case studies. The case studies illustrate the effectiveness of proposed model and the solution method for identifying the critical components.

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