Title :
Quantitative Transmission-System-Reliability Assessment
Author :
Chowdhury, Ali Asraf ; Koval, Don O.
Author_Institution :
California Indep. Syst. Operator, Folsom, CA, USA
Abstract :
Quantitative transmission-system reliability is a prerequisite in transmission-system planning and operation supplying industrial and commercial customer loads. A utility industry traditionally has relied on a set of deterministic criteria such as the widely used N - 1 criterion to guide transmission planning supplying all customer types, e.g., residential, agricultural, commercial, industrial, and sensitive high-tech electronic customers. The conventional deterministic planning criteria are based on the system planner´s experience and intuition which are lacking a formal and consistent framework for their development. Although easy to use and understand, due to inherent limitations, the deterministic criteria cannot realistically model the probabilistic nature of power-system behavior. Moreover, the application of deterministic criteria possesses the inherent risk of over/under investment in transmission-system-facility additions to meet the system load growth. Over the past two decades, different quantitative transmission-system-reliability techniques have been developed to accurately reflect the stochastic nature of a power-system behavior and assess its reliability performance. This paper illustrates applications of reliability models used to compute the reliability performance of a practical transmission system supplying industrial, commercial, and other customer types.
Keywords :
load management; power transmission planning; power transmission reliability; commercial customer loads; deterministic planning; industrial customer loads; power system behavior; practical transmission system; quantitative transmission system reliability; transmission system operation; transmission system planning; Industrial and commercial customers; probabilistic criteria; reliability performance indexes; reliability techniques; transmission-system planning;
Journal_Title :
Industry Applications, IEEE Transactions on
DOI :
10.1109/TIA.2009.2036505