Utilizing Bulk Electric System Reliability Performance Index Probability Distributions in a Performance Based Regulation Framework

Parameter distribution analysis and its potential utilization are relatively new concepts in bulk electric system (BES) reliability assessment and decision making. Sequential Monte Carlo simulation is used in this paper to assess the annual variability of BES reliability performance indices. The potential utilization of BES reliability performance index probability distributions is demonstrated by application to the performance based regulation (PBR) concept, proposed by policymakers involved in deregulating the electric power industry. Reliability performance measures such as SAIFI and SAIDI can be used as integral elements in a PBR mechanism to provide power utilities with economic incentives to maintain and improve service reliability, and at the same time to discourage them from sacrificing service reliability in the pursuit of economic objectives. The basic concepts of BES reliability performance index probability distributions associated with a PBR protocol are illustrated in this paper by application to the IEEE-RTS and RBTS using simulation results, and by application using actual historical reliability data