Probabilistic criteria for power system expansion planning

Abstract

This paper presents a new methodology to power system expansion planning using probabilistic criteria. A selecting process for capturing the best expansion alternatives is proposed bearing in mind the application of different reliability evaluating models, which follow a hierarchical procedure. The state enumeration technique and the non-sequential Monte Carlo simulation are utilized basically as filters. The pseudo-chronological Monte Carlo simulation is then used to evaluate, in detail, the expansion costs of the previously selected alternatives. The major contribution is to show how traditional procedures and criteria should be adapted to the new competitive environment, where the minimum cost expansion planning has to be achieved considering the reliability worth. An expansion study of the MRTS-modified IEEE reliability system is carried out in order to demonstrate the efficiency of the proposed methodology.