Congestion management based roulette wheel simulation for optimal capacity selection: Probabilistic transmission expansion planning

Abstract

This paper proposes a single-stage probabilistic transmission expansion planning (TEP) methodology where apriory specification of candidate transmission lines capacity is not required. The proposed methodology involves: (i) minimization of the sum of the investment, expected demand not served (EDNS), expected generation not served (EGNS) and expected wheeling loss (EWL) costs to put together economic and reliability analysis on a single platform, (ii) probabilistic contingency analysis using Monte Carlo simulation (MCS), (iii) merit order dispatch of generators to minimizes operational cost of generators, (iv) a non-iterative DC load flow analysis to calculate EDNS, EGNS, and EWL, (v) a novel congestion management based roulette wheel selection method to calculate optimum capacity of the transmission lines, and (vi) genetic algorithm (GA) optimization method. The overall methodology has been implemented on a modified IEEE 5-bus test system. Simulations show an important result: addition of only new transmission lines is not sufficient to minimize EDNS.