Two-Stage Stochastic Approach for Reference Network Considering Uncertain Reliability

Abstract

With the increasing load level in the future, the optimal capacity of each transmission line is an important factor which can protect the power systems with contingency events. In this paper, a two-stage stochastic model is proposed to determine the optimal transmission line capacities based on reference network model , in which the generators and loads are the same as those in the existing transmission system and the expected interruption cost (EIC) under contingency events should be respected. It can guide the transmission network planning. The objective function is to minimize the generation cost, the investment cost of transmission lines and the EIC. In the first-stage, the initial power flow and generated output without contingency events is calculated. In the second-stage, the optimal line flow and generated output under contingency events is calculated. The large-scale problem can be divided into two parts: 1) the master problem; 2) a series of sub problems considering contingency. So the model can be solved by using a decomposed algorithm based on Bender’s decomposition. The model was applied to IEEE 118-node system for verification and efficiency.