Transmission Network Expansion Planning Based on Dependent-chance Bi-level Programming Method

Transmission Network Expansion Planning method considers return rate based on Dependent- chance bi-level programming method is presented in the paper. The upper level objective of the model is maximum realization rate of return rate being bigger than one realization level. The lower level programs have two sub-problems, one is social profit maximization in normal operation, the other is load shedding being lower than one realization rate in N-1 operation environment. Monte-Carlo method is adopted to mimic uncertain parameters. A hybrid algorithm combining Genetic algorithm and prime-dual interior point method is adopted to solve the proposed model. 18-bus system has been tested in the paper, the results prove proposed method is valid.