Transmission expansion planning based on Locational Marginal Prices and ellipsoidal approximation of uncertainties

This paper proposes an algorithm for transmission expansion planning (TEP) which minimizes the congestion surplus calculated from optimized nonlinear (AC) Optimal Power Flow (OPF) and Locational Marginal Prices (LMPs). Uncorrelated and correlated uncertainties related to operating conditions of the future transmission network and expected costs of the submitted energy bids to the energy market are constrained by bounding hyper-ellipsoid around base case AC OPF solution, with assumption of additive uncertainties. Perturbed uncertain points inside a hyper-ellipsoid are selected by proposed quasi-random sampling algorithm. For these points, the linearized OPF around base case AC OPF solution is proposed. The Genetic Algorithm (GA) does selection of lines and years for transmission expansion, where the increments of the fitness function are calculated by proposed linearized AC OPF model. The results and practical aspects of the proposed methodology are illustrated on 12- and 118-bus test power system examples.