A Central Limit Theorem-Based Method for DC and AC Power Flow Analysis Under Interval Uncertainty of Renewable Power Generation

Abstract

This paper proposes a central limit theorem-based method (CLTM) to overcome the conservatism of interval DC and AC power flow analysis under uncertainty of renewable power generation. Interval DC power flow (IDCPF) models are solved by expressing the bus angle and active transmission power as linear combinations of interval nodal power injections, and then the central limit theorem is applied to obtain high-confidence intervals of DC power flow variables. Interval AC power flow (IACPF) models are solved by first applying the optimizing-scenarios method to acquire more accurate affine arithmetic forms of the power flow variables defined according to linear combinations of nodal power injections, and then high-confidence intervals of AC power flow variables are obtained via the central limit theorem. In addition, a criterion formulation is established to evaluate the errors of interval power flow methods. The results of simulations validate the effectiveness and superiority of the proposed method relative to the performances of previously established methods, including the Monte Carlo simulation, affine arithmetic-based method and optimizing-scenarios method.