Tight Semidefinite Relaxation for Interval Power Flow Model Based on Multi-Dimensional Holomorphic Embedding Method
Yuge Sun, Tao Ding, Ming Qu, Fangxing Li, Mohammad Shahidehpour
Abstract
In order to quantify the impact of uncertainties on power systems resulted from renewable energy, a novel interval power flow method based on multi-dimensional holomorphic embedding method (MDHEM) and tight semidefinite relaxation technique are proposed. First, the MDHEM is used to address the spatial correlation of renewable energy basis, and the analytical expressions of bus voltages and active branch flows are derived. Second, the general interval power flow (IPF) model can be cast as a box constrained polynomial optimization problem. Third, a tight semidefinite relaxation is designed to solve this special optimization problem. Simulation results on several large-scale test systems show the effectiveness and computational tractability of the proposed model.