Probabilistic load flow calculation with Latin hypercube sampling applied to grid-connected induction wind power system

Abstract

This paper investigates the probabilistic load flow (PLF) calculation with Latin hypercube sampling (LHS) technique for grid-connected induction wind power system. Considering the uncertainties of both loads and wind power outputs, firstly, probabilistic models of main components in wind power generation system are introduced. A combined iterative method for deterministic load flow is then extended to the PLF calculation for grid-connected induction wind power system, which facilitates simultaneous correction for the slip of induction generator and the nodal voltages during all iterations. Furthermore, to overcome the drawback of simple random sampling like excessive time consumption, LHS is combined with Monte Carlo simulation to execute the PLF. Finally, the proposed method is verified by an IEEE 14-bus system modified to include 20 wind turbines. Simulation results confirm the efficiency of the proposed method and reveal the impact of wind farm capacity on PLF results.