| With the increment of capacity, wind farms have more and more response to the power grid. The random energy output of wind power generators and their different properties, which compared with traditional generators, make a great influence on the distribution of active and reactive power flow and power system voltage stability. This paper is mainly about the random energy output of wind farms and discusses the influence of wind farms on power system based on probabilistic load flow models.This paper applies a new method—the stochastic response surface method (SRSM) to analyze the impact of wind farms on uncertainties of power system. Polynomial expressions between responses of system and parameters can be established by this method. Compared with the traditional approaches, the presented method can obtain statistical information with less simulation time. A probabilistic load flow model and assessment of voltage stability model based on this method is established. A simulation conducted for IEEE-14bus system integrated with wind farms, demonstrates the validity of the suggested method.On the basis, the method was introduced to solve the problem of multi-objective reactive power optimization of wind farm based on a probabilistic system model. This paper, combining probabilistic system model with Pareto-based Multi-Objective Particle Swarm Optimization (MOPSO) algorithm, establishes a mathematic model of reactive power optimization, which regarding the minimization of bus voltage beyond limits probability and expectation value of active power losses and the maximization of expectation value of load margin as objective function. A simulation conducted for IEEE-14bus system integrated with wind farms reveals that the proposed method is more reasonable than traditional determine methods. The proposed method can overall consider effects of wind speed randomness, so that a more reasonable reactive power dispatch scheme could be found. |
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