Research Of Power System Intraday Dispatch Model Considering Uncertainty Of Wind Power Prediction

With the increasing depletion of fossil fuels and environmental pollution problems becoming increasingly prominent, new energy which give priority to wind power generation have been vigorously developed. However, the uncertainty of wind power prediction brings enormous pressure on intraday scheduling system and AGC regulation, especially for the large-scale wind farms connected to the power grid. Under the existing prediction accuracy, how to apply the prediction results effectively and make the uncertainty be included in the process of optimal dispatching is the hot spot issue for a long time. Based on the analysis of wind power prediction error, this paper establish power system intraday dispatch model which considering uncertain prediction from wind generators.Firstly, based on fuzzy theory, dynamic fuzzy dispatching model which considering wind power was built. In order to describe the characteristics of wind power output better, wind power output were fuzzified through defining gauss membership function, then this bi-objective optimization problem was reformulated into an equivalent clear optimization problem by means of the fuzzy satisfaction maximum-minimum technique. An example which using matlab programming demonstrates the effectiveness of the model. The impact of the triangular, trapezoidal, Gaussian membership function on the results are also compared,Gaussian membership function describing the uncertainty of the wind power has more advantages. The simulation results of power system with wind farm demonstrate that the proposed bi-objective scheduling optimization model is more reasonable than the single-objective optimization goal.。Probabilistic optimal dispatching model based on multi-scenasio is also developed in this paper. The range of possible fluctuations of wind power is discretized into multi-scene in this model, and on this basis the scenes probability can be get by discretizing wind power prediction error distribution curves, at the same time with considering the correlation of the prediction error of the adjacent time segment in the time scale. By means of leading probability adjustment costs into objective function, the optimization result can consider the cost due to the fluctuation of wind power. The rationality and effectiveness of the proposed method is verified by testing and demonstrating IEEE-30bus system with a wind farm.Finally, the two modeling ideas is compared from the complexity of modeling, solving, decision-making, practical provide a reference for economic dispatch of power system with wind power.