Study On Economic Dispatch Of Power System With Wind Farm Basrd On Wind Power Forecasting

In modern society,the demand for electricity is increasing sharply,but with the one-time energy depletion caused by traditional thermal power and air pollution are becoming increasingly serious,wind power and other renewable energy power generation has been paid more and more attention.Wind power is a kind of clean and pollution-free energy,and it can be recycled.It is effective that wind power can improve the current energy structure,save primary energy and promote the construction of environment-friendly economy.However,because of the intermittent and random nature of wind energy,it may bring a lot of adverse effects to the traditional power system when wind power is connected to a large scale.Therefore,it is conductive to the formulation optimization of unit commitment,power trading strategy plan and the normal operation of the power system to study the short wind power forecasting and the wind power economic dispatch.This paper firstly analyzes the characteristics of wind power generations,it also qualitatively discusses the influence of wind speed,temperature,pressure,humidity,air density and other weather information on the wind power,which provides a reference on the input parameter for the prediction model.Then it analyzes the impact of wind roughness,topography and wake effect on wind power.At the end,the influence of wind power to the power quality of electric power system is analyzed,and the mechanism of the generation of the power quality is described in detail.Due to the randomness and uncertainty of wind power,it is necessary to predict the short-term wind power for reducing the adverse effects of wind power on power system and helping electric power dispatching departments to manage the power system.Single prediction model has lower accuracy and reliability,therefore the BP neural network and support vector regression are combined together to predict the wind power.A new optimal weighting factor is applied to the predicting model in this paper,and the results show that this method can improve the accuracy and reliability of the prediction system.On the basis of short term forecast of wind power,the dynamic economic dispatch of power system with large scale wind farm integration is studied.The scheduling cycle is 24h,and the objective function is the sum of the fuel cost of thermal power unit and wind power generation cost.The PSO algorithm is used to solve the optimization problem,the results show that the grid connected wind power can reduce the cost of power generation.The wind power should be keep in the maximum state in the dynamic economic dispatch of power system,it can reduce the operation cost of power system,and can reduce the environmental pollution caused by thermal power units.Accurate short-term prediction of wind power is conducive to the wind farm output bidding,and dispatching department can adjust the traditional power grid scheduling strategy according to the prediction results to enhance the power grid regulation.It is very important to study the short-term forecasting of wind power and economic dispatch considering wind power grid connection,which is of great significance to improve the utilization of wind power.