Chance Constraints Model Of High Energy-Consuming Enterprises To Participate In Wind Power Consumptive

In the21st century, with the greenhouse effect, and a new awareness of traditional fossil fuels. Countries in the world for the development of clean, safe and sustainable energy research into new more enthusiasm. Wind resource-rich storage in nature, is a clean, safe and environmentally friendly new energy. And do not emit pollutants on the environment and greenhouse gas hazards in wind power generation process. Due to the nature of wind are volatile, random, intermittent and seasonal characteristics, and therefore does not have the conventional energy wind power FM, peaking capabilities. When large-scale wind power connected to the grid at peak load capacity is not enough, the safe and stable operation of the grid system will bring a serious security risk. So when the wind power grid systems require peaking shall reserve sufficient margin. When excess peaking capacity is wasteful system, too little will affect the security and stability. Improve the prediction accuracy of wind power peaking capacity can be able to adjust the size of the system.In this paper, to improve the level of wind power consumptive and maintenance of the grid system safe and stable operation, adopting prediction method of empirical mode decomposition and neural network based on a combination of wind power output predicted. By comparing the traditional BP neural network prediction method improved the accuracy of prediction. Wind could affect the accuracy of predicted stability of the grid system is running in a great extent. Short-term load forecasting accuracy, it is possible to set aside an appropriate grid system peaking capacity to make a reference. Short-term load forecasting based on support vector machine can cope with more disturbance factors, the forecast has improved accuracy.In order to solve the problems caused due to lack of wind power peaking consumptive difficult, combining the current situation is characterized by high-energy-consumption enterprises and wind farm operators, the proposed high-energy-consuming enterprises to participate in the grid wind power consumptive of local consumption patterns. The establishment of a high energy consumption enterprises cooperating with the wind farm model, through the price mechanism and the power grid peak load design constraints to guide the daily electricity load of high energy-consuming enterprises to follow the wind power output fluctuations and adjust the size of the grid peak load electricity. Balance wind power fluctuations and reduce the peak power load of poor aim. To make a favorable decision makers the chance constrained programming framework based on the results meet certain confidence level to provide guidance.