Application Of Data Fusion Technology In Wind Power Enterprise Information System

The rapid development of science and technology at the same time,energy consumption is also growing rapidly,leading to fossil energy depletion.Therefore,wind energy as a kind of clean energy,get extensive development and utilization.In our large-scale use of wind energy at the same time,there have been many problems,such as wind power grid,due to wind energy instability on the stability of the entire power system operation impact.So far,the instability of wind energy has limited the development of wind power to a great extent.Wind power enterprise information system is the most important part of the wind power credit forecast,because the instability of wind energy,resulting in wind power fluctuations and intermittent and anti-peak characteristics to achieve accurate prediction of wind power,the power grid can be based on predicted power,To ensure the stability of the power grid,but also can maximize the efficiency of the use of wind energy,to avoid the wind power instability and scheduling problems resulting in wind power can not make the best use.Reasonable wind power enterprise information system can help the power grid to complete the credit scheduling problem,while promoting the utilization of wind energy,reducing the consumption of fossil fuels.In this thesis,the data fusion technology is studied,and the definition,classification and data fusion methods of data fusion are studied.Pixel-level fusion,feature-level fusion and decision-level fusion are mainly studied.The Bayesian method,the D_S evidence reasoning,the artificial neural network and the fuzzy theory algorithm in the data fusion are introduced in detail.In addition,the wind power forecasting technology and wind power forecasting method are studied in this thesis.By comparing the existing wind power forecasting technology and data fusion technology,this thesis designs a wind power prediction algorithm based on data fusion.The algorithm is divided into two stages,the first stage through the close degree of screening,cleaning,and finally the data fusion.In the second stage,four steps are taken: establishing neural network,making fuzzy control rules,designing fuzzy reasoning,and finally reducing the output variables to get the predicted value of wind power.The algorithm has good real-time performance and eliminates the error of inaccurate data.In the end,the design and research of the wind power enterprise information system is mainly carried out.The system is mainly used to forecast the wind power,so as to meet the local management needs and the grid connection requirements.Mainly from the overall system design,demand analysis and system architecture and development framework for analysis and research.The data fusion algorithm is applied to the system to complete the design of wind power enterprise information system,and the interface display.In this thesis,the data fusion technology is applied to the wind power data processing to solve the problem of wind power forecasting in wind power enterprise informatization.This method can remove the redundant data comprehensively,synthesize various information and get the correct result,which is convenient for the wind power enterprise.Suitable wind power enterprise information system to solve the problem of grid instability caused by wind power grid-connected.