Design And Implementation Of Wind Power Forecasting System Based On Big Data

Adequate,safe and clean energy supply is the basic guarantee for economic development and social progress.China has a large population,low per capita energy consumption level,high pressure on energy demand growth,and a very prominent contradiction between energy supply and economic development.To fundamentally solve China's energy problems,protect the environment,and achieve sustainable development,in addition to vigorously improving energy efficiency,speeding up the development and utilization of renewable energy is an important strategic choice.As the main renewable energy source,wind power has developed rapidly in recent years.The installed scale of wind power in the country has continued to expand,ranking first in the world.Wind power has become one of the important energy sources in China.However,due to the intermittent and instability of wind energy,the power generation of wind farms fluctuates greatly,which brings challenges to the safety and stability of the power system,and also causes wind power companies to The operating costs have increased.Therefore,wind power forecasting can not only improve the power generation efficiency of wind farms,but also ensure the stable operation of power grid dispatching departments.The wind power prediction system designed in the thesis is an effective way to solve the current phenomenon of abandoning wind and power.The thesis mainly introduces the wind power forecasting system based on big data,from the design goals and design framework of the system,to the technical route and main functional modules,and then to the main research results,especially the technical route and main functional modules of the system.Explained.First,the concept and definition of big data are explained,and the characteristics of big data and related technical characteristics are explained.Secondly,combined with the actual business of the wind power industry,the demand for the wind power forecasting system is analyzed,and the framework and data flow of the system implementation are sorted out.Then,the application direction and actual operation of the power prediction methods and models based on big data technology are summarized and analyzed,and the algorithm models involved are analyzed.The designed system is based on the geographical location and climatic conditions of the wind farm.Using different algorithm models,targeted research and development of client systems and prediction models suitable for the individual needs of different electric fields.The wind power forecasting system designed in the thesis fully considers the actual application requirements,can meet the forecasting requirements of different climates,different regions,and different electric fields,and has designed and formed a mature wind power forecasting system.Finally,the application effect after the system is put into operation is analyzed.