Monthly Electricity Forecast Of Funning Based On Industry Characteristics

With the continuous development of power system marketization,electricity prediction plays an important role in power grid and Power Distribution Company.As the new normal economy in our country and the corresponding slowdown of economic growth,the renewal and adjustment of industrial structure have a great influence on the national economy,and the electricity consumption of the national economy has been reduced.With the continuous promotion of electricity reform and the rapid development of the market,many electric companies have sprung up like a spring breeze,which incubate the electricity reform in China.In the process of electricity market reform,power supply companies have begun to change their traditional way of operation.In addition,the characteristics of the power supply and the time balance,many power supply companies have a large deviation in the prediction of electricity.Therefore,the accurate prediction of electricity and electricity is particularly important.Therefore,this paper mainly studies the prediction method of power and electricity based on the analysis of industry characteristics.Firstly,this paper introduces the industry division according to the rules of national economic industry,analyzes the ratio of power consumption in different industries,and analyzes the basic power consumption characteristics of different industries.In addition,the factors affecting the power consumption are studied and analyzed,considering the characteristics of power consumption of different user industries,the different electric power forecasting models are established for different industries.For commercial users,this paper establishes a grey power forecasting model based on fractional order operator.For industrial users,this paper establishes a model for predicting the quantity of electricity in multiple regression,and establishes a forecasting model of time series for residents.The electricity consumption of different typical industries is forecasted,and the precision prediction of power consumption is realized.Finally,through the actual power consumption data of Funingcounty and the related meteorological data,several typical industries in this area are predicted.In the process of electricity forecasting,the power consumption characteristics of several typical industries are first combined with different electricity forecasting models to predict the different typical industries.For commercial users,taking several typicalbusinesses as examples,the fractional order operator with particle swarm optimization is used to predict the power consumption of industry,and the results obtained are compared with the results obtained from the traditional grey model.For industrial users,taking several technology companies in Funing County as an example,multiple regression models are used to predict their comprehensive electricity consumption.In order to eliminate the single error,a comprehensive load of several residential areas is analyzed for residential users.The method of time series analysis is used to predict the electricity consumption of the industry.The method of time series analysis is generally applicable to the medium and long term electricity forecasting.Through the analysis of time series,the electricity consumption of the residents is predicted according to the given seasonal trend.Through actual example analysis,it is verified that the above three prediction methods and models have good stability,high prediction accuracy and good portability.Therefore,this paper proposes a typical industry forecasting method of industry classification and a variety of influencing factors,which provides new ideas and directions for Funingcounty to carry out electricity forecasting and formulate corresponding purchasing and selling strategies.