The Intelligent Prediction Of Regional Steel Industry Power Consumption Under The New Policy For Atmospheric Pollution Control

Regional power prediction has great significance for the operation and planning of power system.Researches by identifying the properties of the main power consumer, carrying out the main consumer power forecasting,effectively improve the overall prediction accuracy, so we must attach much importance to the research about the characteristics of the main power consumer. Asthe main power consumer of northern Hebei, Iron and steel industry power load characteristic is relatively complex. Moreover, with the implementation of the new policy for the control of air pollution, the characteristics of iron and steel industry power in northern Hebeihave appeared in the new changes. Therefore, we must carry out the regional steel industry power intelligent prediction research under the new policy for the control of air pollution, which introduces the policy factors bycarrying out the policy quantitative analysis,fianally constructing a new power prediction model to guarantee the power prediction accuracy.The purpose of this paper is to carry out the steel industry power prediction research under the new policy for the control of air pollution, first of all, we conduct the analysis about the present situation of northern Hebei steel industry power consumption and influence factors,constructing an influential factor set byrecognizing from the aspect of the macroscopic economy, production, downstream industry and policy;Secondly,the quantitative research about environmental policys are carried out,in order to provide input variables for subsequent prediction model;Next, using the neural network sensitivity analysis, we can screen and reducethe above-mentioned influence factors, improving the prediction accuracy of subsequent model; then, we respectively use the nonlinear S function, BP neural network, and LSSVM forecasting model in prediction.By selecting two high fitting precision models as the BP neural network and LSSVM, we finally put forward a steel industry power optimization combination forecast model under the new policy for the control of air pollution. Finally, the article carry out more sight prediction using the above-mentioned steel industry power optimization combination forecast model under the new policy for the control of air pollution,giving out the prediction results corresponding to the given situation.As the policy for the control of air pollutionwidely applying,policy will gradually become the important influence factor of high energy-consuming industries power consumption. This paper puts forward the intelligent power optimization combination forecast model under the new policy for the control of air pollution, whichcan be widely applied to other high energy-consuming industrial city, improving the iron and steel industry or other high energy-consuming industries power forecasting precision by the quantitative analysis of policy factors. The precise prediction could offer guidesfor the supporting the planning and construction of relatedpower facilities, ensuring the timeliness and economy of electric power construction.