Study On Energy Prediction Of Iron And Steel Enterprises Based On Data Analytics

Under the environment of sustainable development and ecological civilization,as a large energy consumer in China,to improve energy efficiency and overall competitiveness of iron and steel enterprises is imperative.Therefore,the energy consumption forecast of iron and steel enterprises is used as the research background in this paper.Through the pre-understanding of the issues studied,and analysis research,this paper established data analytics based energy prediction model.Experimental results demonstrated the algorithms designed can solve the problem of prediction effectively.Finally,according to the actual demands of iron and steel enterprises,the forecasting system is developed.The main work of this paper is summarized as follows:(1)Firstly,this thesis studies the research status of energy prediction in literature,and analyzes the mechanism and existing problems of energy consumption in steel enterprises.The energy consumption and regeneration of the main process are studied and analyzed,and the relevant data is statistically organized.(2)Secondly,a least square support vector machine prediction model based on distribution estimation algorithm is proposed.Distribution estimation algorithm is used to estimate the kernel and penalty factor parameters of LSSVM.The model is used to solve the small-sample energy consumption prediction.At the same time,the numerical experiments are carried out to show that the algorithm is effective in energy consumption prediction.(3)Then,the BP neural network algorithm based on differential evolution algorithm is proposed to solve the large-scale energy consumption forecast of iron and steel enterprises.The differential evolution algorithm is used to estimate the weights and thresholds of the network.And the model is used to solve the energy consumption prediction.The numerical experiments show the effectiveness of this algorithm.(4)Finally,based on the actual demand of iron and steel enterprises,according to the overall research ideas of energy medium forecasting,this thesis designs and develops the energy medium forecasting system of iron and steel enterprises to predict the energy consumption of each main process and realizes the function of data management,parameter setting,energy forecast and system management,which provides a strong data support for the enterprise energy information management.