Study On The Prediction Method For Blast Furnace Gas System Based On Improved Echo State Network

The transportation and conversion process of energy in steel industry is relatively complicated. It is an important task for enterprise energy management to guarantee a continuous, safe and economical energy supply. At present, the byproduct gas is the key part of energy optimal scheduling problem. Blast furnace gas (BFG) is with the characteristics of least caloricity, complex generation process and output with big fluctuation, so it will usually be diffused firstly when poor energy scheduling and imbalance occurs, which will create much more harmful gas and degrade the environment. Therefore, the study on reliable prediction of the BFG generation and consumption and its recovery and reuse fully can provide scientific guidance for efficient utilization of the byproduct energy and improve the level to save energy in steel enterprise.In this paper, on basis of the background of Shanghai Baosteel, the generation and consumption users of the BFG system are divided into two types for the prediction problem, which are adjustable users and non-adjustable users, respectively. For non-adjustable users, an improved echo state network (ESN) prediction method with parameters is proposed firstly. Based on Least Mean Square (LMS) error criterion, the network parameters are optimized by stochastic gradient descent in order to achieve a minimized training error. Compared to other methods, such method brings about a better prediction performance. Secondly, an average method is used to predict adjustable users. Since the data of the BFG generation includes a series of noises in practice, the performance is unsatisfactory if using the improved ESN method directly. For resolving this problem, an approach based on empirical mode decomposition (EMD) is employed to implement the data de-noise before prediction. Based on analyzing the influence factors of gas holder level, prediction factor model of the BFG gas holder is built by the ESN method.An application software for the BFG system prediction is developed on the basis of the prediction method. This software consists of server and client terminal. The server predicts the BFG system which includes all users and gas holder at regular intervals and the client terminal presents the real-time data and predict data through the user interfaces. The prediction software has been applied in the Energy Center of Baosteel and the running results demonstrate the validity of the proposed method.