Papers by Author: Hong Juan Li

Abstract: Aiming at the power plant energy consumption and gas balance influenced serious with the affluent gas fluctuate frequently of byproduct gas system in an iron and steel industry, which is very difficult to be modeled using the mechanism modeling, a forecast trend sequence of the gas supply HP-ENN model was established based on the characteristics of self-provided power plant energy utilization and the properties of HP filter, Elman neural network. The prediction results using practical production data show that using the proposed HP-Elman method that sample A 48, 60 points trend forecast average relative error are 0.37%, 0.47% and sample B 48, 60 points trend forecast average relative error are 0.82%, 1.03%,which can effectively for the trend forecast of self-provided power plant gas supply with a reliable prediction capacity.

Abstract: In this paper, we presented a prediction model of oxygen consumption of blast furnace (BF) based on least squares support vector machine (LSSVM) with the production data of an iron and steel factory. This method utilizes data pre-processing and parameters optimization to improve the fitting precision and operation speed of the model. By comparing the prediction results using different models with actual production data, we found out that the modified regression model of LSSVM is more suitable to predict the trend of oxygen consumption than others. The prediction accuracy is satisfactory and is helpful for oxygen system dispatch and production practice.

Abstract: A lot of energy resources such as coal, electricity and oils, are consumed during the steel production, and simultaneously a variety of waste heat and energy is produced. If most of the waste heat and energy can be recovered by the self-supply power plant and other generating devices, then the electricity consumed by the factory can be supplied by itself, which can be called the “autarky mode of electricity”. The autarky mode of electricity can improve the recovery of the waste heat and energy, and thus reduce the energy consumption of an iron & steel factory. Based on the BF-BOF steelmaking routes, the energy-flow models for the electricity generating with waste heat and energy are constructed. The autarky modes of electricity of the factories with different production scales are put forward, and the contribution of the mode to energy saving and economic benefits is analyzed.