Iron And Steel Enterprise Energy Management And Data Correction System Design And Implementation,

Energy is one of the most important resources in the steel corporation. There are many energy facilities accrossing the steel plant and multi-media energy co-exsit. It is a long-term problem which puzzles steel corporation development that the energy consumption stays at a high level. How to manage complex energy facilities and multi-media energy to improve energy efficiency and ensure the economic operation of the energy system are the most critical problems for reducing cost and achieving sustainable development in the steel corporation.Under the background of energy management center construction in a steel corporation, this thesis analysises the current situation of energy management and discusses how to design energy management system, according to the actual needs of enterprises.In this thesis, three prediction models are proposed to predict the amounts of energy production and consumption. A prediction model which based on production scheduling is used for a long-term energy prediction. For power load prediction, a model based on time series is established. Then, a grey Back-Propagation (BP) neural network model is presented to predict gas consumption in the steelmaking process, by combining grey theory with BP neural network. Data correction techniques are used to reconcile the random error and diagnosis gross error in the measurement data. An automatic gas data balance and authorization method is presented to overcome the deficiency of manual method and make the process of gas balance become automation and transparency, and also make results of gas balance become scientific and open.The system has been discussed to apply in a steel corporation. The results show that the system has the advantages of secure and reliable and easy to expand and easy to maintenance. Real-time monitoring of energy can ensure a stable and secure operation on the production process. Using the prediction models proposed in this thesis can predict the amounts of energy supply and demand more accurately, which provides a reliable basis for energy planning and optimal schecduling. Automatic gas data balance and authorization mothed is used in the system, which solves many disadvantages such as low degree of automation and lack of scientific. Implementation and application of Energy management system provides an effective way to save energy and create significant economic and social benefits for enterprise.