Data Integration And Processing In The Enterprises Energy Management System

With the world energy demand is becoming more and more intense, the role of energy management gets important increasingly. Effective Energy Management System cannot only help enterprises know their energy consumption comprehensively and accurately, but also can help them carry out some energy analysis, in order to find a solution to energy saving.By investigating a cigarette factory’s Energy Management in Yunnan Province, we introduce the production process and energy demand in cigarette industry. Besides, according to the properties of different energy medium, like water, gas, electricity and steam, we will talk about the energy flow of air compress system, water supply system, power supply and distribution system, and boiler system respectively. In order to realize in monitoring these important subsystems, the factory adopts three layer network structure and redundant ring network to monitor the whole energy medium information and production equipment status information, which is ready for the next energy consumption analysis and forecast.For those acquired production data, this paper using different methods respectively to evaluate the enterprise production process, aiming to help the managers to master the operation. This article uses three different approaches to analyze the data collected from practical production. In this way, we can make an overall and exact evaluation of the production operation in the enterprise. In addition, this paper offers some advice and suggestion on technology and management in energy saving.Moreover, energy prediction is another important method for qualitative analysis of enterprise. In this article, we apply linear regression analysis method, residual grey model analysis and the additional momentum BP neural network method in predicting the energy data. It has been proved that these three approaches are simple and efficient, which can be reliable enough to predict the future energy consumption.