With development of smart grid, study of power demand model of high energy consumers becomes an important topic in China. As a result of preliminary research, initial power demand model of high energy consumer is built up based on data mining. Such a model opens out the relationship of power demand and market factors, which can be applied to demand side management (DSM) for high energy consumers under Chinese market environment. A power demand forecasting method based on consumer classification and high energy consumer demand model is proposed. Such a model can also be applied to strategy making in DSM. Case study is carried out with real-life data from Guiyang city power grid where a large percentage of power demand is that from high energy consumers mainly consisting of phosphor plants and electrolytic aluminum plants. Case study results shows that demand forecasting precision is improved significantly and quantitative DSM strategies for high energy consumers can be made based on the proposed model.