Grey Forecasting Model And Its Application In Electric Power Demands

The grey system theory is founded by Professor Deng Julong who is the famousscholar in China.，the research object of which is the uncertainty system that partialinformation is known and some is unknown. Grey forecasting model is one of theimportant content in the grey system theory, which has been widely applied in theeconomy, industry, agriculture, biological and so on. Therefore, the study of the greyforecasting model has important significance.In this paper, the grey forecasting model was studied with GM (1,1) model as thecore and based on grey system theory. On the one hand, the residual model wasoptimized based on the background value optimization of the original model. Bycomparing the example, the accuracy of the prediction can be improved by theoptimization of the residual GM (1,1) model effectively. Meanwhile, in view of thegrey forecasting model and Markova model can be used in prediction of related timeseries directly, the combinations of the grey forecast model and Markova not onlyplayed the advantage of a little gray prediction model data, a short period of time, smallfluctuations, but also embodies the characteristics that Markov model is applicable torandom fluctuations. Based on this situation, taking into account the structure of thebackground value in the original GM (1,1) model affected the precision of the model,the combination of GM (1,1) model that improved the background value of and theMarkov model was studied in this paper, in order to improve the model precision,so asto achieve complementarity between the different models. As the application of themethod, electricity demand of the whole society of Shaanxi Province and the residentialwas forecasted in this paper, the results showed that the prediction accuracy ofimproved gray Markov model is relatively high, and the calculation process is relatively simple. The results can provide some reference for electricity demand of ShaanxiProvince, in the next few years.The power demand will be affected by the GDP, the price and other factors. In thispaper, electricity demand of Shaanxi Province and its influencing factors were analyzedby the gray relational analysis, from two angles on the external factors and internalstructure. The study has practical significance and can provide some reference for theelectricity demand.