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The Application of a Grey Markov Model in Forecasting the Errors of EIA’s Projections in Gas Production and Energy Intensity

Grey system theory looks for realistic patterns based on modeling with a few available data. In this paper, a Grey-Markov prediction model which is the combination of the GM(1,1) and Markov model was studied; Moreover, its applications in energy system were presented. The average errors of Energy Information Administration’s predictions for Natural Gas production and Energy intensity from 1985 to 2008 and 1985 to 2007 respectively were used as two forecasted examples. Comparing with GM(1,1) prediction model, we showed that the Grey- Markov prediction model improves the forecast accuracy.