Abstract
The markov prediction and analysis is a method based on markov chain theory, according to the present states and tendency of some variables, the possible states in a given period in the future will be forecasted. To determine the transition probability matrix is the crux of this method. This paper applies stochastic time series based on markov chain model to forecast the developing trends of China’s energy consumption structure under the influence of energy policy. This model is adopted to forecast the total amount of energy consumption and the trends of energy production and consumption structures. China’s energy consumption during 2006–2011 are simulated and its trends in 2015 and 2020 are forecast through this model. Results demonstrate that this model can effectively simulate and forecast the total amount and structures of primary energy consumption. Although the growth rate of energy consumption in China has decreased under the energy saving policy, but it not enough to achieve the objective of carbon reduction.
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This work was supported by Natural Science Foundation of Hubei Province of China (Grant 2014CFB917).
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Ruan, Z., Luo, A. & Yao, H. Stochastic Time Series Analysis for Energy System Based on Markov Chain Model. Mobile Netw Appl 22, 427–434 (2017). https://doi.org/10.1007/s11036-016-0796-3
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DOI: https://doi.org/10.1007/s11036-016-0796-3