Energy and Power Engineering

Volume 5, Issue 4 (July 2013)

ISSN Print: 1949-243X   ISSN Online: 1947-3818

Google-based Impact Factor: 0.73  Citations  h5-index & Ranking

A Fuzzy Probability-based Markov Chain Model for Electric Power Demand Forecasting of Beijing, China

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DOI: 10.4236/epe.2013.54B094    4,653 Downloads   5,615 Views  Citations

ABSTRACT

In this study, a fuzzy probability-based Markov chain model is developed for forecasting regional long-term electric power demand. The model can deal with the uncertainties in electric power system and reflect the vague and ambiguous during the process of power load forecasting through allowing uncertainties expressed as fuzzy parameters and discrete intervals. The developed model is applied to predict the electric power demand of Beijing from 2011 to 2019. Different satisfaction degrees of fuzzy parameters are considered as different levels of detail of the statistic data. The results indicate that the model can reflect the high uncertainty of long term power demand, which could support the programming and management of power system. The fuzzy probability Markov chain model is helpful for regional electricity power system managers in not only predicting a long term power load under uncertainty but also providing a basis for making multi-scenarios power generation/development plans.

Share and Cite:

X. Zhou, Y. Tang, Y. Xie, Y. Li and H. Zhang, "A Fuzzy Probability-based Markov Chain Model for Electric Power Demand Forecasting of Beijing, China," Energy and Power Engineering, Vol. 5 No. 4B, 2013, pp. 488-492. doi: 10.4236/epe.2013.54B094.

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