Comparison between Markov chain Techniques for Future Forecasting Using Production and Consumption of Electric Energy

Mohammed Alqatqat¹ , Ma Tie Feng²

Section:Research Paper, Product Type: Journal-Paper
Vol.8 , Issue.1 , pp.56-71, Feb-2021

Online published on Feb 28, 2021

Copyright © Mohammed Alqatqat, Ma Tie Feng . This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
 

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Abstract :
Forecasting of electric energy production and consumption is a fundamental phenomenon for a country’s planning. This study aims to make a comparison between four forecasting methods namely Markov developed by Fiering and Thomas , Markov chains Transformation , Fuzzy Time Series Markov Chain , and proposed method By combining two methods Markov developed by Fiering and Thomas and Markov chains Transformation of predict future production and consumption of electricity in 2016, 2017, 2018,2019 this study examined the accuracy of the prediction of production and consumption of electric energy based on monthly data for production and consumption of electricity during 2016 to 2019 in China. By comparing the four models using the Mean Absolute Percentage Error (MAPE), proposed method was found as the most appropriate model for predicting and analysing the data of interest. Based on this model, production and consumption of electricity can be forecasted. The predictive values were consistent with the original values of the series, which indicated the efficiency of the proposed method in production electric with lowest MAPE but the predictive of consumption electric get low MAPE by Markov chains Transformation and we note that the random number in Markov developed by Fiering and Thomas has impact in our proposed method.

Key-Words / Index Term :
Time series analysis, predictive modelling, Markov chains, Fuzzy time series

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