Predictive analysis on electric-power supply and demand in China

Min Huang, Yong He and Haiyan Cen

Renewable Energy, 2007, vol. 32, issue 7, 1165-1174

Abstract: In order to analyze the electric-power demand and supply in China efficiently, this paper presents a Grey–Markov forecasting model to forecast the electric-power demand in China. This method takes into account the general trend series and random fluctuations about original time-series data. It has the merits of both simplicity of application and high forecasting precision. This paper was based on historical data of the electric-power requirement from 1985 to 2001 in China, and forecasted and analyzed the electric-power supply and demand in China by the Grey–Markov forecasting model. The forecasting precision of Grey-Markov forecasting model from 2002 to 2004 is 99.42%, 98.05% and 97.56% respectively, and in GM(1,1) Grey forecasting model, it is 98.53%, 94.02% and 88.48%, respectively. It shows that the Grey–Markov forecasting models has higher precision than GM(1,1) Grey forecasting model. The forecast values from 2002 to 2013 were as follows: 16106.7, 18541.3, 20575.7, 23940.5, 24498.0, 26785.1, 27977.2, 29032.2, 31247.5, 33428.8, 35865.4, and 38399.3TWh. The results provide scientific basis for the planned development of the electric-power supply in China.

Keywords: GM(1,1); Markov chain; Grey–Markov; Forecast; Electric-power demand (search for similar items in EconPapers)
Date: 2007
References: View complete reference list from CitEc
Citations: View citations in EconPapers (17)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:renene:v:32:y:2007:i:7:p:1165-1174

DOI: 10.1016/j.renene.2006.04.005

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