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Information 2017, 8(1), 33; doi:10.3390/info8010033

Analysis and Modeling for China’s Electricity Demand Forecasting Based on a New Mathematical Hybrid Method

1
Business College, Hebei Normal University, Shijiazhuang 050000, China
2
Department of Economics and Management, North China Electric Power University, Beijing 102206, China
*
Author to whom correspondence should be addressed.
Academic Editor: Willy Susilo
Received: 11 February 2017 / Accepted: 11 March 2017 / Published: 13 March 2017
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Abstract

Electricity demand forecasting can provide the scientific basis for the country to formulate the power industry development strategy and the power-generating target, which further promotes the sustainable, healthy and rapid development of the national economy. In this paper, a new mathematical hybrid method is proposed to forecast electricity demand. In line with electricity demand feature, the framework of joint-forecasting model is established and divided into two procedures: firstly, the modified GM(1,1) model and the Logistic model are used to make single forecasting. Then, the induced ordered weighted harmonic averaging operator (IOWHA) is applied to combine these two single models and make joint-forecasting. Forecasting results demonstrate that this new hybrid model is superior to both single-forecasting approaches and traditional joint-forecasting methods, thus verifying the high prediction validity and accuracy of mentioned joint-forecasting model. Finally, detailed forecasting-outcomes on electricity demand of China in 2016–2020 are discussed and displayed a slow-growth smoothly over the next five years. View Full-Text
Keywords: electricity demand; joint-forecasting model; IOWHA operator; modified GM(1,1) model; logistic model electricity demand; joint-forecasting model; IOWHA operator; modified GM(1,1) model; logistic model
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Liang, J.; Liang, Y. Analysis and Modeling for China’s Electricity Demand Forecasting Based on a New Mathematical Hybrid Method. Information 2017, 8, 33.

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