Zeng Ming
School of Economics and Management, North China Electric Power University, Beijing, 102206, China
Liu Daoxin
School of Economics and Management, North China Electric Power University, Beijing, 102206, China
Duan Kaiyan
School of Economics and Management, North China Electric Power University, Beijing, 102206, China
Xue Song
School of Economics and Management, North China Electric Power University, Beijing, 102206, China
Li Yulong
School of Economics and Management, North China Electric Power University, Beijing, 102206, China
Zhan Haiyan
School of Economics and Management, North China Electric Power University, Beijing, 102206, China
ABSTRACT
Urban economic development and its electricity consumption have interactions with each other. Moreover, the currently existing urban electricity demand forecasting methods cannot accurately predict urban electricity based on economic development. For this complex system of urban economic development forecasting and its electricity demand, System Dynamics (SD) has the characteristics of comprehensive and dynamic, while econometrics is adept in seeking the intrinsic link among a lot of data. Thus, these two methods are applied to comprehensively forecast urban power consumption. A case study is taken based on actual data from Shandong Province and the results shows that Gross Domestic Product (GDP) will raise, but it will experience steady decline after brief rise in GDP growth. Moreover, with a lag impact from economic development, power consumption during the same period will be rising, providing endless power for economic development and will remain steady at about 680 billion kWh. This case study verifies the accuracy and scientific of proposed model.
PDF References Citation
Received: August 05, 2013;
Accepted: November 06, 2013;
Published: November 12, 2013
How to cite this article
Zeng Ming, Liu Daoxin, Duan Kaiyan, Xue Song, Li Yulong and Zhan Haiyan, 2013. Pre-integrated Forecasting Method Research of Urban Electricity Consumption
Based on System Dynamics and Econometric Model. Journal of Applied Sciences, 13: 4732-4737.
DOI: 10.3923/jas.2013.4732.4737
URL: https://scialert.net/abstract/?doi=jas.2013.4732.4737
DOI: 10.3923/jas.2013.4732.4737
URL: https://scialert.net/abstract/?doi=jas.2013.4732.4737
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