Abstract
The power grid is one of the foundations of national economic construction. Considering the future development trend of power grid and power market, and the important challenges of grid investment decision, this paper mainly studies various factors affecting grid investment from two aspects: internal and external. Therefore, the grid enterprises can accurately grasp the investment ability, make reasonable investment decisions, increase the profit margin, and adapt to the new situation of power development. The ARMA model and Johansen cointegration analysis theory of grid investment are used to analyze the relationship between power grid and various influencing factors, and the relationship between influencing factors and grid investment is obtained. The validity of this relationship is demonstrated by using data from the State Grid Corporation of 2005–2015. It is of great practical significance for grid companies to further understand the factors affecting investment and how to find effective ways to make investment decisions.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Deng G (2015) Research on long-term and dynamic relationship of factors affecting grid investment based on time series analysis. Zhejiang University (in Chinese)
Xu X (2017) Research on investment decision-making of complex grid optimization based on power demand and investment capacity. North China Electric Power University, Beijing (in Chinese)
Ji L, Yang L, Fei G (2016) Analysis and forecast of factors affecting power grid engineering investment. China Power Enterp Manag (in Chinese)
Cheng Y, Zhang Z (2006) Co-integration modeling analysis of sales price and electricity demand. In: Proceedings of the CSEE (in Chinese)
Zhao H, Yang W, Li C (2011) Predictive research on grid investment demand based on cointegration theory and error correction model. Electric Netw Technol (in Chinese)
Cui H, Wang W (2010) Research on China’s energy-economy-environment (3E) system based on VAR model. J Beijing Inst Technol (in Chinese)
Yuan J, Ding W, Hu Z (2006) Cointegration and volatility analysis of power consumption and China’s economic development. Power Syst Technol (in Chinese)
Zhang X, Niu Y, Zhao X (2008) Model of coordination relationship in China’s power consumption. In: Proceedings of the CSEE (in Chinese)
Wang C, Liu C, Zhou J (2012) Analysis of the impact of power grid investment on the operating efficiency of power grid enterprises. China High-tech Enterp (in Chinese)
Wang S, Hu J (2009) Trend cycle decomposition of China’s GDP and the persistence effect of random impact. Econ Res (in Chinese)
Acknowledgments
This research was one of the results of the science and technology project of State Grid Jiangsu Electric Power Co. Itd. Economic Research Institute called “Evaluation and Analysis of Differential Sensitive Factors in the Whole Process of Power Grid Project Investment”.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2020 Springer Nature Switzerland AG
About this paper
Cite this paper
Zhang, W., Nan, K., Yang, Q., Zhang, J., Chen, H., Zhang, X. (2020). Analysis of Factors Affecting Power Grid Investment Based on Johansen Cointegration Analysis Theory. In: Xu, Z., Choo, KK., Dehghantanha, A., Parizi, R., Hammoudeh, M. (eds) Cyber Security Intelligence and Analytics. CSIA 2019. Advances in Intelligent Systems and Computing, vol 928. Springer, Cham. https://doi.org/10.1007/978-3-030-15235-2_201
Download citation
DOI: https://doi.org/10.1007/978-3-030-15235-2_201
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-030-15234-5
Online ISBN: 978-3-030-15235-2
eBook Packages: Intelligent Technologies and RoboticsIntelligent Technologies and Robotics (R0)