Abstract
Electricity has become one of the most important energy in human social. A reliable analysis of the influencing factors of electricity sales will help strengthen the electricity companies, related national energy departments’ control and security over the expected electricity consumption across the country. In this paper, we analyze the relationship between different types of electricity sales and a variety of potential factors, including immediacy factors, leading factors and the influencing of Chinese New Year by using Pearson correlation coefficient, dynamical time warping. Through the result of experiment, we found that the influencing factors are different for different electricity usage categories. And some factors have lagging effects on electricity sales, so we need to comprehensively consider immediacy factors and leading factors when forecasting electricity sales. At the same time, we also found that Chinese New Year also has a significant impact on electricity sales, thus Chinese New Year is also is also an important factor affecting electricity sales.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Zhang, C., Zhou, K., Yang, S., Shao, Z.: On electricity consumption and economic growth in China. Renew. Sustain. Energy Rev. 76, 353–368 (2017)
Fang, D., Hao, P., Hao, J.: Study of the influence mechanism of China’s electricity consumption based on multi-period ST-LMDI model. Energy 170, 730–743 (2019)
Zhang, Y., Da, Y.: The decomposition of energy-related carbon emission and its decoupling with economic growth in China. Renew. Sustain. Energy Rev. 41, 1255–1266 (2015)
Steenhof, P.: Decomposition of electricity demand in China’s industrial sector. Energy Econ. 28(3), 370–384 (2006)
Xu, X., Xiao, B., Li, C.: Critical factors of electricity consumption in residential buildings: an analysis from the point of occupant characteristics view. J. Clean. Product. 256, 120423 (2020)
Jiang, S., Zhu, Y., He, G., Wang, Q., Lu, Y.: Factors influencing China’s non-residential power consumption: estimation using the Kaya–LMDI methods. Energy 201, 117719 (2020)
Liu, Y.: Exploring the relationship between urbanization and energy consumption in China using ARDL (autoregressive distributed lag) and FDM (factor decomposition model). Energy 34(11), 1846–1854 (2009)
Engle, R., Granger, C., Rice, J., Weiss, A.: Semiparametric estimates of the relation between weather and electricity sales. J. Am. Stat. Assoc. 81(394), 310–320 (1986)
Franco, G., Sanstad, A.: Climate change and electricity demand in California. Clim. Change 87(1), 139–151 (2008)
Chan, A.: Developing future hourly weather files for studying the impact of climate change on building energy performance in Hong Kong. Energy Build. 43(10), 2860–2868 (2011)
Guo, Z., Zhou, K., Zhang, C., Lu, X., Chen, W., Yang, S.: Residential electricity consumption behavior: Influencing factors, related theories and intervention strategies. Renew. Sustain. Energy Rev. 81, 399–412 (2018)
Liu, Y.: Exploring the relationship between urbanization and energy consumption in China using ARDL (autoregressive distributed lag) and FDM (factor decomposition model). Energy 34(11), 1846–1854(2009)
Schober, P., Boer, C., Schwarte, L.: Correlation coefficients: appropriate use and interpretation. Anesth. Analg. 126(5), 1763–1768 (2018)
Müller, M.: Dynamic time warping. Information Retrieval for Music and Motion, pp. 69–84 (2007). https://doi.org/10.1007/978-3-540-74048-3_4
Acknowledgement
This work was supported in part by the National Natural Science Foundation of China under Grant No. 61803391, and in part by the Hunan Provincial Natural Science Foundation of China under Grant No. 2019JJ50803.
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2021 Springer Nature Switzerland AG
About this paper
Cite this paper
He, H., Zou, W., Guo, Q., Wu, W., Xiao, K. (2021). Analysis on Influencing Factors of Electricity Sales for Electric Data Security. In: Cheng, J., Tang, X., Liu, X. (eds) Cyberspace Safety and Security. CSS 2020. Lecture Notes in Computer Science(), vol 12653. Springer, Cham. https://doi.org/10.1007/978-3-030-73671-2_15
Download citation
DOI: https://doi.org/10.1007/978-3-030-73671-2_15
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-030-73670-5
Online ISBN: 978-3-030-73671-2
eBook Packages: Computer ScienceComputer Science (R0)