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International Journal of Frontiers in Sociology, 2022, 4(5); doi: 10.25236/IJFS.2022.040511.

Medium and Long-term Power Load Forecasting Based on Grey Markov Correction Model

Author(s)

Jinting Sun

Corresponding Author:
Jinting Sun
Affiliation(s)

Department of Economic Management, North China Electric Power University, Baoding, China

Abstract

Medium and long-term load forecasting is a necessary prerequisite for distribution network planning, and is of great significance for the improvement of economic and social benefits of the power system. Aiming at the defects of low prediction accuracy and poor applicability of traditional grey forecasting model, a medium and long-term load forecasting method of power system based on Markov residual correction and improved grey theory is proposed. Based on the classical grey forecasting GM(1,1) model, this method first divides the state according to the relative residuals, calculates the Markov residual transition matrix, and then uses the equal-dimensional innovation method to construct the grey Markov correction forecast. Model, and finally use residual processing method to revise the prediction results. The simulation results based on an actual example of load forecasting of annual power consumption in Guangxi Province show that compared with the traditional grey forecasting model, the grey Markov residual correction model proposed in this paper has significant advantages in forecasting accuracy and applicability.

Keywords

Load forecasting; Grey model; Markov chain; Equal-dimensional innovation

Cite This Paper

Jinting Sun. Medium and Long-term Power Load Forecasting Based on Grey Markov Correction Model. International Journal of Frontiers in Sociology (2022), Vol. 4, Issue 5: 53-62. https://doi.org/10.25236/IJFS.2022.040511.

References

[1] N. An, W. Zhao, J. Wang, D. Shang, and E. Zhao, “Using multi-output feedforward neural network with empirical mode decomposition based signal filtering for electricity demand forecasting,” Energy 49(1), 279–288 (2013). 

[2] D. C. Li, C. J. Chang, C. C. Chen, and W. C. Chen, “Forecasting short-term electricity consumption using the adaptive grey-based approach—An Asian case,” Omega 40(6), 767–773 (2012).

[3] Zhou C, Xing W, LI Y. Summarization on load forecasting method of electrical power system. Journal of power supply, 2012, 6: 32-39.

[4] Wang Yong, Huang Guoxing, PENG Daogang. Application of multiple linear-feedback regression analysis to electric load forecasting. Computer Applications and Software, 2008,25(1): 82-84(in Chinese)

[5] Huang X. Application of BP neural network in power system load forecasting based on principal component analysis. Science and Technology Information, 2008(16): 313-314(in Chinese)

[6] Duan F, Sun Q. Application of two improved power load gray prediction models Science Technology and Engineering,2011,11(32):7923-7924. 

[7] Sun JM , Qian X Ting, Wang Ying. Medium and long term power load forecasting based on improved grey model. Journal of electro technical, 2019(19):28-31.

[8] GP Ren, SW Shen. Power system load forecasting base on grey forecasting model of equidimensional filling vacancies. Journal of Hebei Electric Power Technology, 2014, 33(03):26-28.

[9] W lian, XH Du. Application of Gray et al-payup prediction model in long-term load forecast of power systems .Science and technology intelligence development and economy,2007,17(1):167-168.

[10] LY He. Application of Improved Grey Model in medium and Long-term Power Load Forecasting [D]. Harbin University of Science and Technology,2018.

[11] Y Liu, L Guo, F Yang ,DL Jiang, L Ren, J li. Medium and long Term load forecasting Based on Improved Gray Theory . Power system and clean energy, 2016, 32(08):51-56+61.

[12] Hua-ren Y U, Jun M O, Jin L I. Market demand prediction based on grey markov model. Commercial Research, 2009. 

[13] Y Yu, XB Yang, W Du. Prediction method based on gray-Markov chain improvement method. Journal of Statistics and Decision 2008, 13:5356.

[14] Yong C, Chuan W, Xiaolong C, et al. Application of Grey-Markov Prediction Model on Long-Term Load Forecasting. Modern Electric Power, 2011.

[15] Wang H Z, Zhou J, Liu K. Summary of research on the short-term load forecasting method of the electric power system. On Electrical Automation, 2015, 37(01): 1-3+ 39. 

[16] Mao L, Yao J, Jin Y, et al. Theoretical study of combination model for medium and long term load forecasting. Proceedings of the CSEE, 2010, 30(16): 53-59.