Mid-term load forecasting based on modified grey model

Haijiang Wang; Shanlin Yang

doi:10.1007/978-3-319-01273-5_18

Mid-term load forecasting based on modified grey model

Haijiang Wang
, Shanlin Yang

Hefei University of Technology

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

1 Scopus citations

Abstract

The construction of smart grid put forward higher requirements on deployment accuracy of the energy. Power generation and electricity sectors have carried out more accurate data analysis and forecasting. In this context, we provide a Gauss-Chebyshev GM(1,1) model, This model could overcome the lack of traditional grey model and made accurate forecasting of electricity consumption in smart grid, Finally, numerical examples demonstrate that this method can efficiently improve the prediction accuracy.

Original language	English
Title of host publication	Proceedings of the 2013 International Conference on Mechatronics and Automatic Control Systems, ICMS 2013
Publisher	Springer Verlag
Pages	169-175
Number of pages	7
ISBN (Print)	9783319012728
DOIs	https://doi.org/10.1007/978-3-319-01273-5_18
State	Published - 2014
Externally published	Yes
Event	2013 International Conference on Mechatronics and Automatic Control Systems, ICMS 2013 - Hangzhou, China Duration: 10 Aug 2013 → 11 Aug 2013

Publication series

Name	Lecture Notes in Electrical Engineering
Volume	237 LNEE
ISSN (Print)	1876-1100
ISSN (Electronic)	1876-1119

Conference

Conference	2013 International Conference on Mechatronics and Automatic Control Systems, ICMS 2013
Country/Territory	China
City	Hangzhou
Period	10/08/13 → 11/08/13

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 7 Affordable and Clean Energy

Keywords

GM (1,1) model
Load forecasting
Smart grid

Access to Document

10.1007/978-3-319-01273-5_18

Cite this

@inproceedings{32fc82947d2c410bb57ab44740101497,

title = "Mid-term load forecasting based on modified grey model",

abstract = "The construction of smart grid put forward higher requirements on deployment accuracy of the energy. Power generation and electricity sectors have carried out more accurate data analysis and forecasting. In this context, we provide a Gauss-Chebyshev GM(1,1) model, This model could overcome the lack of traditional grey model and made accurate forecasting of electricity consumption in smart grid, Finally, numerical examples demonstrate that this method can efficiently improve the prediction accuracy.",

keywords = "GM (1,1) model, Load forecasting, Smart grid",

author = "Haijiang Wang and Shanlin Yang",

year = "2014",

doi = "10.1007/978-3-319-01273-5\_18",

language = "英语",

isbn = "9783319012728",

series = "Lecture Notes in Electrical Engineering",

publisher = "Springer Verlag",

pages = "169--175",

booktitle = "Proceedings of the 2013 International Conference on Mechatronics and Automatic Control Systems, ICMS 2013",

note = "2013 International Conference on Mechatronics and Automatic Control Systems, ICMS 2013 ; Conference date: 10-08-2013 Through 11-08-2013",

}

Wang, H & Yang, S 2014, Mid-term load forecasting based on modified grey model. in Proceedings of the 2013 International Conference on Mechatronics and Automatic Control Systems, ICMS 2013. Lecture Notes in Electrical Engineering, vol. 237 LNEE, Springer Verlag, pp. 169-175, 2013 International Conference on Mechatronics and Automatic Control Systems, ICMS 2013, Hangzhou, China, 10/08/13. https://doi.org/10.1007/978-3-319-01273-5_18

Mid-term load forecasting based on modified grey model. / Wang, Haijiang; Yang, Shanlin.
Proceedings of the 2013 International Conference on Mechatronics and Automatic Control Systems, ICMS 2013. Springer Verlag, 2014. p. 169-175 (Lecture Notes in Electrical Engineering; Vol. 237 LNEE).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - Mid-term load forecasting based on modified grey model

AU - Wang, Haijiang

AU - Yang, Shanlin

PY - 2014

Y1 - 2014

N2 - The construction of smart grid put forward higher requirements on deployment accuracy of the energy. Power generation and electricity sectors have carried out more accurate data analysis and forecasting. In this context, we provide a Gauss-Chebyshev GM(1,1) model, This model could overcome the lack of traditional grey model and made accurate forecasting of electricity consumption in smart grid, Finally, numerical examples demonstrate that this method can efficiently improve the prediction accuracy.

AB - The construction of smart grid put forward higher requirements on deployment accuracy of the energy. Power generation and electricity sectors have carried out more accurate data analysis and forecasting. In this context, we provide a Gauss-Chebyshev GM(1,1) model, This model could overcome the lack of traditional grey model and made accurate forecasting of electricity consumption in smart grid, Finally, numerical examples demonstrate that this method can efficiently improve the prediction accuracy.

KW - GM (1,1) model

KW - Load forecasting

KW - Smart grid

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DO - 10.1007/978-3-319-01273-5_18

M3 - 会议稿件

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SN - 9783319012728

T3 - Lecture Notes in Electrical Engineering

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BT - Proceedings of the 2013 International Conference on Mechatronics and Automatic Control Systems, ICMS 2013

PB - Springer Verlag

T2 - 2013 International Conference on Mechatronics and Automatic Control Systems, ICMS 2013

Y2 - 10 August 2013 through 11 August 2013

ER -

Mid-term load forecasting based on modified grey model

Abstract

Publication series

Conference

UN SDGs

Keywords

Access to Document

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