Data mining approach for short term load forecasting by combining wavelet transform and group method of data handling (WGMDH)

Trisna Yuniarti; Isti Surjandari Prajitno; Erlinda Muslim; Enrico Laoh

doi:10.1109/ICSITech.2017.8257085

Data mining approach for short term load forecasting by combining wavelet transform and group method of data handling (WGMDH)

Trisna Yuniarti, Isti Surjandari Prajitno, Erlinda Muslim, Enrico Laoh

Department of Industrial Engineering

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

5 Citations (Scopus)

Abstract

Forecasting is one of the essential activities at the electrical power company. Inaccurate forecasting will lead to wastage of operating costs. Data mining has been widely used to solve the problem of forecasting. In this study, we propose a method using data mining technique for doing electrical load forecasting, which is a combination of wavelet transform and group method of data handling (WGMDH). The proposed algorithm is used to predict the short-term power load which aims to improve the accuracy of forecasting. The results show that by using proposed algorithm better accuracy is achieved compared with the coefficient method which is used by Indonesian Power Company in Sumatera to forecast the electrical load. The method can improve the forecasting of electricity on average above 50% per year, both for the type of similar day and daily electricity load characteristic pattern.

Original language	English
Title of host publication	Proceeding - 2017 3rd International Conference on Science in Information Technology
Subtitle of host publication	Theory and Application of IT for Education, Industry and Society in Big Data Era, ICSITech 2017
Editors	Rafal Drezewski, Goutam Chakraborty, Shah Nazir, Lala Septem Riza, Ummi Raba'ah Hashim, Aji Prasetyo Wibawa, Yaya Wihardi, Andri Pranolo, Enjun Junaeti, Shi-Jinn Horng, Heui Seok Lim, Leonel Hernandez
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	53-58
Number of pages	6
ISBN (Electronic)	9781509058662
DOIs	https://doi.org/10.1109/ICSITech.2017.8257085
Publication status	Published - 12 Jan 2018
Event	3rd International Conference on Science in Information Technology, ICSITech 2017 - Bandung, Indonesia Duration: 25 Oct 2017 → 26 Oct 2017

Publication series

Name	Proceeding - 2017 3rd International Conference on Science in Information Technology: Theory and Application of IT for Education, Industry and Society in Big Data Era, ICSITech 2017
Volume	2018-January

Conference

Conference	3rd International Conference on Science in Information Technology, ICSITech 2017
Country/Territory	Indonesia
City	Bandung
Period	25/10/17 → 26/10/17

Keywords

classification
gmdh
load forecasting
stlf
wavelet transform

Access to Document

10.1109/ICSITech.2017.8257085

Cite this

Yuniarti, T., Prajitno, I. S., Muslim, E., & Laoh, E. (2018). Data mining approach for short term load forecasting by combining wavelet transform and group method of data handling (WGMDH). In R. Drezewski, G. Chakraborty, S. Nazir, L. S. Riza, U. R. Hashim, A. P. Wibawa, Y. Wihardi, A. Pranolo, E. Junaeti, S.-J. Horng, H. S. Lim, & L. Hernandez (Eds.), Proceeding - 2017 3rd International Conference on Science in Information Technology: Theory and Application of IT for Education, Industry and Society in Big Data Era, ICSITech 2017 (pp. 53-58). (Proceeding - 2017 3rd International Conference on Science in Information Technology: Theory and Application of IT for Education, Industry and Society in Big Data Era, ICSITech 2017; Vol. 2018-January). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ICSITech.2017.8257085

Yuniarti, Trisna ; Prajitno, Isti Surjandari ; Muslim, Erlinda et al. / Data mining approach for short term load forecasting by combining wavelet transform and group method of data handling (WGMDH). Proceeding - 2017 3rd International Conference on Science in Information Technology: Theory and Application of IT for Education, Industry and Society in Big Data Era, ICSITech 2017. editor / Rafal Drezewski ; Goutam Chakraborty ; Shah Nazir ; Lala Septem Riza ; Ummi Raba'ah Hashim ; Aji Prasetyo Wibawa ; Yaya Wihardi ; Andri Pranolo ; Enjun Junaeti ; Shi-Jinn Horng ; Heui Seok Lim ; Leonel Hernandez. Institute of Electrical and Electronics Engineers Inc., 2018. pp. 53-58 (Proceeding - 2017 3rd International Conference on Science in Information Technology: Theory and Application of IT for Education, Industry and Society in Big Data Era, ICSITech 2017).

@inproceedings{02d5f4a96d1548d6ae9b704eda3e3740,

title = "Data mining approach for short term load forecasting by combining wavelet transform and group method of data handling (WGMDH)",

abstract = "Forecasting is one of the essential activities at the electrical power company. Inaccurate forecasting will lead to wastage of operating costs. Data mining has been widely used to solve the problem of forecasting. In this study, we propose a method using data mining technique for doing electrical load forecasting, which is a combination of wavelet transform and group method of data handling (WGMDH). The proposed algorithm is used to predict the short-term power load which aims to improve the accuracy of forecasting. The results show that by using proposed algorithm better accuracy is achieved compared with the coefficient method which is used by Indonesian Power Company in Sumatera to forecast the electrical load. The method can improve the forecasting of electricity on average above 50% per year, both for the type of similar day and daily electricity load characteristic pattern.",

keywords = "classification, gmdh, load forecasting, stlf, wavelet transform",

author = "Trisna Yuniarti and Prajitno, {Isti Surjandari} and Erlinda Muslim and Enrico Laoh",

year = "2018",

month = jan,

day = "12",

doi = "10.1109/ICSITech.2017.8257085",

language = "English",

series = "Proceeding - 2017 3rd International Conference on Science in Information Technology: Theory and Application of IT for Education, Industry and Society in Big Data Era, ICSITech 2017",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

pages = "53--58",

editor = "Rafal Drezewski and Goutam Chakraborty and Shah Nazir and Riza, {Lala Septem} and Hashim, {Ummi Raba'ah} and Wibawa, {Aji Prasetyo} and Yaya Wihardi and Andri Pranolo and Enjun Junaeti and Shi-Jinn Horng and Lim, {Heui Seok} and Leonel Hernandez",

booktitle = "Proceeding - 2017 3rd International Conference on Science in Information Technology",

address = "United States",

note = "3rd International Conference on Science in Information Technology, ICSITech 2017 ; Conference date: 25-10-2017 Through 26-10-2017",

}

Yuniarti, T, Prajitno, IS , Muslim, E & Laoh, E 2018, Data mining approach for short term load forecasting by combining wavelet transform and group method of data handling (WGMDH). in R Drezewski, G Chakraborty, S Nazir, LS Riza, UR Hashim, AP Wibawa, Y Wihardi, A Pranolo, E Junaeti, S-J Horng, HS Lim & L Hernandez (eds), Proceeding - 2017 3rd International Conference on Science in Information Technology: Theory and Application of IT for Education, Industry and Society in Big Data Era, ICSITech 2017. Proceeding - 2017 3rd International Conference on Science in Information Technology: Theory and Application of IT for Education, Industry and Society in Big Data Era, ICSITech 2017, vol. 2018-January, Institute of Electrical and Electronics Engineers Inc., pp. 53-58, 3rd International Conference on Science in Information Technology, ICSITech 2017, Bandung, Indonesia, 25/10/17. https://doi.org/10.1109/ICSITech.2017.8257085

Data mining approach for short term load forecasting by combining wavelet transform and group method of data handling (WGMDH). / Yuniarti, Trisna; Prajitno, Isti Surjandari ; Muslim, Erlinda et al.
Proceeding - 2017 3rd International Conference on Science in Information Technology: Theory and Application of IT for Education, Industry and Society in Big Data Era, ICSITech 2017. ed. / Rafal Drezewski; Goutam Chakraborty; Shah Nazir; Lala Septem Riza; Ummi Raba'ah Hashim; Aji Prasetyo Wibawa; Yaya Wihardi; Andri Pranolo; Enjun Junaeti; Shi-Jinn Horng; Heui Seok Lim; Leonel Hernandez. Institute of Electrical and Electronics Engineers Inc., 2018. p. 53-58 (Proceeding - 2017 3rd International Conference on Science in Information Technology: Theory and Application of IT for Education, Industry and Society in Big Data Era, ICSITech 2017; Vol. 2018-January).

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

TY - GEN

T1 - Data mining approach for short term load forecasting by combining wavelet transform and group method of data handling (WGMDH)

AU - Yuniarti, Trisna

AU - Prajitno, Isti Surjandari

AU - Muslim, Erlinda

AU - Laoh, Enrico

PY - 2018/1/12

Y1 - 2018/1/12

N2 - Forecasting is one of the essential activities at the electrical power company. Inaccurate forecasting will lead to wastage of operating costs. Data mining has been widely used to solve the problem of forecasting. In this study, we propose a method using data mining technique for doing electrical load forecasting, which is a combination of wavelet transform and group method of data handling (WGMDH). The proposed algorithm is used to predict the short-term power load which aims to improve the accuracy of forecasting. The results show that by using proposed algorithm better accuracy is achieved compared with the coefficient method which is used by Indonesian Power Company in Sumatera to forecast the electrical load. The method can improve the forecasting of electricity on average above 50% per year, both for the type of similar day and daily electricity load characteristic pattern.

AB - Forecasting is one of the essential activities at the electrical power company. Inaccurate forecasting will lead to wastage of operating costs. Data mining has been widely used to solve the problem of forecasting. In this study, we propose a method using data mining technique for doing electrical load forecasting, which is a combination of wavelet transform and group method of data handling (WGMDH). The proposed algorithm is used to predict the short-term power load which aims to improve the accuracy of forecasting. The results show that by using proposed algorithm better accuracy is achieved compared with the coefficient method which is used by Indonesian Power Company in Sumatera to forecast the electrical load. The method can improve the forecasting of electricity on average above 50% per year, both for the type of similar day and daily electricity load characteristic pattern.

KW - classification

KW - gmdh

KW - load forecasting

KW - stlf

KW - wavelet transform

UR - http://www.scopus.com/inward/record.url?scp=85046653451&partnerID=8YFLogxK

U2 - 10.1109/ICSITech.2017.8257085

DO - 10.1109/ICSITech.2017.8257085

M3 - Conference contribution

T3 - Proceeding - 2017 3rd International Conference on Science in Information Technology: Theory and Application of IT for Education, Industry and Society in Big Data Era, ICSITech 2017

SP - 53

EP - 58

BT - Proceeding - 2017 3rd International Conference on Science in Information Technology

A2 - Drezewski, Rafal

A2 - Chakraborty, Goutam

A2 - Nazir, Shah

A2 - Riza, Lala Septem

A2 - Hashim, Ummi Raba'ah

A2 - Wibawa, Aji Prasetyo

A2 - Wihardi, Yaya

A2 - Pranolo, Andri

A2 - Junaeti, Enjun

A2 - Horng, Shi-Jinn

A2 - Lim, Heui Seok

A2 - Hernandez, Leonel

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 3rd International Conference on Science in Information Technology, ICSITech 2017

Y2 - 25 October 2017 through 26 October 2017

ER -

Yuniarti T, Prajitno IS , Muslim E, Laoh E. Data mining approach for short term load forecasting by combining wavelet transform and group method of data handling (WGMDH). In Drezewski R, Chakraborty G, Nazir S, Riza LS, Hashim UR, Wibawa AP, Wihardi Y, Pranolo A, Junaeti E, Horng SJ, Lim HS, Hernandez L, editors, Proceeding - 2017 3rd International Conference on Science in Information Technology: Theory and Application of IT for Education, Industry and Society in Big Data Era, ICSITech 2017. Institute of Electrical and Electronics Engineers Inc. 2018. p. 53-58. (Proceeding - 2017 3rd International Conference on Science in Information Technology: Theory and Application of IT for Education, Industry and Society in Big Data Era, ICSITech 2017). doi: 10.1109/ICSITech.2017.8257085

Data mining approach for short term load forecasting by combining wavelet transform and group method of data handling (WGMDH)

Abstract

Publication series

Conference

Keywords

Access to Document

Other files and links

Fingerprint

Cite this