Staff View: Correlation and wavelet-based short-term load forecasting using anfis

Correlation and wavelet-based short-term load forecasting using anfis

Objective: This paper addresses the issue of model inputs selection before the forecasting exercise. Appropriate data analysis is one of the basic steps in obtaining accurate load forecast. It shapes the forecasting data in to working data by reducing the variation between the individual forecasting...

Full description

Saved in:

Bibliographic Details
Main Authors:	Mustapha, M., Mustafa, M. W., Khalid, S. N., Abubakar, I., Abdilahi, A. M.
Format:	Article
Published:	Indian Society for Education and Environment 2016
Subjects:	TK Electrical engineering. Electronics Nuclear engineering
Online Access:	http://eprints.utm.my/id/eprint/71209/ https://www.scopus.com/inward/record.uri?eid=2-s2.0-85007518496&doi=10.17485%2fijst%2f2016%2fv9i46%2f107141&partnerID=40&md5=b86776352f0743be12f9c26bf14b6e2c
Tags:	Add Tag No Tags, Be the first to tag this record!

id	my.utm.71209
record_format	eprints
spelling	my.utm.712092017-11-15T04:07:06Z http://eprints.utm.my/id/eprint/71209/ Correlation and wavelet-based short-term load forecasting using anfis Mustapha, M. Mustafa, M. W. Khalid, S. N. Abubakar, I. Abdilahi, A. M. TK Electrical engineering. Electronics Nuclear engineering Objective: This paper addresses the issue of model inputs selection before the forecasting exercise. Appropriate data analysis is one of the basic steps in obtaining accurate load forecast. It shapes the forecasting data in to working data by reducing the variation between the individual forecasting variables, or reduces the number of the model inputs. Also, the information received from data analysis determines the method to be used, or how to use it. Methods/Statistical Analysis: It employs the use of correlation analysis to select the forecasting variables, and wavelet transforms to decompose the selected data in to a number of approximations. The purpose is to select the actual forecasting variables, and to limit the variation between them (model inputs). ANFIS was used to forecast the load using the processed data. Findings: From the result obtained, it was observed that selecting the data based on correlation analysis, and wavelet transform improve the accuracy of the forecast, and enhanced the forecasting speed. Applications/Improvements: Improving the forecasting accuracy will save the utility economically, and improving the speed will enhance the time taken to make crucial decisions in power system operation. Indian Society for Education and Environment 2016 Article PeerReviewed Mustapha, M. and Mustafa, M. W. and Khalid, S. N. and Abubakar, I. and Abdilahi, A. M. (2016) Correlation and wavelet-based short-term load forecasting using anfis. Indian Journal of Science and Technology, 9 (46). ISSN 0974-6846 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85007518496&doi=10.17485%2fijst%2f2016%2fv9i46%2f107141&partnerID=40&md5=b86776352f0743be12f9c26bf14b6e2c
institution	Universiti Teknologi Malaysia
building	UTM Library
collection	Institutional Repository
continent	Asia
country	Malaysia
content_provider	Universiti Teknologi Malaysia
content_source	UTM Institutional Repository
url_provider	http://eprints.utm.my/
topic	TK Electrical engineering. Electronics Nuclear engineering
spellingShingle	TK Electrical engineering. Electronics Nuclear engineering Mustapha, M. Mustafa, M. W. Khalid, S. N. Abubakar, I. Abdilahi, A. M. Correlation and wavelet-based short-term load forecasting using anfis
description	Objective: This paper addresses the issue of model inputs selection before the forecasting exercise. Appropriate data analysis is one of the basic steps in obtaining accurate load forecast. It shapes the forecasting data in to working data by reducing the variation between the individual forecasting variables, or reduces the number of the model inputs. Also, the information received from data analysis determines the method to be used, or how to use it. Methods/Statistical Analysis: It employs the use of correlation analysis to select the forecasting variables, and wavelet transforms to decompose the selected data in to a number of approximations. The purpose is to select the actual forecasting variables, and to limit the variation between them (model inputs). ANFIS was used to forecast the load using the processed data. Findings: From the result obtained, it was observed that selecting the data based on correlation analysis, and wavelet transform improve the accuracy of the forecast, and enhanced the forecasting speed. Applications/Improvements: Improving the forecasting accuracy will save the utility economically, and improving the speed will enhance the time taken to make crucial decisions in power system operation.
format	Article
author	Mustapha, M. Mustafa, M. W. Khalid, S. N. Abubakar, I. Abdilahi, A. M.
author_facet	Mustapha, M. Mustafa, M. W. Khalid, S. N. Abubakar, I. Abdilahi, A. M.
author_sort	Mustapha, M.
title	Correlation and wavelet-based short-term load forecasting using anfis
title_short	Correlation and wavelet-based short-term load forecasting using anfis
title_full	Correlation and wavelet-based short-term load forecasting using anfis
title_fullStr	Correlation and wavelet-based short-term load forecasting using anfis
title_full_unstemmed	Correlation and wavelet-based short-term load forecasting using anfis
title_sort	correlation and wavelet-based short-term load forecasting using anfis
publisher	Indian Society for Education and Environment
publishDate	2016
url	http://eprints.utm.my/id/eprint/71209/ https://www.scopus.com/inward/record.uri?eid=2-s2.0-85007518496&doi=10.17485%2fijst%2f2016%2fv9i46%2f107141&partnerID=40&md5=b86776352f0743be12f9c26bf14b6e2c
_version_	1643656136368324608
score	13.211869

Correlation and wavelet-based short-term load forecasting using anfis

Similar Items