Short-Term Load Forecasting with a Novel Wavelet-Based Ensemble Method

“Short-term load forecasting (STLF)” is increasingly significant because of the extensive use of distributed energy resources, the incorporation of intermitted RES, and the implementation of DSM. This paper provides a novel ensemble forecasting model with wavelet transform for the STLF depending on...

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Main Authors: V. Y. Kondaiah, B. Saravanan
Format: Article
Language:English
Published: MDPI AG 2022-07-01
Series:Energies
Subjects:
Online Access:https://www.mdpi.com/1996-1073/15/14/5299
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author V. Y. Kondaiah
B. Saravanan
author_facet V. Y. Kondaiah
B. Saravanan
author_sort V. Y. Kondaiah
collection DOAJ
description “Short-term load forecasting (STLF)” is increasingly significant because of the extensive use of distributed energy resources, the incorporation of intermitted RES, and the implementation of DSM. This paper provides a novel ensemble forecasting model with wavelet transform for the STLF depending on the decomposition principle of load profiles. The model can effectively capture the portion of daily load profiles caused by seasonal variations. The results indicate that it is possible to improve STLF accuracy with the proposed method. The proposed approach is tested with the data taken from Ontario’s electricity market in Canada. The results show that the proposed technique performs well in-terms of prediction when compared to existing traditional and cutting-edge methods. The performance of the model was validated with different datasets. Moreover, this approach can provide accurate load forecasting using ensemble models. Therefore, utilities and smart grid operators can use this approach as an additional decision-making tool to improve their real-time decisions.
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spelling doaj.art-81b341c4ea3c49e291af877aa94f3a0c2023-11-30T23:09:03ZengMDPI AGEnergies1996-10732022-07-011514529910.3390/en15145299Short-Term Load Forecasting with a Novel Wavelet-Based Ensemble MethodV. Y. Kondaiah0B. Saravanan1School of Electrical Engineering, Vellore Institute of Technology, Vellore 632014, Tamilnadu, IndiaSchool of Electrical Engineering, Vellore Institute of Technology, Vellore 632014, Tamilnadu, India“Short-term load forecasting (STLF)” is increasingly significant because of the extensive use of distributed energy resources, the incorporation of intermitted RES, and the implementation of DSM. This paper provides a novel ensemble forecasting model with wavelet transform for the STLF depending on the decomposition principle of load profiles. The model can effectively capture the portion of daily load profiles caused by seasonal variations. The results indicate that it is possible to improve STLF accuracy with the proposed method. The proposed approach is tested with the data taken from Ontario’s electricity market in Canada. The results show that the proposed technique performs well in-terms of prediction when compared to existing traditional and cutting-edge methods. The performance of the model was validated with different datasets. Moreover, this approach can provide accurate load forecasting using ensemble models. Therefore, utilities and smart grid operators can use this approach as an additional decision-making tool to improve their real-time decisions.https://www.mdpi.com/1996-1073/15/14/5299STLFwavelet transformsmart gridensemble methodload forecastDSM
spellingShingle V. Y. Kondaiah
B. Saravanan
Short-Term Load Forecasting with a Novel Wavelet-Based Ensemble Method
Energies
STLF
wavelet transform
smart grid
ensemble method
load forecast
DSM
title Short-Term Load Forecasting with a Novel Wavelet-Based Ensemble Method
title_full Short-Term Load Forecasting with a Novel Wavelet-Based Ensemble Method
title_fullStr Short-Term Load Forecasting with a Novel Wavelet-Based Ensemble Method
title_full_unstemmed Short-Term Load Forecasting with a Novel Wavelet-Based Ensemble Method
title_short Short-Term Load Forecasting with a Novel Wavelet-Based Ensemble Method
title_sort short term load forecasting with a novel wavelet based ensemble method
topic STLF
wavelet transform
smart grid
ensemble method
load forecast
DSM
url https://www.mdpi.com/1996-1073/15/14/5299
work_keys_str_mv AT vykondaiah shorttermloadforecastingwithanovelwaveletbasedensemblemethod
AT bsaravanan shorttermloadforecastingwithanovelwaveletbasedensemblemethod