Short-term individual residential load forecasting using an enhanced machine learning-based approach based on a feature engineering framework: A comparative study with deep learning methods

Author:

Forootani Ali,Rastegar MohammadORCID,Sami AshkanORCID

Publisher

Elsevier BV

Subject

Electrical and Electronic Engineering,Energy Engineering and Power Technology

Reference50 articles.

1. A review of the-state-of-the-art in data-driven approaches for building energy prediction;Sun;Energy Build.,2020

2. Multitask Bayesian spatiotemporal Gaussian processes for short-term load forecasting;Gilanifar;IEEE Trans. Ind. Electron.,2020

3. U.S. Energy Information Administration, “Frequently Asked Questions”, Accessed: July. 2021, [online]. Available: https://www.eia.gov/tools/faqs/faq.php?id=108&t=3.

4. Using smart meter data to improve the accuracy of intraday load forecasting considering customer behavior similarities;Quilumba;IEEE Trans. Smart Grid,2015

5. Clustering of electricity consumption behavior dynamics toward big data applications;Wang;IEEE Trans. Smart Grid,2016

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