Creating optimized machine learning pipelines for PV power generation forecasting using the grid search and tree-based pipeline optimization tool

Creating optimized machine learning pipelines for PV power generation forecasting using the grid search and tree-based pipeline optimization tool

AbstractDemand for electric power, especially amidst limited fossil fuel-based generation capacity, has elevated renewable energy sources to a forefront solution for the growing energy needs. Solar energy, a key renewable source through photovoltaic (PV) panels, faces challenges such as intermittenc...

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Bibliographic Details
Main Authors: Hussam J. Khasawneh, Zaid A. Ghazal, Waseem M. Al-Khatib, Ahmad M. Al-Hadi, Zaid M. Arabiyat
Format: Article
Language:English
Published: Taylor & Francis Group 2024-12-01
Series:Cogent Engineering
Subjects:
Solar energy forecasting
renewable energy systems
energy scheduling optimization
demand response
machine learning
genetic algorithm
Online Access:https://www.tandfonline.com/doi/10.1080/23311916.2024.2323818

Internet

https://www.tandfonline.com/doi/10.1080/23311916.2024.2323818

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