Performance estimation technique for solar-wind hybrid systems: A machine learning approach

Performance estimation technique for solar-wind hybrid systems: A machine learning approach

This study introduces a novel method to assess solar-wind hybrid energy systems, utilizing data analysis for key metrics (Performance Yields YR, Capacity Factor CF, and Performance Ratio PR), focused on their uncertainties estimation. Employing a bootstrapped-based K-means algorithm on features from...

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Bibliographic Details
Main Authors: Fabian Salazar-Caceres, Harrynson Ramirez-Murillo, Carlos Andrés Torres-Pinzón, Martha Patricia Camargo-Martínez
Format: Article
Language:English
Published: Elsevier 2024-01-01
Series:Alexandria Engineering Journal
Subjects:
Bootstrap method
Clustering analysis
Hybrid power systems
Machine learning
Probability density function
Solar power generation
Online Access:http://www.sciencedirect.com/science/article/pii/S1110016823011213

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http://www.sciencedirect.com/science/article/pii/S1110016823011213

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