Hybrid Intelligent Modelling in Renewable Energy Sources-Based Microgrid. A Variable Estimation of the Hydrogen Subsystem Oriented to the Energy Management Strategy

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- Investigación (EPEF) [589]
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Hybrid Intelligent Modelling in Renewable Energy Sources-Based Microgrid. A Variable Estimation of the Hydrogen Subsystem Oriented to the Energy Management StrategyAutor(es)
Data
2020Cita bibliográfica
Casteleiro-Roca, J.-L.; Vivas, F.J.; Segura, F.; Barragán, A.J.; Calvo-Rolle, J.L.; Andújar, J.M. Hybrid Intelligent Modelling in Renewable Energy Sources-Based Microgrid. A Variable Estimation of the Hydrogen Subsystem Oriented to the Energy Management Strategy. Sustainability 2020, 12, 10566. https://doi.org/10.3390/su122410566
Resumo
[Abstract] This work deals with the prediction of variables for a hydrogen energy storage system integrated into a microgrid. Due to the fact that this kind of system has a nonlinear behaviour, the use of traditional techniques is not accurate enough to generate good models of the system under study. Then, a hybrid intelligent system, based on clustering and regression techniques, has been developed and implemented to predict the power, the hydrogen level and the hydrogen system degradation. In this research, a hybrid intelligent model was created and validated over a dataset from a lab-size migrogrid. The achieved results show a better performance than other well-known classical regression methods, allowing us to predict the hydrogen consumption/generation with a mean absolute error of 0.63% with the test dataset respect to the maximum power of the system.
Palabras chave
Clustering
Prediction
Regression
Hydrogen-based systems
Renewable sources-based microgrid
Hybrid model
Prediction
Regression
Hydrogen-based systems
Renewable sources-based microgrid
Hybrid model
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Creative Commons License Attribution 4.0 (CC BY 4.0)
ISSN
2071-1050