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

Sustainability

Francisca Segura¹  JoséManuel Andújar¹  FranciscoJosé Vivas¹  AntonioJavier Barragán¹  JoseLuis Calvo-Rolle²  José-Luis Casteleiro-Roca² 

[1] Department of Electronic Engineering, Computer Systems and Automatic, Campus de El Carmen, University of Huelva, 21071 Huelva, Spain;Department of Industrial Engineering, University of A Coruña, CTC, CITIC, 15405 Ferrol, Spain;

关键词: clustering;    prediction;    regression;    hydrogen-based systems;    renewable sources-based microgrid;    hybrid model;   

DOI  :  10.3390/su122410566

来源: DOAJ

【 摘 要 】

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.

【 授权许可】

Unknown