A review of hydrogen-based hybrid renewable energy systems: Simulation and optimization with artificial intelligence

Cai, W., Li, C., Agbossou, K., Bénard, P. et Xiao, J. (2022). A review of hydrogen-based hybrid renewable energy systems: Simulation and optimization with artificial intelligence. Journal of Physics: Conference Series, 2208 . Article 012012. ISSN 1742-6588 1742-6596 DOI 10.1088/1742-6596/2208/1/012012

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Résumé

Abstract

With the massive use of traditional fossil fuels, greenhouse gas emissions are increasing, and environmental pollution is becoming an increasingly serious problem, which led to an imminent energy transition. Therefore, the development and application of renewable energy are particularly important. This paper reviews a wide range of issues associated with hybrid renewable energy systems (HRESs). The issues concerning system configurations, energy storage options, simulation and optimization with artificial intelligence are discussed in detail. Storage technology options are introduced for stand-alone (off-grid) and grid-connected (on-grid) HRESs. Different optimization methodologies, including classical techniques, intelligent techniques, hybrid techniques and software tools for sizing system components, are presented. Besides, the artificial intelligence methods for optimizing the solar/wind HRESs are discussed in detail.

Type de document:	Article
Mots-clés libres:	Artificial intelligence Computer aided software engineering Fossil fuels Gas emissions Greenhouse gases Development and applications Energy system optimizations Energy system simulations Energy transitions Environmental pollutions Greenhouse gas emissions Hybrid renewable energies Renewable energies Simulation and optimization Systems Configuration Renewable energy resources
Date de dépôt:	22 janv. 2026 13:19
Dernière modification:	22 janv. 2026 13:19
Version du document déposé:	Version officielle de l'éditeur
URI:	https://depot-e.uqtr.ca/id/eprint/12541

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