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A Review of Hydrogen-based Hybrid Renewable Energy Systems: Simulation and Optimization with Artificial Intelligence


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.

Funding source: This research is related to a hydrogen energy storage and safety project funded by the National Natural Science Foundation of China (52176191) and battery energy storage and safety projects funded by the Research Programme of Wuhan University of Technology Chongqing Research Institute (YF2021-08), and the Science and Technology Development Foundation of CMVR (China Merchants Vehicle Research Institute) (20AKC3). Wenchao Cai thanks the support from CSC (China Scholarship Council) and FRQNT (Fonds de Recherche du Québec-Nature et Technologies) for the PBEEE fellowship (No.308465).
Related subjects: Applications & Pathways

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