A review of hydrogen-based hybrid renewable energy systems: Simulation and optimization with artificial intelligence. Issue 1 (1st March 2022)

• Record Type: Journal Article
• Authors: Cai, Wenchao; Li, Chenglong; Agbossou, Kodjo; Bénard, Pierre; Xiao, Jinsheng
• Is Part Of: Journal of physics. Volume 2208:Issue 1(2022)
• Publication Date: 2022-03-01
• Subjects: Physics -- Congresses; 530.5
• DOI: 10.1088/1742-6596/2208/1/012012
• Languages: English
• ISSNs: 1742-6588

Abstract

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.