Extended-Window Algorithms for Model Prediction Applied to Hybrid Power Systems

• Published in: Technologies (Basel) Vol. 12; no. 1; p. 6
• Main Authors: Wang, Fu-Cheng, Huang, Hsiao-Tzu
• Format: Journal Article
• Language: English
• Published: Basel MDPI AG 01.01.2024
• Subjects: Algorithms; Alternative energy sources; Artificial intelligence; Back up systems; Batch processes; Costs; Electricity distribution; Energy consumption; Energy resources; Energy storage; extended window; fuel cell; Fuel cells; Genetic algorithms; hybrid power; Hybrid systems; Hydrogen; Hydrogen production; Machine learning; management; Optimization; Photovoltaic cells; Power management; prediction; Prediction models; Radiation; Renewable resources; Solar energy; Solar radiation; System effectiveness; Wind power; Taiwan

This paper proposes extended-window algorithms for model prediction and applies them to optimize hybrid power systems. We consider a hybrid power system comprising solar panels, batteries, a fuel cell, and a chemical hydrogen generation system. The proposed algorithms enable the periodic updating of...