Journal
IEEE ACCESS
Volume 8, Issue -, Pages 213748-213757Publisher
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/ACCESS.2020.3037134
Keywords
Adaptive control; GMDH; adaptive learning; energy management; PV panels; solar energy; machine learning
Categories
Funding
- Project Support of Research and Development activities of the J. Selye University in the field of Digital Slovakia and creative industry of the Research and Innovation Operational Programme
- European Regional Development Fund [NFP313010T504]
- project in the framework of the New Szechenyi Plan [EFOP-3.6.2-16-2017-00016]
- European Union
- European Social Fund
- Alexander von Humboldt Foundation
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In this paper a new control system on basis of group method for data handling neural networks (GMDH-NNs) is designed for voltage and power regulation in the photovoltaic (PV)/Fuel/Battery systems. The dynamics of all subsystems are considered to be fully uncertain. The suggested GMDH-NN is learned using online tuning rules that are concluded through the robustness investigation. The challenging operation conditions such as variable unknown dynamics, unknown temperature and irradiation and suddenly changes in output load are taken into account and are handled by suggested control system. The superiority of the suggested method is shown by simulation in several scenarios and comparison with other techniques.
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