Abstract
This paper presents the energy saving technology of a photovoltaic system’s control. Based on the photovoltaic system’s state, the fuzzy selective neural net creates an effective control signal under random perturbations. The architecture of the selective neural net was evolved using a neuro-evolutionary approach. The validity and advantages of the proposed energy saving technology of a photovoltaic system’s control are demonstrated using numerical simulations. The simulation results show that the proposed technology achieves real-time control speed and competitive performance, as compared to a classical control scheme with a PID controller.
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The authors wish also to thank Daniel Foty and the reviewers for valuable comments.
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Engel, E.A., Kovalev, I.V. (2016). The Energy Saving Technology of a Photovoltaic System’s Control on the Basis of the Fuzzy Selective Neuronet. In: Tan, Y., Shi, Y., Li, L. (eds) Advances in Swarm Intelligence. ICSI 2016. Lecture Notes in Computer Science(), vol 9713. Springer, Cham. https://doi.org/10.1007/978-3-319-41009-8_41
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DOI: https://doi.org/10.1007/978-3-319-41009-8_41
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