Application of Intelligent Technologies for Control of Generator Sets in Power Supply Systems for Non-Traction Consumers
- https://doi.org/10.2991/aer.k.220308.002How to use a DOI?
- Railways; Power supply systems; Distributed generation plants; Intelligent control technologies; Fuzzy logic; Genetic algorithm; Neural network regulator
One of the key features of the current transition of the electric power industry to the smart grid technological platform is a large-scale application of distributed generation (DG) plants. The efficient operation of such plants is not possible without the development of new approaches to the control of their generators. In modern conditions, these approaches are based on intelligent technologies. This article discusses intelligent control technologies for DG plants used in power supply systems for non-traction consumers. The purpose of this research is to assess possible effects produced by intelligent technologies in the control of DG plants. The research simulation and calculations were carried out in MATLAB. Using the fuzzy logic system, we demonstrated the operation the proposed control system for the settings of the automatic regulators of the DG plants. Determination of optimal settings of the regulators was carried out using a genetic algorithm. The results of simulating neural network regulators of DG plants are presented. The simulation results revealed that the use of intelligent control technologies for DG plants increases the control accuracy and improves control quality indicators.
- © 2022 The Authors. Published by Atlantis Press International B.V.
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Cite this article
TY - CONF AU - Yuri Bulatov AU - Andrey Kryukov AU - Konstantin Suslov AU - Pio Lombardi AU - Przemysław Komarnicki PY - 2022 DA - 2022/03/24 TI - Application of Intelligent Technologies for Control of Generator Sets in Power Supply Systems for Non-Traction Consumers BT - Proceedings of the International Scientific and Practical Conference "Young Engineers of the Fuel and Energy Complex: Developing the Energy Agenda of the Future" (EAF 2021) PB - Atlantis Press SP - 7 EP - 13 SN - 2352-5401 UR - https://doi.org/10.2991/aer.k.220308.002 DO - https://doi.org/10.2991/aer.k.220308.002 ID - Bulatov2022 ER -