LAPSE:2023.15195
Published Article

LAPSE:2023.15195
Using Group Predictive Voltage and Frequency Regulators of Distributed Generation Plants in Cyber-Physical Power Supply Systems
March 2, 2023
Abstract
The widespread use of distributed generation (DG) plants in cyber-physical power supply systems (CPPSS) requires solving the complex problem of setting their regulators. The presented study aimed to determine the performance of the group predictive voltage and frequency regulators of DG plants in CPPSS. These studies were conducted in the MatLab environment on the CPPSS models with gas turbine units and with a small-scale hydroelectric power plant. The proposed method for tuning group predictive regulators makes it possible to improve the quality control indices. The research has established that with an additional load connected, the maximum voltage dip is reduced by a factor of 3.5 compared to conventional control regulators. In addition, the time of a transient process for the generator rotor speed is decreased by a factor of 3. In the case of a short-term short circuit, predictive regulators can reduce the time of the transient process by a factor of 1.5 and the overshoot by more than 2 times. The simulation results have confirmed the efficiency of group predictive regulators when used in DG plants, i.e., improvement of the quality of control processes in various operating modes.
The widespread use of distributed generation (DG) plants in cyber-physical power supply systems (CPPSS) requires solving the complex problem of setting their regulators. The presented study aimed to determine the performance of the group predictive voltage and frequency regulators of DG plants in CPPSS. These studies were conducted in the MatLab environment on the CPPSS models with gas turbine units and with a small-scale hydroelectric power plant. The proposed method for tuning group predictive regulators makes it possible to improve the quality control indices. The research has established that with an additional load connected, the maximum voltage dip is reduced by a factor of 3.5 compared to conventional control regulators. In addition, the time of a transient process for the generator rotor speed is decreased by a factor of 3. In the case of a short-term short circuit, predictive regulators can reduce the time of the transient process by a factor of 1.5 and the overshoot by more than 2 times. The simulation results have confirmed the efficiency of group predictive regulators when used in DG plants, i.e., improvement of the quality of control processes in various operating modes.
Record ID
Keywords
automatic speed regulator, automatic voltage regulator, cyber-physical power supply systems, distributed generation plant, group regulation, Modelling, predictive control algorithms, synchronous generator
Subject
Suggested Citation
Bulatov Y, Kryukov A, Suslov K. Using Group Predictive Voltage and Frequency Regulators of Distributed Generation Plants in Cyber-Physical Power Supply Systems. (2023). LAPSE:2023.15195
Author Affiliations
Bulatov Y: Department of Energy, Bratsk State University, 665730 Bratsk, Russia [ORCID]
Kryukov A: Department of Electric Power Engineering of Transport, Irkutsk State Transport University, 664074 Irkutsk, Russia; Department of Power Supply and Electrical Engineering, Irkutsk National Research Technical University, 664074 Irkutsk, Russia
Suslov K: Department of Power Supply and Electrical Engineering, Irkutsk National Research Technical University, 664074 Irkutsk, Russia; Department of Energy, Transbaikal State University, 672039 Chita, Russia [ORCID]
Kryukov A: Department of Electric Power Engineering of Transport, Irkutsk State Transport University, 664074 Irkutsk, Russia; Department of Power Supply and Electrical Engineering, Irkutsk National Research Technical University, 664074 Irkutsk, Russia
Suslov K: Department of Power Supply and Electrical Engineering, Irkutsk National Research Technical University, 664074 Irkutsk, Russia; Department of Energy, Transbaikal State University, 672039 Chita, Russia [ORCID]
Journal Name
Energies
Volume
15
Issue
4
First Page
1253
Year
2022
Publication Date
2022-02-09
ISSN
1996-1073
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Original Submission
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PII: en15041253, Publication Type: Journal Article
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LAPSE:2023.15195
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https://doi.org/10.3390/en15041253
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Mar 2, 2023
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