Proceedings of the Vth International workshop "Critical infrastructures: Contingency management, Intelligent, Agent-based, Cloud computing and Cyber security" (IWCI 2018)

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Neuro Fuzzy Control system for Distributed Generation Plants

Authors
Yury Bulatov, Andrey Kryukov
Corresponding Author
Yury Bulatov
Available Online August 2018.
DOI
10.2991/iwci-18.2018.3How to use a DOI?
Keywords
distributed regeneration, automatic excitation regulator, automatic regulator of rotor speed, matched tuning, neuro-fuzzy algorithms
Abstract

The transition of electric power industry to a new technological platform based on the concept of smart power grids with an active-and-adaptive network will allow to increase the efficiency of control, durability and reliability of power supply systems. The idea of applying the intelligent algorithms to control power grids becomes more pressing in case of wide using the distributed generation plants (DGP) and other grid active elements that allow to control power grid operation modes. The article describes the DGP consisting of synchronous generators that operate in various modes and often with poor power supply quality. To provide the parallel operation stability of synchronous turbo/ hydro generators of DGP, automatic excitation regulator (AER) and automatic regulator of rotor speed (ARRS) are used. Due to low inertia constant of distributed generation unit rotors, the problem of matched tuning of AER and ARRS becomes more topical. To increase stability and reliable integration of DGP in power grids, a control system built on a neuro-fuzzy match system is proposed. The system corrects AER/ ARRS settings. In this case, the following smart technologies were used: genetic algorithm to search optimal settings of AER and ARRS; a neuro-fuzzy network to identify an operation mode of a DGP and power grid; fuzzy interference to correct settings of AER/ ARRS in various modes of DGP operation. Based on modelling done in MATLAB system the efficiency of using the proposed neuro-fuzzy match system to identify DGP operation modes and to adaptively control matched tuning of AER and ARRS of synchronous generators is shown. If using the intellectual control system, one can decrease transition process time, generator voltage / frequency overcontrol, as well as provide reliability and durability of a power system in various operation modes of a DGP and power grids.

Copyright
© 2018, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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Volume Title
Proceedings of the Vth International workshop "Critical infrastructures: Contingency management, Intelligent, Agent-based, Cloud computing and Cyber security" (IWCI 2018)
Series
Advances in Intelligent Systems Research
Publication Date
August 2018
ISBN
978-94-6252-544-3
ISSN
1951-6851
DOI
10.2991/iwci-18.2018.3How to use a DOI?
Copyright
© 2018, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

Cite this article

risenwbib
TY  - CONF
AU  - Yury Bulatov
AU  - Andrey Kryukov
PY  - 2018/08
DA  - 2018/08
TI  - Neuro Fuzzy Control system for Distributed Generation Plants
BT  - Proceedings of the Vth International workshop "Critical infrastructures: Contingency management, Intelligent, Agent-based, Cloud computing and Cyber security" (IWCI 2018)
PB  - Atlantis Press
SP  - 13
EP  - 19
SN  - 1951-6851
UR  - https://doi.org/10.2991/iwci-18.2018.3
DO  - 10.2991/iwci-18.2018.3
ID  - Bulatov2018/08
ER  -