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Article

Artificial Neural Network Controller in Two-Area and Five-Area System with Security Attack and Game-Theory Based Defender Action

1
Electrical and Electronics Engineering Department, Jawaharlal Nehru Technological University Anantapur, Ananthapuramu, Anantapur 515002, Andhra Pradesh, India
2
Electrical and Electronics Engineering Department, Vallurupalli Nageswara Rao Vignana Jyothi Institute of Engineering and Technology, Hyderabad 500090, Telangana, India
*
Author to whom correspondence should be addressed.
Academic Editors: Tek Tjing Lie, Nurhidajat Sisworahardjo, Sebastian A. Nugroho and Yi Guo
Energies 2022, 15(15), 5715; https://doi.org/10.3390/en15155715 (registering DOI)
Received: 15 June 2022 / Revised: 18 July 2022 / Accepted: 1 August 2022 / Published: 5 August 2022
(This article belongs to the Special Issue Control, Optimization, and Cybersecurity of Electric Power Systems)
Smart grids are the latest technology to generate and dispatch an optimal amount of power. Thus, there is a need for stability analysis in smart grid systems. If the smart grid is incorporated into the power system, then the phasor measurement unit (PMU) is used to measure the voltage, current, and frequency. Additionally, the central control unit monitors and controls the power. However, there is a possibility of inserting wrong data into the smart grid as the PMUs are transmitting the data through the Internet and other wireless protocols. There is a need to find solutions to this threat to make the power flow safe and secure in the future. In this paper, two-area load frequency control (LFC) is used for testing the game-theory based security treatment and improving the system’s stability by using an artificial neural network. The two-area system and five-area system are used to test the stability of the power system. View Full-Text
Keywords: artificial neural network; game-theory; load frequency control; multi-area power system artificial neural network; game-theory; load frequency control; multi-area power system
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MDPI and ACS Style

Khadarvali, S.; Madhusudhan, V.; Kiranmayi, R. Artificial Neural Network Controller in Two-Area and Five-Area System with Security Attack and Game-Theory Based Defender Action. Energies 2022, 15, 5715. https://doi.org/10.3390/en15155715

AMA Style

Khadarvali S, Madhusudhan V, Kiranmayi R. Artificial Neural Network Controller in Two-Area and Five-Area System with Security Attack and Game-Theory Based Defender Action. Energies. 2022; 15(15):5715. https://doi.org/10.3390/en15155715

Chicago/Turabian Style

Khadarvali, S., V. Madhusudhan, and R. Kiranmayi. 2022. "Artificial Neural Network Controller in Two-Area and Five-Area System with Security Attack and Game-Theory Based Defender Action" Energies 15, no. 15: 5715. https://doi.org/10.3390/en15155715

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