Analysis of Artificial Neural Network Methods with Application in Reactive Power Flow Control

Author(s):  
Andressa Oliveira ◽  
Alessandra Picanco
2014 ◽  
Vol 19 (4) ◽  
pp. 397-405
Author(s):  
Leonardo Poltronieri Sampaio ◽  
Moacyr Aureliano Gomes de Brito ◽  
Guilherme de Azevedo e Melo ◽  
Carlos Alberto Canesin

2020 ◽  
Vol 9 (5) ◽  
pp. 1755-1765
Author(s):  
Mohammed Y. Suliman ◽  
Mahmood T. Al-Khayyat

The power flow controlled in the electric power network is one of the main factors that affected the modern power systems development. The unified power flow controller (UPFC) is a FACTS powerful device that can control both active and reactive power flow of parallel transmission lines branches. In this paper, modelling and simulation of active and reactive power flow control in parallel transmission lines using UPFC with adaptive neuro-fuzzy logic is proposed. The mathematical model of UPFC in power flow is also proposed. The results show the ability of UPFC to control the flow of powers components "active and reactive power" in the controlled line and thus the overall power regulated between lines.


Author(s):  
Vireshkumar Mathad ◽  
Gururaj Kulkarni

The series and shunt control scheme of unified power flow controller (UPFC) impacts the performance and stability of the power system during power swing. UPFC is the most versatile and voltage source converter device as it can control the real and reactive power of the transmission system simultaneously or selectively. When any system is subjected to any disturbance or fault, there are many challenges in damping power oscillation using conventional methods. This paper presents the neural network-based controller that replaces the proportional-integral (PI) controller to minimize the power oscillations. The performance of the artificial neural network (ANN) controller is evaluated on IEEE 9 bus system and compared with a conventional PI controller.


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