"

Cookies ussage consent

I agree.

Our site saves small pieces of text information (cookies) on your device in order to deliver better content and for statistical purposes. You can disable the usage of cookies by changing the settings of your browser. By browsing our site without changing the browser settings you grant us permission to store that information on your device.

SVC adaptive controller based on ANN by using radial basis function and multilayer perceptron to improve voltage stability

KADIR ABACI1,* , ZAFER ÖZER2, M. ALI YALÇIN3, ERCAN KÖSE4

Affiliation

  1. Electrical and Ele ctronics Engineering Department, Mersin University, Turkey
  2. Departement Distance learning, Tece Campus, Mersin University, Turkey
  3. Electrical and Electronics Engineering Department, Esentepe Campus, 54187, Turkey
  4. Mechatronics Engineer ing Department, Tarsus Campus, Mersin University, Turkey

Abstract

Reactive power co ntrol is the most efficient and popular voltage control method, especially for variable active power demand. Static Var Compensators (SVCs) are being increasingly employed in modern power systems. This paper proposes an Artificial Neural Network (ANN) base d Static Var Compensator (SVC) controller and a novel bus reducing methud.for power systems. Two types of artificial neural network controllers namely are Multi Layer Perceptrons (MLP) with back propagation learning algorithm, and Radial Basis Function (RB F) network are used. In the simulations, a variable power demand is modelled as a disturbance effect and voltage stability control was done at the operating points with SVC. It is shown that the voltage output was successfully regulated and desired voltage value are obtained quickly. Transient responses for voltage and susceptance show that SVC controller with ANNs provide optimum system performance for a disturbance effect. Performance of ANN based SVC controllers were tested. The effectiveness and feasibi lity of the proposed control is demonstrated with the simple two bus system and three machine nine bus WSCC system. The results show that improvement especially ANN based RBF controller has better performance the MLP based controller..

Keywords

Voltage Stability, Artificial Neural Network (ANN), Multi Layer Perceptrons (MLP), Radial Basis Function (RBF), Static Var Compensator (SVC).

Citation

KADIR ABACI, ZAFER ÖZER, M. ALI YALÇIN, ERCAN KÖSE, SVC adaptive controller based on ANN by using radial basis function and multilayer perceptron to improve voltage stability, Optoelectronics and Advanced Materials - Rapid Communications, 9, 3-4, March-April 2015, pp.537-546 (2015).

Submitted at: May 20, 2014

Accepted at: March 19, 2015