Title :
Feasibility of application of artificial neural network (ANN) controllers for HVDC systems control
Author :
Gamal, A.B. ; El-Sadek, M.Z. ; Mubarak, Y.A.
Author_Institution :
Dept. of Electr. Eng., Cairo Univ., Giza, Egypt
Abstract :
Up till now conventional controls are used with either two terminals links or multi-terminal HVDC systems. In this study the recent artificial neural network (ANN) control is applied to the HVDC system control. Suggested novel (ANN) control is used in creating a new supplementary control signal added to the input of the conventional controller in a special manner. The control is applied to the rectifier station. Transient time simulations of the nonlinear system performance after certain disturbances have proved the effectiveness of such (ANN) controls, which act very fast to follow transient system conditions and to restore its stability subsequent to severe disturbances through fast oscillation damping. Numerical integration is used to solve the nonlinear system equations.
Keywords :
HVDC power transmission; damping; integration; neurocontrollers; nonlinear equations; nonlinear systems; power system control; power system simulation; power system transient stability; rectifier substations; ANN controllers; HVDC systems control; artificial neural network; nonlinear system equations; nonlinear system performance; numerical integration; oscillation damping; rectifier station; stability; supplementary control signal; transient time simulations; Artificial neural networks; Control systems; HVDC transmission; Neural networks; Nonlinear control systems; Power engineering and energy; Power system control; Power system dynamics; Rectifiers; Signal processing;
Conference_Titel :
Universities Power Engineering Conference, 2004. UPEC 2004. 39th International
Print_ISBN :
1-86043-365-0