Title :
Neural Network and Nonlinear Prime-Dual Interior Algorithm for Optimization Reactive Power Compensation
Author :
Fang, Lu ; Luo, An ; Xu, Xianyong ; Fang, Houhui
Author_Institution :
Coll. of Electr. & Inf. Eng., Hunan Univ., Changsha, China
Abstract :
This paper briefly analyses the conventional reactive power optimization compensation. The new method proposes a new optimization reactive power compensation for electrical network that uses neural network to predict electric network´s important parameters and nonlinear prime-dual interior algorithm to optimize reactive power. This intelligent control system diminishes power losses, and settles the problems that the electric power has complicated parameters and it is hard to constitute the compensation system model. The result shows that the effect of this intelligent control system is good and this algorithm is valid.
Keywords :
intelligent control; neural nets; optimisation; reactive power control; electrical network; intelligent control system; neural network; nonlinear prime dual interior algorithm; optimization; reactive power compensation; Artificial neural networks; Mathematical model; Neurons; Optimization; Prediction algorithms; Reactive power; neural network; nonlinear prime-dual interior algorithm; reactive power optimization compensation; static var compensator;
Conference_Titel :
Electrical and Control Engineering (ICECE), 2010 International Conference on
Conference_Location :
Wuhan
Print_ISBN :
978-1-4244-6880-5
DOI :
10.1109/iCECE.2010.951