@article{(Open Science Index):https://publications.waset.org/pdf/10001889,
	  title     = {Using Artificial Neural Network Algorithm for Voltage Stability Improvement},
	  author    = {Omid Borazjani and  Mahmoud Roosta and  Khodakhast Isapour and  Ali Reza Rajabi},
	  country	= {},
	  institution	= {},
	  abstract     = {This paper presents an application of Artificial Neural
Network (ANN) algorithm for improving power system voltage
stability. The training data is obtained by solving several normal and
abnormal conditions using the Linear Programming technique. The
selected objective function gives minimum deviation of the reactive
power control variables, which leads to the maximization of
minimum Eigen value of load flow Jacobian. The considered reactive
power control variables are switchable VAR compensators, OLTC
transformers and excitation of generators. The method has been
implemented on a modified IEEE 30-bus test system. The results
obtain from the test clearly show that the trained neural network is
capable of improving the voltage stability in power system with a
high level of precision and speed.},
	    journal   = {International Journal of Electrical and Computer Engineering},
	  volume    = {9},
	  number    = {3},
	  year      = {2015},
	  pages     = {365 - 370},
	  ee        = {https://publications.waset.org/pdf/10001889},
	  url   	= {https://publications.waset.org/vol/99},
	  bibsource = {https://publications.waset.org/},
	  issn  	= {eISSN: 1307-6892},
	  publisher = {World Academy of Science, Engineering and Technology},
	  index 	= {Open Science Index 99, 2015},