%0 Journal Article
%T Voltage Stability Constrained Optimal Power  Flow Using NSGA-II
%A Sandeep Panuganti
%A Preetha Roselyn John
%A Durairaj Devraj
%A Subhransu Sekhar Dash
%J Computational Water, Energy, and Environmental Engineering
%P 1-8
%@ 2168-1570
%D 2013
%I Scientific Research Publishing
%R 10.4236/cweee.2013.21001
%X <p class=\"MsoNormal\" style=\"text-align:justify;\">
	<span lang=\"EN-US\">Voltage stability has become an important issue in
planning and operation of many power systems. This work includes multi</span><span lang=\"EN-US\">-</span><span lang=\"EN-US\">objective
evolutionary algorithm techniques such as Genetic Algorithm (GA) and
Non-dominated Sorting Genetic Algorithm II (NSGA II) approach for solving
Voltage Stability Constrained-Optimal Power Flow (VSC-OPF).</span><span lang=\"EN-US\"> </span><span lang=\"EN-US\">Base</span><span lang=\"EN-US\"> </span><span lang=\"EN-US\">case
generator power output, voltage magnitude of generator buses are taken as the
control variables and maximum L-index of load buses is used to specify the
voltage stability level of the system. Multi-Objective OPF, formulated as a multi-objective
mixed integer nonlinear optimization problem, minimizes fuel cost and minimizes
emission of gases, as well as improvement of voltage profile in the system.
NSGA-II based OPF-case 1-Two objective-Min Fuel cost and Voltage stability
index; case 2-Three objective-Min Fuel cost, Min Emission cost and Voltage
stability index. The above method is tested on standard IEEE 30-bus test system
and simulation results are done for base case and the two severe contingency
cases and also on loaded conditions.</span> 
</p>
%K Voltage Stability
%K Optimal Power Flow
%K Multi Objective Evolutionary Algorithms
%U http://www.scirp.org/journal/PaperInformation.aspx?PaperID=27473