Voltage Stability Constrained Optimal Power Flow Using NSGA-II


Voltage stability has become an important issue in planning and operation of many power systems. This work includes multi-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). Base 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.

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Panuganti, S. , John, P. , Devraj, D. and Dash, S. (2013) Voltage Stability Constrained Optimal Power Flow Using NSGA-II. Computational Water, Energy, and Environmental Engineering, 2, 1-8. doi: 10.4236/cweee.2013.21001.

Conflicts of Interest

The authors declare no conflicts of interest.


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