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Genetic-algorithm-based optimal power flow for security enhancement

Genetic-algorithm-based optimal power flow for security enhancement

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Power-system-security enhancement deals with the task of taking remedial action against possible network overloads in the system following the occurrence of contingencies. Line overload can be removed by means of generation redispatching and by adjustment of phase-shifting transformers. The paper presents a genetic-algorithm (GA) based OPF algorithm for identifying the optimal values of generator active-power output and the angle of the phase-shifting transformer. The locations of phase shifters are selected based on sensitivity analysis. To overcome the shortcomings associated with the representation of real and integer variables using the binary string in the GA population, the control variables are represented in their natural form. Also, crossover and mutation operators which can deal directly with integers and floating-point numbers are used. Simulation results on IEEE 30-bus and IEEE 118-bus test systems are presented and compared with the results of other approaches.

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