13-04-2016, 07:03 PM
16-04-2016, 09:43 AM
genetic algorithm for 30 bus system matlab code
Abstract
Reactive power optimization plays an important role in the functioning of the power system. Optimal planning of reactive power reduces the losses in the system. In this study, reactive power optimization function is taken to minimize the active power losses in the transmission network. This objective function is subjected to the energy system of inequality and equality constraints and reactive power balance. Genetic algorithms are very popular in solving complex optimization problems. Due to their suitability for parallel computing, ease of implementation and flexibility. In this paper, the reactive power optimization is performed on the IEEE-14 and IEEE 30-bus system bus test for this MATLAB program is developed based on the binary type of genetic algorithm.
Abstract
Reactive power optimization plays an important role in the functioning of the power system. Optimal planning of reactive power reduces the losses in the system. In this study, reactive power optimization function is taken to minimize the active power losses in the transmission network. This objective function is subjected to the energy system of inequality and equality constraints and reactive power balance. Genetic algorithms are very popular in solving complex optimization problems. Due to their suitability for parallel computing, ease of implementation and flexibility. In this paper, the reactive power optimization is performed on the IEEE-14 and IEEE 30-bus system bus test for this MATLAB program is developed based on the binary type of genetic algorithm.