PSO and CSA to estimate of parameter in power line

Short circuits, voltage drop, harmonic distortion and power loss which is factors affect to power quality of power line as negative. Power line parameters affect to values of these factors. Therefore, power line parameters affect the quality of the electrical energy of transmission and distribution lines. Before new load is included to power line, power line parameters must be determined and so adversely effect of these factors can be prevented. In this study, parameters of power line, which will be added new load, were estimated by using clonal selection algorithm (CSA) and particle swarm optimization (PSO). The results of these two methods were compared with real parameter value of power line and accuracy rating of these methods was determined separately. Primarily, harmonic measurement was made from load connection point of power line and was determined parallel resonance impedance to determine power line parameter from the connection point of new load. The obtained parallel resonance impedance from this measurement result was evaluated with CSA and PSO and so power line parameters were tried to estimate. The end of this study, accuracy rate of CSA and accuracy rate of PSO were compared and the algorithm which had the best results was selected.