Optimal power flow with sinus chaotic map and escape velocity based gravitational search algorithm

In this study, it is aimed to improve the performance of gravity search algorithm by combining sinus chaotic mapping and escape velocity based operators. The new algorithm developed for this purpose has been tested 30 times in a total of 23 comparison test functions which are single mode, multi mode, multi mode and very low size. Minimum, median and mean values of the results obtained from the test study were taken and these values were compared with particle herd optimization, genetic algorithm, gravity search algorithm, survival fast gravity search algorithm and chaotic jerky gravity search algorithms and the best result was improved gravity search algorithm. In addition, the developed algorithm has been used in the solution of the optimal power flow problem for the general cost calculation, power loss calculation, valve point effective cost calculation, combined general cost and emission cost calculation in the IEEE-30 bus test system. The results were compared with moth herd algorithm, prairie worm optimization algorithm and gravity search algorithm. When the results are analyzed, it is seen that the developed algorithm gives effective results.