Research Information System
4th International Artificial Intelligence and Data Science Congress ICADA 2024 , İzmir, Turkey, 14 - 15 March 2024, pp.1-7, (Full Text)
One of the key factors that determine the sustainability and efficiency of the electrical power system is the optimum control of the variables of that system to reach the Optimal Power Flow (OPF), which takes into account security restrictions and both upper and lower limits of all components of the system, including power and voltage of generators, transformers and its tap changers, the capacity of transmission lines, shunt capacitors, and buses voltage. In this work, the genetic algorithm—one artificial intelligence technique—was employed for controlling the genetic algorithm's parameters to determine the optimum flow of power for the IEEE-30 bus standard test system, by controlling genetic algorithm (GA) parameters (mutation, and probability simple crossover), both of them affect the efficiency of the solution to this algorithm by widening the search space of those parameters rather than fixed values that do not reach the optimal value. Three different iterations (100, 500, and 1000) of the search space were tested to confirm the validity of the approach. One of the goals of the suggested strategy was to arrive at the lowest operating fuel cost possible. It is evident from the comparison of this outcome with the findings documented in the literature that the suggested method was successful and promising in addressing such problems.