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Optimal power flow study using conventional and neural networks methods

The solution of the power flow problem provides basic and useful information about the electrical performance of the power system. The planner of this system can easily evaluate the impact of different configurations of transmission and generation for any desired level of load. The power flow operator can anticipate the effect of changing the system before such action takes place. This paper presents an optimal power flow study using conventional and artificial intelligence methods; the IEEE 30-bus test network will be the electrical system of our study. In the first approach, a conventional method (developed by power world simulator software) is studied. This software is based on Newton-Raphson technique which is the most relevant power flow calculating technique because of its rapid convergence. The second approach belongs to the field of artificial intelligence, which is the neural networks method. A comparison between the results obtained using the two mentioned approaches is performed at the end of this work.