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    Finding the stability boundary values in electrical power systems by using the particle swarm optimization algorithm
    (2011) Kandara, Osman; Öztürk, A.; Tosun, S.; Yalçın, M.A.
    The critical values of a power system are the limit values of its highest active power, voltage amplitude, and the angles of the busses for its voltage stability. In this research, the particle swarm optimization (PSO) algorithm was examined to determine the critical values in electrical power systems. We first determined the critical values using the Jacabian matrix obtained with the load flowing analysis, where the determinant was zero, after which the same critical values were computed using the PSO method and then the results were evaluated. We observed that the critical values can be determined more easily and were reliable with the PSO. © 2011 Academic Journals.
  • Küçük Resim Yok
    Öğe
    Genetic algorithms to determine the critical values of a power energy system for different operating conditions
    (Sila Science, 2012) Kandara, Osman; Öztürk, Ali
    Critical values of a power system are the values of load bus active power, load bus voltage amplitude, and load bus angle when the load bus has the highest active power value. These values depend on various factors such as the length, voltage, the number, and the serial and shunt compensation rates of the line. In this study, we take the IEEE's 6-bus power system as our base system. We first used the Newton Raphson (NR) method to determine the critical values under various operating conditions. Then, we used genetic algorithms, which is an artificial intelligence method commonly used in optimization, to determine the critical values under the same operating conditions. At the end, we compared the results. The results show that overall the critical values determined using GA is as good as with or better than those obtained using the traditional NR method.