Abstract-This paper proposes an efficient differential evolution (DE) algorithm for the solution of the optimal reactive power dispatch (ORPD) problem. The main objective of ORPD is to minimize the total active power loss with optimal setting of control variables. The continuous control variables are generator bus voltage magnitudes. The discrete control variables are transformer tap settings and reactive power of shunt compensators. In DE algorithm the other form of differential mutation operator is used. It consists to add the global best individual in the differential mutation operator to improve the solution. The DE algorithm solution has been tested on the standard IEEE 30-Bus test system to minimize the total active power loss without and with voltage profile improvement. The results have been compared to the other heuristic methods such as standard genetic algorithm and particle swarm optimization method. Finally, simulation results show that this method converges to better solutions.
In this paper, the sine and cosine algorithm is enhanced (ESCA) by selecting the best elements of the group in the next iterations to reduce active power loss. The sine and cosine algorithm (SCA) converges to an optimal solution through the sinus and cosine-based mathematical relations and the destination or the best global element in each iteration. Also, it uses the current elements for generating new elements without keeping the elements that have a better solution in the next generations. In ESCA this problem is avoided by applying the selection operator for keeping the best elements to the next generation. This method improves the optimal solution and is obtained in most implementations of the algorithm, which reduces the disturbances in obtaining the optimal solution. Also, one of the parameters of the standard method is fixed to the normal one value for the performance improvement of the algorithm. This method has been applied to a typical power network such as IEEE 30-bus and IEEE 118-bus in order to reduce the active power loss, reduce the power loss with the voltage deviation and with the stability of the voltage. Finally, this method proved effective than the standard method and with the previously applied metaheuristic methods.
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