Optimal reactive power dispatch using an improved slime mould algorithm

Abstract

The optimal reactive power dispatch (ORPD) problem plays an important role in the reliability and economy of a power system. At present, the methods for solving the ORPD problem are insufficient in terms of both accuracy and computation time. The inspiration for the slime mould algorithm (SMA) comes from the oscillation mode of slime mould foraging in the real world. However, in some cases, SMA skips over the real solution and becomes trapped at sub-optimal solution, which leads to premature convergence and negatively affects the search for the global optima. Therefore, to address these issues, in this paper, we propose an improved SMA (ISMA) to solve the ORPD problem. In the performance evaluation, 23 IEEE CEC 2017 benchmark functions were used to compare ISMA with standard SMA and several state-of-the-art methods. The experimental results show that ISMA performs well with respect to the mean (standard deviation), Friedman test, Wilcoxon test, and convergence curves. Moreover, to perform the ORPD task, this method was implemented on the IEEE 57-bus, IEEE 118-bus, and IEEE 300-bus test systems, and the results were compared with those of other recent optimization techniques. The advantages of this algorithm were demonstrated, and its effectiveness and robustness for solving ORPD problem of power system were also demonstrated.

Keywords

• Slime mould algorithm
• Improved slime mould algorithm
• Reactive power dispatch problem
• Optimization
• Swarm intelligence