基于混合混沌算法的电力系统无功优化

Power System Reactive Optimization Based on Hybrid Chaos Algorithm

提出了一种基于混沌算法的主动禁忌混合混沌算法(RTSCOA),该算法结合了混沌算法的全局遍历性和禁忌算法的“记忆”功能,利用主动禁忌法的反馈机制控制管理禁忌表长度,能够有效地跳出局部极小点。分别对IEEE 6和IEEE 30节点进行仿真,并与标准遗传算法/改进遗传算法(SGA/AGA)进行比较,以证明该算法在电力系统无功控制中应用的有效性。经比较,该方法较其他算法在计算速度、寻优能力上有一定的提高。

The paper puts forward an active taboo hybrid chaos algorithm based on chaos algorithm. The algorithm combined the ergodic property of the chaos algorithm and the memory function of the taboo algorithm. It can effectively trip out of the local minimum point using the feedback mechanism of the active taboo algorithm to control and manage the size of the taboo table. Simulations were done to IEEE 6 bus and IEEE 30 bus system respectively and comparisons between this method and SGA/AGA were made, in order to show the effectiveness of the method in reactive power control of power systems. Cooperation shows that the calculation speed and capability of seeking global optimization of this method are better than those of other algorithms.