摘要
在鲸鱼优化算法(WOA)对求解电网无功优化问题中容易陷入局部最优、收敛速度慢、求解精度低等缺点时,本文将一种引入冯诺依曼拓扑结构的改进鲸鱼优化算法(AWOA)应用到ORPD问题中,在鲸鱼对猎物进行狩猎行为时,能够增加猎物的多样性,提高了算法的全局搜索能力。以系统有功网损和电压偏差为双目标函数,对IEEE 30节点系统进行仿真,并利用方差分析法(ANOVA)将所得结果与基本鲸鱼优化算法(WOA)、粒子群优化算法(PSO)进行比较,研究表明AWOA算法在搜索能力、迭代次数、收敛性上的潜力,并证明了在解决ORPD问题上的有效性、高效性及鲁棒性,同时也为解决非线性约束问题提供了新途径。
When the whale optimization algorithm(WOA)is easy to fall into local optimum,slow convergenceand low accuracy in solving the reactive power optimization problem of the grid,in this paper,a kind of von neumann neighborhood topology,which is called the whale optimization algorithm(AWOA),is applied to the ORPD problem to increase diversity of prey as the whales hunt their prey,which improves the global search capability of the algorithm. The active network loss and voltage deviation are taken as dual objective functions,the IEEE 30 node system is simulated and the result obtained by the ANOVA is compared with WOA and PSO. It is shown by the study that the potential of the AWOA algorithm search ability,iteration number and convergence are proved and the effectiveness,efficiency and robustness in solving the ORPD problem are also proved and,atthe same time,a new way to solve the nonlinear constraint problem is provided.
引文
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