基于改进差分进化-生物地理学优化算法的最优潮流问题

生物地理学优化算法(biogeography-based optimization,BBO)是一种新提出的全局智能优化算法,但是其应用于最优潮流计算时,具有早熟和收敛不稳定的问题。将BBO与差分进化(differential evolution,DE)算法相结合,并对差分进化部分的改进策略稍做修改,形成改进DE-BBO算法。应用所提方法对IEEE 30节点系统进行了有功优化的计算,并和GA、PSO、BBO和DE 4种方法进行了分析和比较,结果表明所提方法具有良好的收敛稳定性,可以有效缩短迭代时间。

Optimal Power Flow on Basis of Combining Improved Differential Evolution Algorithm With Biogeography-Based Optimization Algorithm

Biogeography-based optimization(BBO) is a newly proposed global intelligent optimization algorithm,however there are defects of early-maturing and instable convergence when it is used to the calculation of optimal power flow.Combining BBO with differential evolution(DE) and making small modifications for the mutation strategy of DE,an improved DE-BBO algorithm is formed.Applying the improved DE-BBO algorithm,the active power optimization of IEEE 30-bus system is performed,and the obtained results are compared with the results by GA algorithm,PSO algorithm,only using BBO algorithm and only using DE algorithm respectively,comparison result shows that the proposed improved DE-BBO algorithm possesses good and stable convergence and the time for iteration can be reduced effectively.