山东大学学报 (工学版) ›› 2021, Vol. 51 ›› Issue (1): 11-23.doi: 10.6040/j.issn.1672-3961.0.2020.050
• • 上一篇
武慧虹1,钱淑渠1*,刘衍民2,徐国峰3,郭本华1
WU Huihong1, QIAN Shuqu1*, LIU Yanmin2, XU Guofeng3, GUO Benhua1
摘要: 为有效解决复杂多目标动态环境经济调度问题,提出一种基于精英克隆局部搜索的多目标动态环境经济调度差分进化算法。以传统的差分进化(differential evolution, DE)算法为框架,为了提高DE算法的开采和探索能力,增设精英群的克隆和突变机制,采用动态选择方式确定精英群,有效增强算法的全局搜索能力。数值试验以IEEE-30的10机、15机系统为测试实例,并将提出的算法与三种代表性算法比较。结果表明,新算法所获的Pareto前沿具有较好的收敛性和延展性,可为电力系统调度人员提供更灵活的决策方案。
中图分类号:
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