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混合SQP的基于完全学习的粒子群优化算法在电力系统中经济分配问题的应用 被引量:2

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摘要 电力系统经济负荷分配(ELD)问题是电力系统运行中一个重要的优化问题.此前,多种经典数学逼近方法和启发式搜索算法被用于对该问题进行了求解.但是,这些方法仍然存在两个很重要而未引起足够重视的问题:1)算法的稳定性得不到有效保证;2)算法在大规模ELD问题上的性能仍然不能令人满意.CLPSO是一种新的高效全局优化算法.针对其存在的多样性保持能力强但收敛性不足的问题,文中引入序列二次规划SQP,提出了一种新的混合SQP的CLPSO算法SQP-CLPSO.用其求解多个典型ELD问题,并与多种知名算法进行了对比.实验结果表明,SQP-CLPSO具有优秀的收敛性、多样性和可拓展性,是求解复杂ELD问题的有效算法.
出处 《中国科学:信息科学》 CSCD 2010年第3期403-411,共9页 Scientia Sinica(Informationis)
基金 国家自然科学基金(批准号:60401015 U0835002) IEEE Walter Kaplus夏季学生研究基金 中国科学院研究生科技创新基金 中国科学技术大学研究生创新基金资助项目
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参考文献16

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同被引文献21

  • 1蒙文川,邱家驹,卞晓猛.电力系统经济负荷分配的人工免疫混沌优化算法[J].电网技术,2006,30(23):41-44. 被引量:22
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