基于混合布谷鸟搜索算法的多区域经济调度

K. P. Nguyen, N. D. Dinh, G. Fujita
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引用次数: 16

摘要

提出了一种求解多区域经济调度问题的混合布谷鸟搜索算法。混合布谷鸟搜索算法是将布谷鸟搜索算法与基于教学的优化相结合,增加TLBO的学习者阶段,提高布谷鸟蛋的性能。该方法已应用于3个多区域经济调度问题的实例。该问题的目标是在满足发电机运行约束和并线约束的情况下使发电总成本最小。将该方法与传统的布谷鸟搜索算法和基于教学的优化算法进行了比较,验证了其有效性。数值计算结果表明,该方法的解优于两种性能优良的比较方法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Multi-area economic dispatch using Hybrid Cuckoo search algorithm
This paper proposes a Hybrid Cuckoo search algorithm to solve Multi-area economic dispatch problem (MAED). Hybrid Cuckoo search algorithm is a combination of the Cuckoo search algorithm and Teaching-learning-based optimization, where the learner phase of TLBO is added to improve performance of Cuckoo eggs. The proposed method has been applied for solving three tested cases of Multi-area economic dispatch problem. The objective of this problem is to minimize a total generation cost while satisfying generator operational constraints and tie- line constraints. The proposed method has been compared with the conventional Cuckoo search algorithm and Teaching-learning-based optimization to obtain its effectiveness. Numerical results show that the proposed method gives better solutions than two compared methods with high performance.
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