ABSTRACT In this study, an improved invasive weed optimisation (CMIWO) algorithm is investigated to solve the dynamic economic dispatch (DED) problem with valve-point effects. In the proposed algorithm, a hybrid operator including selective crossover, random mutation and row crossover is proposed to improve the exploration and exploitation abilities. Moreover, a self-adaption repair method is developed and embedded into the proposed algorithm to repair infeasible solutions. To verify the optimisation performance of CMIWO, six well-known DED problems in three different-scale power systems are tested and compared with other algorithms that have been proposed in the literature. The experimental results show that CMIWO can find the more economical dispatch solutions compared to other algorithms, and the self-adaption repair method can successfully convert infeasible solutions into feasible solutions. The convergence ability of CMIWO is also verified after the detailed comparison.

中文翻译：

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一种求解具有阀点效应的动态经济调度问题的改进侵入式杂草优化算法

摘要 在这项研究中，研究了一种改进的侵入式杂草优化 (CMIWO) 算法来解决具有阀点效应的动态经济调度 (DED) 问题。在所提出的算法中，提出了包括选择性交叉、随机变异和行交叉的混合算子，以提高探索和开发能力。此外，开发了一种自适应修复方法并将其嵌入到所提出的算法中以修复不可行的解决方案。为了验证 CMIWO 的优化性能，测试了三个不同规模的电力系统中的六个众所周知的 DED 问题，并与文献中提出的其他算法进行了比较。实验结果表明，与其他算法相比，CMIWO可以找到更经济的调度解决方案，自适应修复方法可以成功地将不可行解转化为可行解。经过详细对比，CMIWO的收敛能力也得到了验证。