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Security Constrained Economic Dispatch using a hybrid Fuzzy Genetic Algorithm approach

机译:混合模糊遗传算法的安全约束经济调度

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Premature convergence, which occurs due to loss of diversity, is one of the major issues in Genetic Algorithm. The adaptive probabilities of cross-over and mutation can be used to realize the twin goals of maintaining diversity in the population and sustaining the convergence capacity of the Genetic Algorithm. In this work, the Genetic Algorithm operators of cross-over and mutation are varied adaptively using the fuzzy logic approach and it has been used to reach an optimal solution for the Security Constrained Economic Dispatch problem. A comparative study has been made between Simple Genetic Algorithm and Fuzzy Genetic Algorithm on IEEE 6- bus 3-unit and IEEE 30-bus 6-unit systems. Results of comparison with other techniques are presented, showing the better computational efficiency and convergence property of the proposed approach.
机译:由于多样性的丧失而发生的过早收敛是遗传算法中的主要问题之一。交叉和变异的自适应概率可用于实现维持种群多样性和维持遗传算法收敛能力的双重目标。在这项工作中,使用模糊逻辑方法自适应地改变交叉和变异的遗传算法算子,并已将其用于解决安全约束的经济调度问题的最佳解决方案。在IEEE 6总线3单元系统和IEEE 30总线6单元系统上,对简单遗传算法和模糊遗传算法进行了比较研究。提出了与其他技术的比较结果,表明该方法具有更好的计算效率和收敛性。

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