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Pareto Optimal Reconfiguration of Power Distribution Systems Using a Genetic Algorithm Based on NSGA-II

机译:基于遗传算法的遗传算法对配电系统的帕累托最优重构

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Reconfiguration, by exchanging the functional links between the elements of the system, represents one of the most important measures which can improve the operational performance of a distribution system. The authors propose an original method, aiming at achieving such optimization through the reconfiguration of distribution systems taking into account various criteria in a flexible and robust approach. The novelty of the method consists in: the criteria for optimization are evaluated on active power distribution systems (containing distributed generators connected directly to the main distribution system and microgrids operated in grid-connected mode); the original formulation (Pareto optimality) of the optimization problem and an original genetic algorithm (based on NSGA-II) to solve the problem in a non-prohibitive execution time. The comparative tests performed on test systems have demonstrated the accuracy and promptness of the proposed algorithm.
机译:通过交换系统各组成部分之间的功能链接,重新配置是可以提高配电系统运行性能的最重要措施之一。作者提出了一种原始方法,旨在通过以灵活,强大的方法考虑各种标准的配电系统的重新配置来实现这种优化。该方法的新颖性在于:在有源配电系统(包括直接连接到主配电系统的分布式发电机以及以并网模式运行的微电网)上评估优化标准;优化问题的原始公式(帕累托最优性)和原始遗传算法(基于NSGA-II)在非禁止执行时间内解决问题。在测试系统上进行的比较测试已经证明了所提出算法的准确性和及时性。

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