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Towards the improvement of multi-objective evolutionary algorithms for service restoration

机译:面向服务恢复的多目标进化算法的改进

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Distribution systems (DS) service restoration is a multi-objective, multi-constraint, combinatorial and non-linear optimization problem that must be quickly solved. Four multi-objective evolutionary algorithms (MOEAs) are proposed, which combine prominent aspects of highlighted MOEAs in the literature, for dealing with SR problem. Their main differentials are the providing of improved Pareto fronts and prioritization of switching operation in remotely controlled switches, which is widely used in smart grids. Proposed MOEAs were compared with a MOEA from literature by several tests in a large-scale DS. The MOEAs' performance was measured by four metrics for evaluation of Pareto fronts and Welch's t-hypothesis test was used for statistical comparison of such performance. Test results indicate all proposed MOEAs performed better than the MOEA from literature.
机译:配电系统(DS)服务恢复是必须快速解决的多目标,多约束,组合和非线性优化问题。提出了四种多目标进化算法(MOEA),它们结合了文献中突出的MOEA的突出方面,用于处理SR问题。它们的主要区别是提供了改进的Pareto前沿,并优先控制了在智能电网中广泛使用的远程控制开关中的开关操作。通过大规模DS中的多项测试,将拟议的MOEA与文献中的MOEA进行了比较。 MOEA的绩效通过四个衡量帕累托前沿的指标来衡量,而Welch的t假设检验用于对此类绩效进行统计比较。测试结果表明,所有提出的MOEA均比文献中的MOEA表现更好。

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