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Genetic algorithm based optimal operation for photovoltaic systems under different fault criteria

机译:不同故障准则下基于遗传算法的光伏系统最优运行

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The need to optimize the operation of PV systems is justified by the fact that PV systems are expensive to build, fuel- free source, and it is therefore natural that user of such systems would want them to perform at their most optimal point. Under the faulted condition, the power curve has a multi-peak nature; conventional optimization technique can easily fall down in local optimal and initial point problems. Genetic algorithm as a global optimization technique is adopted to optimize photovoltaic power system under different faulted conditions. The proposed PV system and GA scheme is tested for three different sizes (three module panel five module and seven module panel) of PV system under different faulted conditions and the simulation results sbown in the paper. It is shown from the results that the genetic algorithm captured the exact optimization point accurately for the tested cases.
机译:事实证明,优化光伏系统的运行是有理由的,因为光伏系统的建造成本高,无燃料,因此,此类系统的用户自然希望它们在最佳状态下运行。在故障条件下,功率曲线具有多峰性质;传统的优化技术很容易陷入局部最优和初始点问题。采用遗传算法作为全局优化技术,对不同故障条件下的光伏发电系统进行了优化。在不同故障条件下,对三种不同尺寸(三个模块面板,五个模块面板和七个模块面板)的光伏系统和遗传算法进行了测试,仿真结果不理想。从结果可以看出,遗传算法为测试案例准确地捕获了精确的优化点。

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