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首页> 外文期刊>Journal of King Saud University-Engineering Sciences >Design approach and performance analysis of trap filter for three-phase PV grid integration systems using evolutionary search algorithms
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Design approach and performance analysis of trap filter for three-phase PV grid integration systems using evolutionary search algorithms

机译：使用进化搜索算法设计三相PV网格集成系统陷阱滤波器的设计方法及性能分析

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The main objective of this article is to provide an efficient design approach of passive grid filters based on evolutionary search algorithms. The case study is conducted on a passive trap filter (one of modern high order passive filters that can provide better performance compared with first order scheme) to be incorporated with a three-phase grid-tied inverter fed from PV array and a battery bank, forming a typical PV grid integration system. The filter design approach is mainly based on particle swarm optimization technique (PSO) as one of the efficient evolutionary search algorithms meanwhile Genetic Algorithm (GA) has been utilized as well for comparison purposes. The developed PSO algorithm searches for the optimum numerical values of filter passive components that can optimize a customized objective function of multiple terms. Unlike single-term objective function, the adopted approach has the advantage of involving multiple items in the customized objective function, such as harmonic attenuation factor and the numerical values of passive filter elements to be minimized. Moreover, the evolutionary search-based design approach is characterized by offering several groups of solutions for the same optimization problem. Thus, the obtained solution is not unique. Consequently, the choice between those solutions depends on the system designers who can select the most convenient solution among several alternatives based on component availability in market, the overall cost of the filter and the desired upper limit of THD of grid currents. The obtained results of this study demonstrate also the capability of evolutionary search approach to get optimum values of filter components that achieve good harmonic attenuation and satisfy the related grid codes such as the IEEE standard 519. Compared with traditional filter design method, the obtained results indicate that the PSO technique achieves lower numerical values of filter parameters in the most of parameters, resulting in an overall reduction in the size and cost of the passive grid filter. In addition, the employed GA succeeded to provide satisfactory numerical values of trap filter as well. However, the PSO technique is better than GA in several terms such as lower final value of objective function and lower numerical values of filter elements and convergence to the optimal solution(s) irrespective the initial guess values. Matlab? has been employed as a simulation platform for PSO and GA algorithms. While the overall grid integration system has been modelled and studied using professional version of PSIM software?.
机译：本文的主要目的是基于进化搜索算法提供无源网格滤波器的有效设计方法。案例研究是在无源陷阱滤波器上进行的（现代高阶无源滤光器之一，可以提供与第一订单方案相比的更好的性能），以与从PV阵列和电池组馈送的三相网格连接逆变器结合，形成典型的PV网格集成系统。过滤器设计方法主要基于粒子群优化技术（PSO）作为一种有效的进化搜索算法之一，同时已经利用了遗传算法（GA）以进行比较目的。开发的PSO算法搜索过滤器无源组件的最佳数值，可以优化多个术语的定制目标函数。与单学期的目标函数不同，采用的方法具有涉及定制的目标函数中的多个项目的优点，例如谐波衰减因子和被动滤波器元件的数值最小化。此外，基于进化搜索的设计方法的特点是为同一优化问题提供几组解决方案。因此，所获得的溶液不是唯一的。因此，这些解决方案之间的选择取决于系统设计人员，他们可以根据市场中的组件可用性，过滤器的总成本以及电网电流THD的所需上限之间选择最方便的解决方案。本研究的获得结果还示出了进化搜索方法的能力，以获得实现良好谐波衰减的滤波器组件的最佳值，并满足相关网格代码，例如IEEE标准519.与传统的过滤器设计方法相比，所获得的结果表明PSO技术在大多数参数中实现了滤波器参数的数值降低，导致无源网格滤波器的大小和成本的总体降低。此外，所采用的GA也成功地提供了陷阱过滤器的令人满意的数值。然而，PSO技术在几个术语中优于GA，例如目标函数的较低最终值，并且滤波器元件的数值和收敛到最佳解决方案的收敛而无论初始猜测值如何。 matlab？已被用作PSO和GA算法的仿真平台。虽然整个网格集成系统已经使用PSIM软件的专业版本进行了建模和研究？

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