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Multi-objective design approach of passive filters for single-phase distributed energy grid integration systems using particle swarm optimization
Energy Reports ( IF 5.2 ) Pub Date : 2020-11-01 , DOI: 10.1016/j.egyr.2019.12.015 Mohamed Azab
Energy Reports ( IF 5.2 ) Pub Date : 2020-11-01 , DOI: 10.1016/j.egyr.2019.12.015 Mohamed Azab
Abstract This article presents a non-conventional design approach of high order passive filters incorporated with distributed energy grid integration systems based on particle swarm optimization (PSO) as one of multi-objective evolutionary search algorithms. Two topologies of passive grid filters (third order passive damped LCL-filter and trap filter) are chosen as case studies. The presented grid filter design is based searching the optimum values of filter passive elements that can optimize an objective function composed of several terms such as harmonic attenuation factor and size (value) of passive elements (inductors and capacitors). The employed multi-objective design approach has three main advantages: (1) The PSO algorithm offers several groups of solutions to the same optimization problem. Accordingly, the most convenient solution can be chosen based on several factors such as cost of realization, availability in the market and the corresponding THD of grid current. (2) Multi-objective design approach is flexible enough to include other factors in the customized objective function to achieve different design criteria in accordance with new (or updated) versions of grid codes. (3) The PSO algorithm converges to the optimum solution(s) regardless the initial search values (initial guess). Consequently, the algorithm does not need any prior knowledge about filter numerical values The PSO algorithm has been developed in Matlab®, while the overall hardware grid-integration system has been modeled and studied using PSIM® software package. The obtained results demonstrate the effectiveness of the proposed approach to get practical and applicable values of filter components that result in good harmonic attenuation and satisfy the related codes of grid integration such as the IEEE standard 519. The main contribution of this paper is the utilization of evolutionary optimization technique to achieve an optimum design of passive grid filters that can optimize simultaneously several contradictory goals such as achieving the maximum possible harmonic attenuation at the lowest possible filter size. Compared with conventional design approach, the PSO-based filter design approach results in lower numerical values of filter components, which leads to considerable reduction in the size and cost of the passive grid filter. Moreover, grid filter design based on evolutionary search approach permits accommodation of several design criteria in the customized objective function with arbitrary weighting factors upon system design requests and new grid codes constrains.
中文翻译:
基于粒子群优化的单相分布式能源并网系统无源滤波器多目标设计方法
摘要 本文提出了一种基于粒子群优化 (PSO) 作为多目标进化搜索算法的分布式能源网格集成系统的高阶无源滤波器的非常规设计方法。选择两种无源网格滤波器拓扑结构(三阶无源阻尼 LCL 滤波器和陷波滤波器)作为案例研究。所提出的网格滤波器设计基于搜索滤波器无源元件的最佳值,可以优化由若干项组成的目标函数,例如谐波衰减因子和无源元件(电感器和电容器)的尺寸(值)。所采用的多目标设计方法具有三个主要优点: (1) PSO 算法为同一优化问题提供了几组解决方案。因此,可以根据多种因素选择最方便的解决方案,例如实现成本、市场可用性和相应的电网电流 THD。(2) 多目标设计方法足够灵活,可以在定制的目标函数中包含其他因素,以根据新的(或更新的)电网规范实现不同的设计标准。(3) 无论初始搜索值(初始猜测)如何,PSO 算法都会收敛到最优解。因此,该算法不需要任何关于滤波器数值的先验知识。PSO 算法是在 Matlab® 中开发的,而整个硬件网格集成系统已使用 PSIM® 软件包进行建模和研究。获得的结果证明了所提出的方法在获得滤波器组件的实用和适用值方面的有效性,这些滤波器组件导致良好的谐波衰减并满足电网集成的相关规范,如 IEEE 标准 519。本文的主要贡献是利用进化优化技术,以实现无源电网滤波器的优化设计,可以同时优化几个相互矛盾的目标,例如以尽可能小的滤波器尺寸实现最大可能的谐波衰减。与传统的设计方法相比,基于 PSO 的滤波器设计方法导致滤波器元件的数值更低,这导致无源网格滤波器的尺寸和成本显着降低。而且,
更新日期:2020-11-01
中文翻译:
基于粒子群优化的单相分布式能源并网系统无源滤波器多目标设计方法
摘要 本文提出了一种基于粒子群优化 (PSO) 作为多目标进化搜索算法的分布式能源网格集成系统的高阶无源滤波器的非常规设计方法。选择两种无源网格滤波器拓扑结构(三阶无源阻尼 LCL 滤波器和陷波滤波器)作为案例研究。所提出的网格滤波器设计基于搜索滤波器无源元件的最佳值,可以优化由若干项组成的目标函数,例如谐波衰减因子和无源元件(电感器和电容器)的尺寸(值)。所采用的多目标设计方法具有三个主要优点: (1) PSO 算法为同一优化问题提供了几组解决方案。因此,可以根据多种因素选择最方便的解决方案,例如实现成本、市场可用性和相应的电网电流 THD。(2) 多目标设计方法足够灵活,可以在定制的目标函数中包含其他因素,以根据新的(或更新的)电网规范实现不同的设计标准。(3) 无论初始搜索值(初始猜测)如何,PSO 算法都会收敛到最优解。因此,该算法不需要任何关于滤波器数值的先验知识。PSO 算法是在 Matlab® 中开发的,而整个硬件网格集成系统已使用 PSIM® 软件包进行建模和研究。获得的结果证明了所提出的方法在获得滤波器组件的实用和适用值方面的有效性,这些滤波器组件导致良好的谐波衰减并满足电网集成的相关规范,如 IEEE 标准 519。本文的主要贡献是利用进化优化技术,以实现无源电网滤波器的优化设计,可以同时优化几个相互矛盾的目标,例如以尽可能小的滤波器尺寸实现最大可能的谐波衰减。与传统的设计方法相比,基于 PSO 的滤波器设计方法导致滤波器元件的数值更低,这导致无源网格滤波器的尺寸和成本显着降低。而且,