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Improved predictive direct power control of shunt active power filter using GWO and ALO – Simulation and experimental study
Ain Shams Engineering Journal ( IF 6.0 ) Pub Date : 2021-05-16 , DOI: 10.1016/j.asej.2021.04.028
Youcef Bekakra , Laid Zellouma , Om Malik

In order to reduce the maximum overshoot and undershoot of the DC-link voltage variation, and minimize power ripples with low current distortion in accord with IEEE Std. 519–2014, an improved predictive direct power control (PDPC) of three-phase (3-phase) shunt active power filter (SAPF), using two metaheuristic methods, namely Grey Wolf Optimizer (GWO) and Ant Lion Optimizer (ALO) algorithms, is presented. Simulation studies using MATLAB/Simulink have been carried out to verify the efficacy of the two proposed approaches, PDPC-GWO and PDPC-ALO. In addition, the overall system is validated experimentally in real time using dSPACE 1104 card. Performance of both PDPC-GWO and PDPC-ALO is compared with the conventional method to show their efficacy. The results show that PDPC-ALO is more efficient than both PDPC-GWO and the conventional method.



中文翻译:

使用 GWO 和 ALO 改进并联有源电力滤波器的预测性直接功率控制——仿真和实验研究

为了减少直流母线电压变化的最大过冲和下冲,并根据 IEEE Std. 519–2014,三相(3相)并联有源滤波器(SAPF)的改进预测直接功率控制(PDPC),使用两种元启发式方法,即灰狼优化器(GWO)和蚂蚁狮子优化器(ALO)算法, 被表达。已经使用 MATLAB/Simulink 进行了仿真研究,以验证两种提议的方法 PDPC-GWO 和 PDPC-ALO 的有效性。此外,整个系统使用 dSPACE 1104 卡进行实时实验验证。将 PDPC-GWO 和 PDPC-ALO 的性能与传统方法进行比较以显示其功效。结果表明,PDPC-ALO 比 PDPC-GWO 和传统方法更有效。

更新日期:2021-05-16
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