scholarly journals A Hierarchical Teaching-Learning-Based Optimization Algorithm for Optimal Design of Hybrid Active Power Filter

IEEE Access ◽  
2020 ◽  
Vol 8 ◽  
pp. 143530-143544
Author(s):  
Zhiling Cui ◽  
Chunquan Li ◽  
Wanxuan Dai ◽  
Leyingyue Zhang ◽  
Yufan Wu
PLoS ONE ◽  
2021 ◽  
Vol 16 (7) ◽  
pp. e0253275
Author(s):  
Tung Khac Truong ◽  
Chau Minh Thuyen

This paper presents a new flowchart for parameters calculation of Hybrid Active Power Filter with Injection Circuit (IHAPF). The first is the necessity to use the IHAPF model and the parameters of the IHAPF needed to search have been shown. Next, the constraints of the parameters to be searched and the objective function to be reached are given. Since then a flowchart is designed to look for parameters of IHAPF using the Jaya optimization algorithm. The Jaya algorithm has the advantage of simplicity, few parameters, and good performance. Therefore it reduces search time. Compared to the flowchart using the firefly algorithm, particle swarm optimization algorithm, and simulated annealing algorithm, the simulation results performed on an IHAPF 10kV-50Hz model have proven that: the proposed flowchart gives better results in minimizing the compensation errors, minimum phase shift angle between supply current, and source voltage, minimum total harmonic distortion of supply current.


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