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Wyświetlanie 1-2 z 2
Tytuł:
Performance Evaluation of BB-QZSI-Based DSTATCOM Under Dynamic Load Condition
Autorzy:
Mangaraj, Mrutyunjaya
Sabat, Jogeswara
Barisal, Ajit Kumar
Patra, Anil Kumar
Chahattaray, Ashok Kumar
Powiązania:
https://bibliotekanauki.pl/articles/2175927.pdf
Data publikacji:
2022
Wydawca:
Politechnika Wrocławska. Oficyna Wydawnicza Politechniki Wrocławskiej
Tematy:
BB-QZSI
DSTATCOM
icos control algorithm
PUN
power utility network
Opis:
This paper presents the shunt compensation performance of quasi-Z-source inverter (QZSI) and back to back connected QZSIs (BB-QZSI) to address the power quality (PQ) issues in the three-phase three-wire power utility network (PUN). Generally, these PQ issues are poor voltage regulation, low power factor (PF), source current distortion, unbalanced voltage, etc. The proposed BB-QZSI-based distribution static compensator (DSTATCOM) consists of two QZSIs with a common dc-link capacitor. Because the QZSI could achieve buck/boost conversion as well as DC to AC inversion in a single-stage and the back to back configuration decreases the system down time cost (if a fault occurs in one QZSI the other can continue the shunt compensation). Particularly, icosφ control algorithmcontrol algorithm is implemented to generate proper switching pulses for the switches of DSTATCOM. The effectiveness of the BB-QZSI is verified through simulation studies over QZSI using MATLAB/Simulink software satisfying the recommended grid code.
Źródło:
Power Electronics and Drives; 2022, 7, 42; 43--55
2451-0262
2543-4292
Pojawia się w:
Power Electronics and Drives
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
VSC-Based DSTATCOM for PQ Improvement: A Deep-Learning Approach
Autorzy:
Mangaraj, Mrutyunjaya
Sabat, Jogeswara
Barisal, Ajit Kumar
Ramaiah, K. Subba
Rao, Gudivada Eswara
Powiązania:
https://bibliotekanauki.pl/articles/2175932.pdf
Data publikacji:
2022
Wydawca:
Politechnika Wrocławska. Oficyna Wydawnicza Politechniki Wrocławskiej
Tematy:
DL approach
deep learning approach
DSTATCOM
distributed static compensator
ALMS
PQ
power quality
Opis:
With the rapid advancement of the technology, deep learning supported voltage source converter (VSC)-based distributed static compensator (DSTATCOM) for power quality (PQ) improvement has attracted significant interest due to its high accuracy. In this paper, six subnets are structured for the proposed deep learning approach (DL-Approach) algorithm by using its own mathematical equations. Three subnets for active and the other three for reactive weight components are used to extract the fundamental component of the load current. These updated weights are utilised for the generation of the reference source currents for VSC. Hysteresis current controllers (HCCs) are employed in each phase in which generated switching signal patterns need to be carried out from both predicted reference source current and actual source current. As a result, the proposed technique achieves better dynamic performance, less computation burden and better estimation speed. Consequently, the results were obtained for different loading conditions using MATLAB/Simulink software. Finally, the feasibility was effective as per the benchmark of IEEE guidelines in response to harmonics curtailment, power factor (p.f) improvement, load balancing and voltage regulation.
Źródło:
Power Electronics and Drives; 2022, 7, 42; 174--186
2451-0262
2543-4292
Pojawia się w:
Power Electronics and Drives
Dostawca treści:
Biblioteka Nauki
Artykuł
    Wyświetlanie 1-2 z 2

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