Power Quality Enhancement in High-Voltage Transmission Systems Using STATCOM by Type 1 and Type 2 Fuzzy Logic Controllers

The continuing growth of load demand leads to increased power system complexity and interconnections. During faults and abnormal operating conditions, conventional power systems change the load flow in transmission lines, which may cause voltage drops or swells, and other power quality issues. Voltage regulation is connected to reactive power compensation in system busbars, and fixed capacitor banks are usually used for this purpose, but they are not flexible and dynamic enough to meet the power quality requirements. With power electronics development, flexible alternative current transmission systems (FACTS) became a popular solution for power quality improvement and power transmission capability increment in power systems, and FACTS can be categorized into series and shunt systems. In this study, STATCOM was used to improve the voltage profile in part of Iraq’s high-voltage transmission system during abnormal operating conditions, such as sudden load addition and removal, which causes voltage dip and voltage swell. Type 1 fuzzy logic controller and type 2 fuzzy logic controller were used as the outer controller in the STATCOM; both controllers were able to regulate the voltage magnitude by reducing the voltage dip from 1.32 to 0.4%, voltage swell from 1.02 to 0.5%, and voltage THD at the connecting point did not exceed 3%, indicating that SATACOM with FLC improves the voltage profile under different operating conditions.

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Publication Details

Journal
International Journal of Computational Intelligence Systems
Published
2024-09-10
DOI
https://doi.org/10.1007/s44196-024-00636-z
Citations
5
Primary Topic
Power Quality and Harmonics
Type
article
Field-Weighted Citation Impact
1.04
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article

Power Quality Enhancement in High-Voltage Transmission Systems Using STATCOM by Type 1 and Type 2 Fuzzy Logic Controllers

Faissl G. Chremk, Hanene Medhaffar
5 citations
International Journal of Computational Intelligence Systems
Power Quality and Harmonics
1.04
article

Power Quality Enhancement in High-Voltage Transmission Systems Using STATCOM by Type 1 and Type 2 Fuzzy Logic Controllers

Faissl G. Chremk, Hanene Medhaffar
article en
5 citations

Abstract

The continuing growth of load demand leads to increased power system complexity and interconnections. During faults and abnormal operating conditions, conventional power systems change the load flow in transmission lines, which may cause voltage drops or swells, and other power quality issues. Voltage regulation is connected to reactive power compensation in system busbars, and fixed capacitor banks are usually used for this purpose, but they are not flexible and dynamic enough to meet the power quality requirements. With power electronics development, flexible alternative current transmission systems (FACTS) became a popular solution for power quality improvement and power transmission capability increment in power systems, and FACTS can be categorized into series and shunt systems. In this study, STATCOM was used to improve the voltage profile in part of Iraq’s high-voltage transmission system during abnormal operating conditions, such as sudden load addition and removal, which causes voltage dip and voltage swell. Type 1 fuzzy logic controller and type 2 fuzzy logic controller were used as the outer controller in the STATCOM; both controllers were able to regulate the voltage magnitude by reducing the voltage dip from 1.32 to 0.4%, voltage swell from 1.02 to 0.5%, and voltage THD at the connecting point did not exceed 3%, indicating that SATACOM with FLC improves the voltage profile under different operating conditions.

International Journal of Computational Intelligence SystemsVol. 17(1)
University of Sfax (TN)
Affordable and clean energy
Openalex Percentile: Top 23%
Power Quality and Harmonics
1.04
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Power Quality Enhancement in High-Voltage Transmission Systems Using STATCOM by Type 1 and Type 2 Fuzzy Logic Controllers — Faissl G. Chremk, Hanene Medhaffar · International Journal of Computational Intelligence Systems (2024) | TGRS Research Map | TGRS