Control of distribution static synchronous compensator using intelligent methods to improve power quality

ÖZDOĞAN N., BAHÇECİ S.

Computers and Electrical Engineering, cilt.126, 2025 (SCI-Expanded, Scopus) identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 126
  • Basım Tarihi: 2025
  • Doi Numarası: 10.1016/j.compeleceng.2025.110552
  • Dergi Adı: Computers and Electrical Engineering
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus, Academic Search Premier, Aerospace Database, Applied Science & Technology Source, Communication Abstracts, Compendex, Computer & Applied Sciences, INSPEC, Metadex, zbMATH, Civil Engineering Abstracts
  • Anahtar Kelimeler: Distribution static synchronous compensator, Harmonic mitigation, Intelligent controller, Power quality
  • Erciyes Üniversitesi Adresli: Evet

Özet

The use of renewable energy sources in electrical energy production is increasing day by day. Ensuring system stability by reducing grid power quality problems is very important for the efficiency of electrical energy. For this purpose, new intelligent control systems were designed with the LCL-filtered Distribution Static Synchronous Compensator (DSTATCOM) model for the grid to which the Doubly Fed Induction Generator (DFIG) wind turbine system modeled in MATLAB/Simulink is connected in the study. With the control models based on Artificial Neural Network (ANN) and Long Short Term Memory (LSTM) proposed for DSTATCOM control, the usability of intelligent methods in control systems and their contributions to power quality improvement were tested. The performances of the modeled control systems were compared with the conventional Proportional Integral (PI) control system by examining in terms of the current Total Harmonic Distortion (THD) values and sudden voltage change contributions. Harmonic analyses were carried out for different load connections and filter parameter changes. According to the results, it was observed that the proposed control models contributed to the reduction of power quality problems and the most successful model was the LSTM-based control system.