AI-Based Control Strategy For UPQC In Smart Grid Applications

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@article{1717052,
      author = {Dr. V. Dhinesh M. E., PhD, M. Ragavi, K. Rubitha, M. Kalaiselvi, S. Keerthika},
      title = {AI-Based Control Strategy For UPQC In Smart Grid Applications},
      journal = {Iconic Research And Engineering Journals},
      year = {2026},
      volume = {9},
      number = {10},
      pages = {4386-4391},
      issn = {2456-8880},
      url = {https://www.irejournals.com/formatedpaper/1717052.pdf},
      abstract = {This paper presents a simplified control technique for This paper presents an advanced AI-based control strategy for Unified Power Quality Conditioner (UPQC) in smart grid applications using a DC-link capacitor without photovoltaic (PV) integration. The UPQC consists of a series and shunt active filter designed to mitigate power quality issues such as voltage sag, swell, harmonics, and unbalance in modern distribution systems. Unlike conventional control methods such as PI and hysteresis controllers, the proposed system incorporates Artificial Intelligence (AI)-based adaptive control, enabling real-time decision-making and improved dynamic response under varying load conditions. The DC-link capacitor acts as the primary energy storage element, ensuring stable power exchange between series and shunt converters. The AI controller continuously monitors system parameters such as voltage, current, Total Harmonic Distortion (THD), and load variations, and generates optimized switching signals for Voltage Source Inverters (VSI). This results in enhanced compensation capability, reduced THD, faster response time, and improved system stability.},
      keywords = {Power Quality, UPFC, Dc Link Capacitors, Facts, UPQC & Dstatcom, VSI, Hysteresis PWM},
      month = {April},
      doi = {https://doi.org/10.64388/IREV9I10-1717052}
  }