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To address various challenges in power generation and distribution such as power quality deterioration, total harmonic distortion (THD), stability issues, and transient response, FACTS (Flexible Alternating Current Transmission Systems) devices are commonly employed. The Unified Power Flow Controller (UPFC) plays a significant role among these devices. Artificial Intelligence techniques, particularly Artificial Neural Networks (ANNs), are utilized to enhance their performance. In this paper, we propose a novel approach combining an ANN controller with UPFC. This combination aims to significantly improve upon previous methodologies by reducing THD values and enhancing power system stability. In conjunction with a shunt filter and transformer, the ANN controller effectively manages power transient conditions, thereby demonstrating superior performance compared to conventional methods.

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Improvement of UPFC Performance in Power Systems Using Artificial Intelligence

  • 会议论文

  • 发表日期：

    2025年

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  • Mamatha Deenakonda,
  • Padma Jyothi Uppalapati,
  • Sridevi Bonthu,
  • Phanikumar Chittala

摘要

To address various challenges in power generation and distribution such as power quality deterioration, total harmonic distortion (THD), stability issues, and transient response, FACTS (Flexible Alternating Current Transmission Systems) devices are commonly employed. The Unified Power Flow Controller (UPFC) plays a significant role among these devices. Artificial Intelligence techniques, particularly Artificial Neural Networks (ANNs), are utilized to enhance their performance. In this paper, we propose a novel approach combining an ANN controller with UPFC. This combination aims to significantly improve upon previous methodologies by reducing THD values and enhancing power system stability. In conjunction with a shunt filter and transformer, the ANN controller effectively manages power transient conditions, thereby demonstrating superior performance compared to conventional methods.