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A SSSC based multi-objective optimal controller to damp power system oscillation is presented in this study. The control action is based on a 2-stage fractional lead-lag controller to improve closed-loop response of the system. The gains of proposed controller are tuned by Manta Ray Foraging Optimization technique (MRFO). The minimization objective function is based on variation in speed and real power, overshoot, undershoot and settling time. A 2-area 4-machine system has been taken into study to validate performance of proposed controller. The case studies considered in this work are variation in mechanical turbine output power, load change and reference voltage to generator. The low frequency modelling of SSSC has been considered and eigen analysis of system response has been analysed to justify efficiency of proposed controller. The performance of MRFO has been compared with PSO and DE techniques for optimal damping action. Also, performance of proposed fractional SSSC action has been compared with only lead-lag based SSSC action and is found to be better than conventional SSSC controller action.

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Multi-objective Manta Ray Foraging Optimized Fractional SSSC Control Action for Enhancing Small Signal Stability Action

  • 会议论文

  • 发表日期：

    2025年

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  • Narayan Nahak,
  • Samarjeet Satapathy,
  • Sourashish Patra,
  • Tarini Bedi,
  • Rajesh Kumar Behera,
  • Alok Kumar Mishra,
  • Akshaya Kumar Patra

摘要

A SSSC based multi-objective optimal controller to damp power system oscillation is presented in this study. The control action is based on a 2-stage fractional lead-lag controller to improve closed-loop response of the system. The gains of proposed controller are tuned by Manta Ray Foraging Optimization technique (MRFO). The minimization objective function is based on variation in speed and real power, overshoot, undershoot and settling time. A 2-area 4-machine system has been taken into study to validate performance of proposed controller. The case studies considered in this work are variation in mechanical turbine output power, load change and reference voltage to generator. The low frequency modelling of SSSC has been considered and eigen analysis of system response has been analysed to justify efficiency of proposed controller. The performance of MRFO has been compared with PSO and DE techniques for optimal damping action. Also, performance of proposed fractional SSSC action has been compared with only lead-lag based SSSC action and is found to be better than conventional SSSC controller action.