A Comparative of Positive Real Truncation and H-Infinity Reduction Techniques for Model Simplification in Electrical Circuits and Power Systems

In the domain of electrical circuits, electronics, and power systems, the escalating complexity of systems and the challenges posed by computational demands, data abundance, and real-time responses have prompted the exploration of model reduction strategies. This paper conducts a comparative study of two model reduction algorithms—Positive Real Balancing (PRR) and H-infinity Balancing (HBR)—applied to an electrical and electronic system. The objective is to assess their efficacy in maintaining system stability, preserving passivity, and reducing complexity. Through a systematic evaluation of error profiles for varying reduction orders, this study unveils the strengths and limitations of each method. The findings elucidate the interplay between accuracy and complexity, offering insights into the trade-offs and optimal scenarios for employing these techniques. The analysis equips practitioners and researchers with a comprehensive understanding of model reduction methods for tackling the challenges of modern electrical circuits and power systems.