Knowledge-Inspired Data-Aided Robust Power Flow in Distribution Networks With ZIP Loads and High DER Penetration

Characterized by increasing penetration of distributed energy resources, active distribution networks necessitate developing uncertainty-adaptive power flow (PF) algorithms to cover broad operating conditions. Despite the success of data-driven methods in improving such adaptivity, the efficacy of t...

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Veröffentlicht in:	IEEE transactions on industry applications 2025, p.1-10
Hauptverfasser:	Chung, Sungjoo, Zhang, Ying, Zhang, Yuanshuo
Format:	Artikel
Sprache:	eng
Schlagworte:	Accuracy Active distribution networks Adaptation models Data models distributed energy resources Distributed power generation Distribution networks Load flow Load modeling outliers physics-informed machine learning power flow Robustness Taylor series Voltage ZIP loads
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