Gaussian Process Learning-based Probabilistic Optimal Power Flow

• المؤلفون الرئيسيون: Pareek, Parikshit, Nguyen, Hung D.
• مؤلفون آخرون: School of Electrical and Electronic Engineering
• التنسيق: مقال
• اللغة: English
• منشور في: 2021
• الموضوعات: Engineering::Electrical and electronic engineering; Uncertainty; Ground Penetrating Radar
• الوصول للمادة أونلاين: https://hdl.handle.net/10356/150725

In this letter, we present a novel Gaussian Process Learning-based Probabilistic Optimal Power Flow (GP-POPF) for solving POPF under renewable and load uncertainties of arbitrary distribution. The proposed method relies on a non-parametric Bayesian inference-based uncertainty propagation approach, c...