Gaussian Process Learning-based Probabilistic Optimal Power Flow

• Main Authors: Pareek, Parikshit, Nguyen, Hung D.
• Other Authors: School of Electrical and Electronic Engineering
• Format: Article
• Language: English
• Published: 2021
• Subjects: Engineering::Electrical and electronic engineering; Uncertainty; Ground Penetrating Radar
• Online Access: https://hdl.handle.net/10356/150725
• Institution: Nanyang Technological University

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...