5 papers
Root Cause Analysis with Latent Confounders using Partial Ancestral Graphs
Henrique O. Caetano, Rafael Arone, Carlos Dias Maciel
Finding the source of failures, known as Root Cause Analysis (RCA), is essential for identifying the root causes of anomalies and maintaining the reliability of complex systems. Wh…
Admittance Sensitivity-Informed Modular GP for Scalable Topology-Adaptive Power-Flow Learning
Henrique O. Caetano, Carlos Dias Maciel, Rahul K. Gupta
Data-driven approaches for learning power flow models suffer from weak generalization across varying network topologies and limited computational scalability. Existing methods typi…
bayesgrid: An Open-Source Python Tool for Generating Probabilistic Synthetic Transmission-Distribution Grids Using Bayesian Hierarchical Models
Henrique O. Caetano, Rahul K. Gupta, Carlos D. Maciel
In this work, we present bayesgrid, an open-source python toolbox for generating synthetic power transmission-distribution systems for any geographical location worldwide, using th…
Bayesian Model-based Generation of Synthetic Unbalanced Distribution Networks Incorporating Reliability Indices
Henrique O. Caetano, Rahul K. Gupta, Cristhian G. da R. de Oliveira +2
Real-world power distribution data are often inaccessible due to privacy and security concerns, highlighting the need for tools for generating realistic synthetic networks. Existin…
A Bayesian Hierarchical Model for Generating Synthetic Unbalanced Power Distribution Grids
Henrique O. Caetano, Rahul K. Gupta, Marco Aiello +1
The real-world data of power networks is often inaccessible due to privacy and security concerns, highlighting the need for tools to generate realistic synthetic network data. Exis…