5 papers
Distributed Reinforcement Learning using Local Smart Meter Data for Voltage Regulation in Distribution Networks
Dong Liu, Juan S. Giraldo, Peter Palensky +1
Centralised reinforcement learning (RL) for voltage magnitude regulation in distribution networks typically involves numerous agent-environment interactions and power flow (PF) cal…
Model-Free Privacy Preserving Power Flow Analysis in Distribution Networks
Dong Liu, Juan S. Giraldo, Peter Palensky +1
Model-free power flow calculation, driven by the rise of smart meter (SM) data and the lack of network topology, often relies on artificial intelligence neural networks (ANNs). How…
Lower Dimensional Spherical Representation of Medium Voltage Load Profiles for Visualization, Outlier Detection, and Generative Modelling
Edgar Mauricio Salazar Duque, Bart van der Holst, Pedro P. Vergara +5
This paper presents the spherical lower dimensional representation for daily medium voltage load profiles, based on principal component analysis. The objective is to unify and simp…
Tensor Power Flow Formulations for Multidimensional Analyses in Distribution Systems
Edgar Mauricio Salazar Duque, Juan S. Giraldo, Pedro P. Vergara +3
In this paper, we present two multidimensional power flow formulations based on a fixed-point iteration (FPI) algorithm to efficiently solve hundreds of thousands of power flows in…
PowerFlowNet: Power Flow Approximation Using Message Passing Graph Neural Networks
Nan Lin, Stavros Orfanoudakis, Nathan Ordonez Cardenas +2
Accurate and efficient power flow (PF) analysis is crucial in modern electrical networks' operation and planning. Therefore, there is a need for scalable algorithms that can provid…