Structure Learning in Power Distribution Networks
type: Item
instance of: scholarly article
title: Structure Learning in Power Distribution Networks
DOI: 10.1109/TCNS.2017.2673546
author: Deepjyoti Deka
author: Scott Backhaus
author: Michael Chertkov
published in: IEEE Transactions on Control of Network Systems
publication date: 2019-03-29T00:00:00Z
Mathematics Subject Classification ID: 93-XX
Mathematics Subject Classification ID: 90-XX
zbMATH DE Number: 7044972
MaRDI profile type: Publication
full work available at URL: tcns.2017.2673546
OpenAlex ID: W1499925099
Recommended article: Learning With End-Users in Distribution Grids: Topology and Parameter Estimation
Recommended article: Exploiting structure in large-scale electrical circuit and power system problems
Recommended article: A Hierarchical Optimization Architecture for Large-Scale Power Networks
Recommended article: Structural evaluation for distribution networks with distributed generation based on complex network
Recommended article: A fully distributed learning algorithm for power allocation in heterogeneous networks
Recommended article: Power system network parameter estimation
Recommended article: Distribution network design: New problems and related models
Recommended article: Distributed learning algorithms and lossless convex relaxation for economic dispatch with transmission losses and capacity limits
description: scientific article; zbMATH DE number 7044972