Distributed Energy Resources Topology Identification via Graphical Modeling

Distributed energy resources (DERs), such as photovoltaic, wind, and gas generators, are connected to the grid more than ever before, which introduces tremendous changes in the distribution grid. Due to these changes, it is important to understand where these DERs are connected in order to sustainab...

Full description

Saved in:
Bibliographic Details
Published in:IEEE transactions on power systems Vol. 32; no. 4; pp. 2682 - 2694
Main Authors: Yang Weng, Yizheng Liao, Rajagopal, Ram
Format: Journal Article
Language:English
Published: New York IEEE 01.07.2017
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subjects:
Computer simulation
Density estimation robust algorithm
Distributed energy resources
Distributed generation
distribution grids
Electric potential
Electric power distribution
Electric utilities
Electricity distribution
Electronic devices
Energy resources
Energy sources
Gas generators
Generators
graphical model
Graphical models
Modelling
mutual information
Network topology
Power flow
Probabilistic logic
Probabilistic methods
Probability theory
Sensors
Topology
topology identification
Voltage measurement
Wind power generation
ISSN:0885-8950, 1558-0679
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:Distributed energy resources (DERs), such as photovoltaic, wind, and gas generators, are connected to the grid more than ever before, which introduces tremendous changes in the distribution grid. Due to these changes, it is important to understand where these DERs are connected in order to sustainably operate the distribution grid. But the exact distribution system topology is difficult to obtain due to frequent distribution grid reconfigurations and insufficient knowledge about new components. In this paper, we propose a methodology that utilizes new data from sensor-equipped DER devices to obtain the distribution grid topology. Specifically, a graphical model is presented to describe the probabilistic relationship among different voltage measurements. With power flow analysis, a mutual information-based identification algorithm is proposed to deal with tree and partially meshed networks. Simulation results show highly accurate connectivity identification in the IEEE standard distribution test systems and Electric Power Research Institute test systems.
Bibliography:ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
content type line 14
ISSN:0885-8950
1558-0679
DOI:10.1109/TPWRS.2016.2628876