Robust mapping rule estimation for power flow analysis in distribution grids

Jiafan Yu, Yang Weng, Ram Rajagopal

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

The increasing integration of distributed energy resources (DERs) calls for new monitoring and operational planning tools to ensure stability and sustainability in distribution grids. One idea is to use existing monitoring tools in transmission grids and some primary distribution grids. However, they usually depend on the knowledge of the system model, e.g., the topology and line parameters, which may be unavailable in primary and secondary distribution grids. Furthermore, a utility usually has limited modeling ability of active controllers as they may belong to a third party like residential customers. To solve the modeling problem in traditional power flow analysis, we propose a support vector regression (SVR) approach to reveal the mapping rules between different variables and recover useful variables based on historical data. We illustrate the advantages of using the SVR model over traditional regression method that finds line parameters in distribution grids. Specifically, the SVR model is robust enough to recover the mapping rules when the regression method fails. This happens when 1) there are measurement outliers, 2) there are active controllers, or 3) measurements are only available at some part of a distribution grid. We demonstrate the superior performance of our method through extensive numerical validation on different scales of distribution grids and IEEE test buses. Robustness of our method is observed.

Original languageEnglish (US)
Title of host publication2017 North American Power Symposium, NAPS 2017
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781538626993
DOIs
StatePublished - Nov 13 2017
Event2017 North American Power Symposium, NAPS 2017 - Morgantown, United States
Duration: Sep 17 2017Sep 19 2017

Other

Other2017 North American Power Symposium, NAPS 2017
CountryUnited States
CityMorgantown
Period9/17/179/19/17

Fingerprint

Power Flow
Grid
Support Vector Regression
Controllers
Monitoring
Energy resources
Sustainable development
Topology
Regression Model
Regression
Planning
Controller
Line
Historical Data
Sustainability
Modeling
Outlier
Customers
Robustness
Resources

ASJC Scopus subject areas

  • Computer Networks and Communications
  • Energy Engineering and Power Technology
  • Control and Optimization
  • Electrical and Electronic Engineering

Cite this

Yu, J., Weng, Y., & Rajagopal, R. (2017). Robust mapping rule estimation for power flow analysis in distribution grids. In 2017 North American Power Symposium, NAPS 2017 [8107397] Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/NAPS.2017.8107397

Robust mapping rule estimation for power flow analysis in distribution grids. / Yu, Jiafan; Weng, Yang; Rajagopal, Ram.

2017 North American Power Symposium, NAPS 2017. Institute of Electrical and Electronics Engineers Inc., 2017. 8107397.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Yu, J, Weng, Y & Rajagopal, R 2017, Robust mapping rule estimation for power flow analysis in distribution grids. in 2017 North American Power Symposium, NAPS 2017., 8107397, Institute of Electrical and Electronics Engineers Inc., 2017 North American Power Symposium, NAPS 2017, Morgantown, United States, 9/17/17. https://doi.org/10.1109/NAPS.2017.8107397
Yu J, Weng Y, Rajagopal R. Robust mapping rule estimation for power flow analysis in distribution grids. In 2017 North American Power Symposium, NAPS 2017. Institute of Electrical and Electronics Engineers Inc. 2017. 8107397 https://doi.org/10.1109/NAPS.2017.8107397
Yu, Jiafan ; Weng, Yang ; Rajagopal, Ram. / Robust mapping rule estimation for power flow analysis in distribution grids. 2017 North American Power Symposium, NAPS 2017. Institute of Electrical and Electronics Engineers Inc., 2017.
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