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Title: Distribution System State Estimation in the Presence of High Solar Penetration

Abstract

In recent years, the low-to-medium voltage distribution networks are experiencing rising levels of distributed energy resources, including renewable generation, along with improved sensing, communication and automation infrastructure. As such, state estimation methods for distribution systems are becoming increasingly relevant as a means to enable better control strategies that can both leverage the benefits and mitigate the risks associated with high penetration of variable and uncertain distributed generation resources. Primary challenges of this problem include modeling complexities (nonlinear non-convex power-flow equations), limited availability of sensor measurements, and high penetration of uncertain renewable generation. This paper formulates the distribution system state estimation as a nonlinear weighted least squares problem, based on sensor measurements as well as forecasts data (both load and generation). We investigate the sensitivity of state estimator accuracy to (load/generation) forecast uncertainties, sensor accuracy, and sensor coverage levels.

Authors:
 [1]; ORCiD logo [1];  [1]; ORCiD logo [1]; ORCiD logo [1]
  1. BATTELLE (PACIFIC NW LAB)
Publication Date:
Research Org.:
Pacific Northwest National Lab. (PNNL), Richland, WA (United States)
Sponsoring Org.:
USDOE
OSTI Identifier:
1583165
Report Number(s):
PNNL-SA-138831
DOE Contract Number:  
AC05-76RL01830
Resource Type:
Conference
Resource Relation:
Conference: American Controls Conference (ACC 2019), July 10-12, 2019, Philadelphia, PA
Country of Publication:
United States
Language:
English
Subject:
Distribution system state estimation, nonlinear optimization

Citation Formats

Ramachandran, Thiagarajan, Reiman, Andrew P., Nandanoori, Sai Pushpak, Rice, Mark J., and Kundu, Soumya. Distribution System State Estimation in the Presence of High Solar Penetration. United States: N. p., 2019. Web. doi:10.23919/ACC.2019.8814486.
Ramachandran, Thiagarajan, Reiman, Andrew P., Nandanoori, Sai Pushpak, Rice, Mark J., & Kundu, Soumya. Distribution System State Estimation in the Presence of High Solar Penetration. United States. doi:10.23919/ACC.2019.8814486.
Ramachandran, Thiagarajan, Reiman, Andrew P., Nandanoori, Sai Pushpak, Rice, Mark J., and Kundu, Soumya. Fri . "Distribution System State Estimation in the Presence of High Solar Penetration". United States. doi:10.23919/ACC.2019.8814486.
@article{osti_1583165,
title = {Distribution System State Estimation in the Presence of High Solar Penetration},
author = {Ramachandran, Thiagarajan and Reiman, Andrew P. and Nandanoori, Sai Pushpak and Rice, Mark J. and Kundu, Soumya},
abstractNote = {In recent years, the low-to-medium voltage distribution networks are experiencing rising levels of distributed energy resources, including renewable generation, along with improved sensing, communication and automation infrastructure. As such, state estimation methods for distribution systems are becoming increasingly relevant as a means to enable better control strategies that can both leverage the benefits and mitigate the risks associated with high penetration of variable and uncertain distributed generation resources. Primary challenges of this problem include modeling complexities (nonlinear non-convex power-flow equations), limited availability of sensor measurements, and high penetration of uncertain renewable generation. This paper formulates the distribution system state estimation as a nonlinear weighted least squares problem, based on sensor measurements as well as forecasts data (both load and generation). We investigate the sensitivity of state estimator accuracy to (load/generation) forecast uncertainties, sensor accuracy, and sensor coverage levels.},
doi = {10.23919/ACC.2019.8814486},
journal = {},
number = ,
volume = ,
place = {United States},
year = {2019},
month = {7}
}

Conference:
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