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Title: Smart-DS: Synthetic Models for Advanced, Realistic Testing: Distribution Systems and Scenarios

Abstract

The National Renewable Energy Laboratory (NREL) in collaboration with Massachusetts Institute of Technology (MIT), Universidad Pontificia Comillas (Comillas-IIT, Spain) and GE Grid Solutions, is working on an ARPA-E GRID DATA project, titled Smart-DS, to create: 1) High-quality, realistic, synthetic distribution network models, and 2) Advanced tools for automated scenario generation based on high-resolution weather data and generation growth projections. Through these advancements, the Smart-DS project is envisioned to accelerate the development, testing, and adoption of advanced algorithms, approaches, and technologies for sustainable and resilient electric power systems, especially in the realm of U.S. distribution systems. This talk will present the goals and overall approach of the Smart-DS project, including the process of creating the synthetic distribution datasets using reference network model (RNM) and the comprehensive validation process to ensure network realism, feasibility, and applicability to advanced use cases. The talk will provide demonstrations of early versions of synthetic models, along with the lessons learnt from expert engagements to enhance future iterations. Finally, the scenario generation framework, its development plans, and co-ordination with GRID DATA repository teams to house these datasets for public access will also be discussed.

Authors:
ORCiD logo [1]; ORCiD logo [1];  [1];  [1];  [1];  [1];  [1];  [1]; ORCiD logo [1];  [2];  [3];  [3];  [3];  [3];  [2];  [2];  [2];  [4];  [4]
  1. National Renewable Energy Laboratory (NREL), Golden, CO (United States)
  2. MIT
  3. IIT Comillas
  4. GE Grid Solutions
Publication Date:
Research Org.:
National Renewable Energy Lab. (NREL), Golden, CO (United States)
Sponsoring Org.:
USDOE Advanced Research Projects Agency - Energy (ARPA-E)
OSTI Identifier:
1375108
Report Number(s):
NREL/PR-5D00-68764
DOE Contract Number:
AC36-08GO28308
Resource Type:
Conference
Resource Relation:
Conference: Presented at the Federal Energy Regulatory Commission (FERC) Technical Conference on Increasing Real-Time and Day-Ahead Market Efficiency through Improved Software, 26-28 June 2017, Washington, D.C.
Country of Publication:
United States
Language:
English
Subject:
24 POWER TRANSMISSION AND DISTRIBUTION; synthetic distribution system datasets; standard scenarios; public data for distribution; grid data; reference network model

Citation Formats

Krishnan, Venkat K, Palmintier, Bryan S, Hodge, Brian S, Hale, Elaine T, Elgindy, Tarek, Bugbee, Bruce, Rossol, Michael N, Lopez, Anthony J, Krishnamurthy, Dheepak, Vergara, Claudio, Domingo, Carlos Mateo, Postigo, Fernando, de Cuadra, Fernando, Gomez, Tomas, Duenas, Pablo, Luke, Max, Li, Vivian, Vinoth, Mohan, and Kadankodu, Sree. Smart-DS: Synthetic Models for Advanced, Realistic Testing: Distribution Systems and Scenarios. United States: N. p., 2017. Web.
Krishnan, Venkat K, Palmintier, Bryan S, Hodge, Brian S, Hale, Elaine T, Elgindy, Tarek, Bugbee, Bruce, Rossol, Michael N, Lopez, Anthony J, Krishnamurthy, Dheepak, Vergara, Claudio, Domingo, Carlos Mateo, Postigo, Fernando, de Cuadra, Fernando, Gomez, Tomas, Duenas, Pablo, Luke, Max, Li, Vivian, Vinoth, Mohan, & Kadankodu, Sree. Smart-DS: Synthetic Models for Advanced, Realistic Testing: Distribution Systems and Scenarios. United States.
Krishnan, Venkat K, Palmintier, Bryan S, Hodge, Brian S, Hale, Elaine T, Elgindy, Tarek, Bugbee, Bruce, Rossol, Michael N, Lopez, Anthony J, Krishnamurthy, Dheepak, Vergara, Claudio, Domingo, Carlos Mateo, Postigo, Fernando, de Cuadra, Fernando, Gomez, Tomas, Duenas, Pablo, Luke, Max, Li, Vivian, Vinoth, Mohan, and Kadankodu, Sree. Wed . "Smart-DS: Synthetic Models for Advanced, Realistic Testing: Distribution Systems and Scenarios". United States. doi:. https://www.osti.gov/servlets/purl/1375108.
@article{osti_1375108,
title = {Smart-DS: Synthetic Models for Advanced, Realistic Testing: Distribution Systems and Scenarios},
author = {Krishnan, Venkat K and Palmintier, Bryan S and Hodge, Brian S and Hale, Elaine T and Elgindy, Tarek and Bugbee, Bruce and Rossol, Michael N and Lopez, Anthony J and Krishnamurthy, Dheepak and Vergara, Claudio and Domingo, Carlos Mateo and Postigo, Fernando and de Cuadra, Fernando and Gomez, Tomas and Duenas, Pablo and Luke, Max and Li, Vivian and Vinoth, Mohan and Kadankodu, Sree},
abstractNote = {The National Renewable Energy Laboratory (NREL) in collaboration with Massachusetts Institute of Technology (MIT), Universidad Pontificia Comillas (Comillas-IIT, Spain) and GE Grid Solutions, is working on an ARPA-E GRID DATA project, titled Smart-DS, to create: 1) High-quality, realistic, synthetic distribution network models, and 2) Advanced tools for automated scenario generation based on high-resolution weather data and generation growth projections. Through these advancements, the Smart-DS project is envisioned to accelerate the development, testing, and adoption of advanced algorithms, approaches, and technologies for sustainable and resilient electric power systems, especially in the realm of U.S. distribution systems. This talk will present the goals and overall approach of the Smart-DS project, including the process of creating the synthetic distribution datasets using reference network model (RNM) and the comprehensive validation process to ensure network realism, feasibility, and applicability to advanced use cases. The talk will provide demonstrations of early versions of synthetic models, along with the lessons learnt from expert engagements to enhance future iterations. Finally, the scenario generation framework, its development plans, and co-ordination with GRID DATA repository teams to house these datasets for public access will also be discussed.},
doi = {},
journal = {},
number = ,
volume = ,
place = {United States},
year = {Wed Aug 09 00:00:00 EDT 2017},
month = {Wed Aug 09 00:00:00 EDT 2017}
}

Conference:
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  • This presentation provides an overview of full-scale, high-quality, synthetic distribution system data set(s) for testing distribution automation algorithms, distributed control approaches, ADMS capabilities, and other emerging distribution technologies.
  • This presentation provides a Smart-DS project overview and status update for the ARPA-e GRID DATA program meeting 2017, including distribution systems, models, and scenarios, as well as opportunities for GRID DATA collaborations.
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