TY - GEN
T1 - Smart-DS: Synthetic Models for Advanced, Realistic Testing: Distribution Systems and Scenarios
AU - Krishnan, Venkat
AU - Palmintier, Bryan
AU - Hodge, Brian
AU - Hale, Elaine
AU - Elgindy, Tarek
AU - Rossol, Michael
AU - Lopez, Anthony
AU - Krishnamurthy, Dheepak
AU - Vergara, Claudio
AU - Domingo, Carlos
AU - Postigo, Fernando
AU - Cuadra, Fernando
AU - Gomez, Tomas
AU - Duenas, Pablo
AU - Luke, Max
AU - Li, Vivian
AU - Vinoth, Mohan
AU - Kadankodu, Sree
AU - Bugbee, Bruce
PY - 2017
Y1 - 2017
N2 - 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.
AB - 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.
KW - grid data
KW - public data for distribution
KW - reference network model
KW - standard scenarios
KW - synthetic distribution system datasets
M3 - Presentation
T3 - 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.
ER -
