Smart-DS: synthetic models for advanced, realistic testing: distribution systems and scenarios

V. Krishnan, B. Palmintier, B.M. Hodge, E.T. Hale, T. Elgindy, B. Bugbee, M.N. Rossol, A.J. Lopez, D. Krishnamurthy, C.R. Vergara Ramírez, C. Mateo, F. Postigo Marcos, F. de Cuadra, T. Gómez, P. Dueñas, M. Luke, V. Li, M. Vinoth, S. Kadankodu

Technical Conference to Increase Real-Time and Day-Ahead Efficiency Through Software - FERC 2017, Washington (United States of America). 26-28 junio 2017

Summary:

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.

Keywords: 24 POWER TRANSMISSION AND DISTRIBUTION; synthetic distribution system datasets; standard scenarios; public data for distribution; grid data; reference network model

Publication date: June 2017.

Citation:
Krishnan, V., Palmintier, B., Hodge, B.M., Hale, E.T., Elgindy, T., Bugbee, B., Rossol, M.N., Lopez, A.J., Krishnamurthy, D., Vergara Ramírez, C.R., Mateo, C., Postigo Marcos, F., de Cuadra, F., Gómez, T., Dueñas, P., Smart-DS: synthetic models for advanced, realistic testing: distribution systems and scenarios, Technical Conference to Increase Real-Time and Day-Ahead Efficiency Through Software - FERC 2017, Washington (United States of America). 26-28 June 2017.

IIT-17-197A_abstract