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Understanding the Computing and Analysis Needs for Resiliency of Power Systems from Severe Weather Impacts

Conference ·

As the frequency and intensity of severe weather has increased, its effect on the electric grid has manifested in the form of significantly more and larger outages in the United States. This has become especially true for regions that were previously isolated from weather extremes. In this paper, we analyze the weather impacts on the electric power grid across a variety of weather conditions, draw correlations, and provide practical insights into the operational state of these systems. High resolution computational modeling of specific meteorological variables, computational approaches to solving power system models under these conditions, and the types of resiliency needs are highlighted as goal-oriented computing approaches are being built to address grid resiliency needs. An example analysis correlating outages to 1km day-ahead weather from two historical winter storms, calculated on a large cluster using a combination of interpolated and extrapolated inputs from multiple instrumented sites to workflows that produce primary meteorological outputs, is shown as initial proof of concept.

Research Organization:
National Renewable Energy Laboratory (NREL), Golden, CO (United States)
Sponsoring Organization:
USDOE Office of Energy Efficiency and Renewable Energy (EERE)
DOE Contract Number:
AC36-08GO28308
OSTI ID:
1996408
Report Number(s):
NREL/CP-5700-85854; MainId:86627; UUID:290e8c31-3f41-4f5a-b828-237af424ef13; MainAdminID:70289
Resource Relation:
Conference: Presented at PASC '23: Platform for Advanced Scientific Computing Conference, 26-28 June 2023, Davos, Switzerland
Country of Publication:
United States
Language:
English

References (18)

State‐of‐the‐art review on power system resilience and assessment techniques journal December 2020
Cascading risks: Understanding the 2021 winter blackout in Texas journal July 2021
Outage prediction models for snow and ice storms journal March 2020
Vulnerability assessment of the power grid against progressing wildfires journal April 2015
Income inequality and renewable energy consumption: Time-varying non-parametric evidence journal May 2021
How unprecedented was the February 2021 Texas cold snap? journal June 2021
Applications and Trends of High Performance Computing for Electric Power Systems: Focusing on Smart Grid journal June 2013
ASCENDS: Advanced data SCiENce toolkit for Non-Data Scientists journal February 2020
Specifying Transformer Winter and Summer Peak-Load Limits journal January 2005
Smart power grid and cloud computing journal August 2013
A multi-hazard approach to assess severe weather-induced major power outage risks in the U.S. journal July 2018
Advanced data science toolkit for non-data scientists – A user guide journal March 2020
Evaluating emerging long-duration energy storage technologies journal May 2022
Energy storage systems for renewable energy power sector integration and mitigation of intermittency journal July 2014
Dynamic modeling of the effects of vegetation management on weather-related power outages journal June 2022
Peak load reduction and load shaping in HVAC and refrigeration systems in commercial buildings by using a novel lightweight dynamic priority-based control strategy journal November 2020
Prediction of Solar Irradiance and Photovoltaic Solar Energy Product Based on Cloud Coverage Estimation Using Machine Learning Methods journal March 2021
Opportunities and challenges for machine learning in weather and climate modelling: hard, medium and soft AI
  • Chantry, Matthew; Christensen, Hannah; Dueben, Peter
  • Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences, Vol. 379, Issue 2194 https://doi.org/10.1098/rsta.2020.0083
journal February 2021