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Title: Importance Sampling with Analog Scenarios for Stochastic Economic Dispatch

Abstract

Increasing penetrations of renewable energy sources such as wind into power grids motivates the investigation of new approaches to 5-minute economic dispatch computation. In this poster, we investigate the application of importance sampling in the two-stage stochastic economic dispatch problem while using historical data to characterize uncertainty. In our numerical experiments, we observe that importance sampling performs better than the standard Monte Carlo sampling approach in preventing loss-of-load. While first-stage costs are comparable for both sampling methods, the second-stage costs are significantly reduced when the importance sampling method is employed.

Authors:
 [1];  [1];  [1];  [1]
  1. National Renewable Energy Laboratory (NREL), Golden, CO (United States)
Publication Date:
Research Org.:
National Renewable Energy Lab. (NREL), Golden, CO (United States)
Sponsoring Org.:
USDOE Office of Science (SC), Advanced Scientific Computing Research (ASCR) (SC-21), Scientific Discovery through Advanced Computing (SciDAC)
OSTI Identifier:
1483233
Report Number(s):
NREL/PO-2C00-72784
DOE Contract Number:  
AC36-08GO28308
Resource Type:
Conference
Resource Relation:
Conference: Presented at the Energy Systems and Optimization Workshop 2018, 15-16 November 2018, Atlanta, Georgia
Country of Publication:
United States
Language:
English
Subject:
97 MATHEMATICS AND COMPUTING; importance sampling; economic dispatch; analog forecasting; electric grid; wind energy; integration

Citation Formats

Satkauskas, Ignas V, Reynolds, Matthew, Sigler, Devon, and Jones, Wesley B. Importance Sampling with Analog Scenarios for Stochastic Economic Dispatch. United States: N. p., 2018. Web.
Satkauskas, Ignas V, Reynolds, Matthew, Sigler, Devon, & Jones, Wesley B. Importance Sampling with Analog Scenarios for Stochastic Economic Dispatch. United States.
Satkauskas, Ignas V, Reynolds, Matthew, Sigler, Devon, and Jones, Wesley B. Mon . "Importance Sampling with Analog Scenarios for Stochastic Economic Dispatch". United States. doi:. https://www.osti.gov/servlets/purl/1483233.
@article{osti_1483233,
title = {Importance Sampling with Analog Scenarios for Stochastic Economic Dispatch},
author = {Satkauskas, Ignas V and Reynolds, Matthew and Sigler, Devon and Jones, Wesley B},
abstractNote = {Increasing penetrations of renewable energy sources such as wind into power grids motivates the investigation of new approaches to 5-minute economic dispatch computation. In this poster, we investigate the application of importance sampling in the two-stage stochastic economic dispatch problem while using historical data to characterize uncertainty. In our numerical experiments, we observe that importance sampling performs better than the standard Monte Carlo sampling approach in preventing loss-of-load. While first-stage costs are comparable for both sampling methods, the second-stage costs are significantly reduced when the importance sampling method is employed.},
doi = {},
journal = {},
number = ,
volume = ,
place = {United States},
year = {Mon Nov 19 00:00:00 EST 2018},
month = {Mon Nov 19 00:00:00 EST 2018}
}

Conference:
Other availability
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