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Title: Uncertainty Quantification in Stochastic Economic Dispatch using Gaussian Process Emulation

Authors:
 [1];  [2];  [3];  [3];  [2];  [3]
  1. University of California, Santa Cruz
  2. Virginia Polytechnic Institute and State University
  3. Lawrence Livermore National Laboratory
Publication Date:
Research Org.:
Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States)
Sponsoring Org.:
USDOE National Nuclear Security Administration (NNSA)
OSTI Identifier:
1668499
Report Number(s):
LLNL-CONF-788518
985920
DOE Contract Number:  
AC52-07NA27344
Resource Type:
Conference
Resource Relation:
Conference: Washington, DC, United States
Country of Publication:
United States
Language:
English
Subject:
Engineering - Power transmission and distribution, Energy - Wind

Citation Formats

Hu, Z, Xu, Y, Korkali, M, Chen, X, Mili, L, and Tong, C H. Uncertainty Quantification in Stochastic Economic Dispatch using Gaussian Process Emulation. United States: N. p., 2020. Web. doi:10.1109/ISGT45199.2020.9087714.
Hu, Z, Xu, Y, Korkali, M, Chen, X, Mili, L, & Tong, C H. Uncertainty Quantification in Stochastic Economic Dispatch using Gaussian Process Emulation. United States. doi:10.1109/ISGT45199.2020.9087714.
Hu, Z, Xu, Y, Korkali, M, Chen, X, Mili, L, and Tong, C H. Sun . "Uncertainty Quantification in Stochastic Economic Dispatch using Gaussian Process Emulation". United States. doi:10.1109/ISGT45199.2020.9087714. https://www.osti.gov/servlets/purl/1668499.
@article{osti_1668499,
title = {Uncertainty Quantification in Stochastic Economic Dispatch using Gaussian Process Emulation},
author = {Hu, Z and Xu, Y and Korkali, M and Chen, X and Mili, L and Tong, C H},
abstractNote = {},
doi = {10.1109/ISGT45199.2020.9087714},
journal = {},
number = ,
volume = ,
place = {United States},
year = {2020},
month = {9}
}

Conference:
Other availability
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