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Title: Chance-constrained economic dispatch with renewable energy and storage

Abstract

Increased penetration of renewables, along with uncertainties associated with them, have transformed how power systems are operated. High levels of uncertainty means that it is not longer possible to guarantee operational feasibility with certainty, instead constraints are required to be satisfied with high probability. We present a chance-constrained economic dispatch model that efficiently integrates energy storage and high renewable penetration to satisfy renewable portfolio requirements. Specifically, it is required that wind energy contributes at least a prespecified ratio of the total demand and that the scheduled wind energy is dispatchable with high probability. We develop an approximated partial sample average approximation (PSAA) framework to enable efficient solution of large-scale chanceconstrained economic dispatch problems. Computational experiments on the IEEE-24 bus system show that the proposed PSAA approach is more accurate, closer to the prescribed tolerance, and about 100 times faster than sample average approximation. Improved efficiency of our PSAA approach enables solution of WECC-240 system in minutes.

Authors:
ORCiD logo [1];  [2];  [2];  [2];  [2];  [3]
  1. Univ. of Arizona, Tucson, AZ (United States)
  2. Sandia National Lab. (SNL-CA), Livermore, CA (United States)
  3. Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)
Publication Date:
Research Org.:
Sandia National Lab. (SNL-CA), Livermore, CA (United States)
Sponsoring Org.:
USDOE National Nuclear Security Administration (NNSA)
OSTI Identifier:
1427212
Report Number(s):
SAND-2015-8031J
Journal ID: ISSN 0926-6003; 603913
Grant/Contract Number:  
AC04-94AL85000
Resource Type:
Journal Article: Accepted Manuscript
Journal Name:
Computational Optimization and applications
Additional Journal Information:
Journal Volume: 70; Journal Issue: 2; Journal ID: ISSN 0926-6003
Publisher:
Springer
Country of Publication:
United States
Language:
English
Subject:
24 POWER TRANSMISSION AND DISTRIBUTION

Citation Formats

Cheng, Jianqiang, Chen, Richard Li-Yang, Najm, Habib N., Pinar, Ali, Safta, Cosmin, and Watson, Jean-Paul. Chance-constrained economic dispatch with renewable energy and storage. United States: N. p., 2018. Web. doi:10.1007/s10589-018-0006-2.
Cheng, Jianqiang, Chen, Richard Li-Yang, Najm, Habib N., Pinar, Ali, Safta, Cosmin, & Watson, Jean-Paul. Chance-constrained economic dispatch with renewable energy and storage. United States. doi:10.1007/s10589-018-0006-2.
Cheng, Jianqiang, Chen, Richard Li-Yang, Najm, Habib N., Pinar, Ali, Safta, Cosmin, and Watson, Jean-Paul. Thu . "Chance-constrained economic dispatch with renewable energy and storage". United States. doi:10.1007/s10589-018-0006-2.
@article{osti_1427212,
title = {Chance-constrained economic dispatch with renewable energy and storage},
author = {Cheng, Jianqiang and Chen, Richard Li-Yang and Najm, Habib N. and Pinar, Ali and Safta, Cosmin and Watson, Jean-Paul},
abstractNote = {Increased penetration of renewables, along with uncertainties associated with them, have transformed how power systems are operated. High levels of uncertainty means that it is not longer possible to guarantee operational feasibility with certainty, instead constraints are required to be satisfied with high probability. We present a chance-constrained economic dispatch model that efficiently integrates energy storage and high renewable penetration to satisfy renewable portfolio requirements. Specifically, it is required that wind energy contributes at least a prespecified ratio of the total demand and that the scheduled wind energy is dispatchable with high probability. We develop an approximated partial sample average approximation (PSAA) framework to enable efficient solution of large-scale chanceconstrained economic dispatch problems. Computational experiments on the IEEE-24 bus system show that the proposed PSAA approach is more accurate, closer to the prescribed tolerance, and about 100 times faster than sample average approximation. Improved efficiency of our PSAA approach enables solution of WECC-240 system in minutes.},
doi = {10.1007/s10589-018-0006-2},
journal = {Computational Optimization and applications},
number = 2,
volume = 70,
place = {United States},
year = {Thu Apr 19 00:00:00 EDT 2018},
month = {Thu Apr 19 00:00:00 EDT 2018}
}

Journal Article:
Free Publicly Available Full Text
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