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Title: Optimal Power Flow in DC Networks with Robust Feasibility and Stability Guarantees

Abstract

With high penetrations of renewable generation and variable loads, there is significant uncertainty associated with power flows in DC networks such that stability and operational constraint satisfaction are of concern. Most existing DC network optimal power flow (DN-OPF) formulations assume exact knowledge of loading conditions and do not provide stability guarantees. Here, in contrast, this paper studies a DN-OPF formulation which considers both stability and operational constraint satisfaction under uncertainty. The need to account for a range of uncertainty realizations in this paper's robust optimization formulation results in a challenging semi-infinite program (SIP). The proposed solution algorithm reformulates this SIP into a computationally tractable problem by constructing a tight convex inner approximation of the stability set using sufficient conditions for the existence of a feasible and stable power flow solution. Optimal generator set-points are obtained by optimizing over the proposed convex stability set. The validity and effectiveness of the propose algorithm is demonstrated through various DC networks adapted from IEEE test cases.

Authors:
 [1];  [2];  [3];  [4];  [5];  [1]
+ Show Author Affiliations
  1. Argonne National Lab. (ANL), Lemont, IL (United States)
  2. National Renewable Energy Lab. (NREL), Golden, CO (United States)
  3. Georgia Institute of Technology, Atlanta, GA (United States)
  4. Xi'an Jiaotong Univ., Shaanxi (China)
  5. Temple Univ., Philadelphia, PA (United States)
Publication Date:
Research Org.:
National Renewable Energy Laboratory (NREL), Golden, CO (United States); Argonne National Laboratory (ANL), Argonne, IL (United States)
Sponsoring Org.:
USDOE Laboratory Directed Research and Development (LDRD) Program; USDOE Office of Energy Efficiency and Renewable Energy (EERE), Renewable Power Office. Solar Energy Technologies Office
OSTI Identifier:
1834045
Alternate Identifier(s):
OSTI ID: 1960312
Report Number(s):
NREL/JA-5D00-81591
Journal ID: ISSN 2325-5870; MainId:82364;UUID:07a415db-3b6f-4158-bb5c-eecda9a5c4b8;MainAdminID:63386
Grant/Contract Number:  
AC36-08GO28308; AC02-06CH11357
Resource Type:
Accepted Manuscript
Journal Name:
IEEE Transactions on Control of Network Systems
Additional Journal Information:
Journal Volume: 9; Journal Issue: 2; Journal ID: ISSN 2325-5870
Publisher:
IEEE
Country of Publication:
United States
Language:
English
Subject:
24 POWER TRANSMISSION AND DISTRIBUTION; generators; load modeling; loading; power system stability; renewable energy sources; uncertainty; voltage

Citation Formats

Liu, Jianzhe, Cui, Bai, Molzahn, Daniel K., Chen, Chen, Lu, Xiaonan, and Qiu, Feng. Optimal Power Flow in DC Networks with Robust Feasibility and Stability Guarantees. United States: N. p., 2021. Web. doi:10.1109/TCNS.2021.3124932.
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Liu, Jianzhe, Cui, Bai, Molzahn, Daniel K., Chen, Chen, Lu, Xiaonan, & Qiu, Feng. Optimal Power Flow in DC Networks with Robust Feasibility and Stability Guarantees. United States. https://doi.org/10.1109/TCNS.2021.3124932
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Liu, Jianzhe, Cui, Bai, Molzahn, Daniel K., Chen, Chen, Lu, Xiaonan, and Qiu, Feng. Thu . "Optimal Power Flow in DC Networks with Robust Feasibility and Stability Guarantees". United States. https://doi.org/10.1109/TCNS.2021.3124932. https://www.osti.gov/servlets/purl/1834045.
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@article{osti_1834045,
title = {Optimal Power Flow in DC Networks with Robust Feasibility and Stability Guarantees},
author = {Liu, Jianzhe and Cui, Bai and Molzahn, Daniel K. and Chen, Chen and Lu, Xiaonan and Qiu, Feng},
abstractNote = {With high penetrations of renewable generation and variable loads, there is significant uncertainty associated with power flows in DC networks such that stability and operational constraint satisfaction are of concern. Most existing DC network optimal power flow (DN-OPF) formulations assume exact knowledge of loading conditions and do not provide stability guarantees. Here, in contrast, this paper studies a DN-OPF formulation which considers both stability and operational constraint satisfaction under uncertainty. The need to account for a range of uncertainty realizations in this paper's robust optimization formulation results in a challenging semi-infinite program (SIP). The proposed solution algorithm reformulates this SIP into a computationally tractable problem by constructing a tight convex inner approximation of the stability set using sufficient conditions for the existence of a feasible and stable power flow solution. Optimal generator set-points are obtained by optimizing over the proposed convex stability set. The validity and effectiveness of the propose algorithm is demonstrated through various DC networks adapted from IEEE test cases.},
doi = {10.1109/TCNS.2021.3124932},
journal = {IEEE Transactions on Control of Network Systems},
number = 2,
volume = 9,
place = {United States},
year = {Thu Nov 04 00:00:00 EDT 2021},
month = {Thu Nov 04 00:00:00 EDT 2021}
}
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https://doi.org/10.1109/TCNS.2021.3124932
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