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Title: A Survey of Distributed Optimization and Control Algorithms for Electric Power Systems

Abstract

Historically, centrally computed algorithms have been the primary means of power system optimization and control. With increasing penetrations of distributed energy resources requiring optimization and control of power systems with many controllable devices, distributed algorithms have been the subject of significant research interest. Here, this paper surveys the literature of distributed algorithms with applications to optimization and control of power systems. In particular, this paper reviews distributed algorithms for offline solution of optimal power flow (OPF) problems as well as online algorithms for real-time solution of OPF, optimal frequency control, optimal voltage control, and optimal wide-area control problems.

Authors:
ORCiD logo [1];  [2];  [3];  [4];  [5];  [5]; ORCiD logo [6]
  1. Argonne National Lab. (ANL), Lemont, IL (United States)
  2. Swiss Federal Institute of Technology (ETH), Zurich (Switzerland)
  3. KTH Royal Institute of Technology, Stockholm (Sweden)
  4. California Inst. of Technology (CalTech), Pasadena, CA (United States)
  5. Univ. of Texas at Austin, Austin, TX (United States)
  6. Univ. of California, Berkeley, CA (United States)
Publication Date:
Research Org.:
Argonne National Lab. (ANL), Argonne, IL (United States)
Sponsoring Org.:
USDOE Office of Electricity Delivery and Energy Reliability (OE)
OSTI Identifier:
1415481
Grant/Contract Number:  
AC02-06CH11357
Resource Type:
Journal Article: Accepted Manuscript
Journal Name:
IEEE Transactions on Smart Grid
Additional Journal Information:
Journal Volume: 8; Journal Issue: 6; Journal ID: ISSN 1949-3053
Publisher:
IEEE
Country of Publication:
United States
Language:
English
Subject:
24 POWER TRANSMISSION AND DISTRIBUTION; electric power systems; Distributed optimization; online optimization

Citation Formats

Molzahn, Daniel K., Dorfler, Florian K., Sandberg, Henrik, Low, Steven H., Chakrabarti, Sambuddha, Baldick, Ross, and Lavaei, Javad. A Survey of Distributed Optimization and Control Algorithms for Electric Power Systems. United States: N. p., 2017. Web. doi:10.1109/TSG.2017.2720471.
Molzahn, Daniel K., Dorfler, Florian K., Sandberg, Henrik, Low, Steven H., Chakrabarti, Sambuddha, Baldick, Ross, & Lavaei, Javad. A Survey of Distributed Optimization and Control Algorithms for Electric Power Systems. United States. doi:10.1109/TSG.2017.2720471.
Molzahn, Daniel K., Dorfler, Florian K., Sandberg, Henrik, Low, Steven H., Chakrabarti, Sambuddha, Baldick, Ross, and Lavaei, Javad. Tue . "A Survey of Distributed Optimization and Control Algorithms for Electric Power Systems". United States. doi:10.1109/TSG.2017.2720471. https://www.osti.gov/servlets/purl/1415481.
@article{osti_1415481,
title = {A Survey of Distributed Optimization and Control Algorithms for Electric Power Systems},
author = {Molzahn, Daniel K. and Dorfler, Florian K. and Sandberg, Henrik and Low, Steven H. and Chakrabarti, Sambuddha and Baldick, Ross and Lavaei, Javad},
abstractNote = {Historically, centrally computed algorithms have been the primary means of power system optimization and control. With increasing penetrations of distributed energy resources requiring optimization and control of power systems with many controllable devices, distributed algorithms have been the subject of significant research interest. Here, this paper surveys the literature of distributed algorithms with applications to optimization and control of power systems. In particular, this paper reviews distributed algorithms for offline solution of optimal power flow (OPF) problems as well as online algorithms for real-time solution of OPF, optimal frequency control, optimal voltage control, and optimal wide-area control problems.},
doi = {10.1109/TSG.2017.2720471},
journal = {IEEE Transactions on Smart Grid},
number = 6,
volume = 8,
place = {United States},
year = {Tue Jul 25 00:00:00 EDT 2017},
month = {Tue Jul 25 00:00:00 EDT 2017}
}

Journal Article:
Free Publicly Available Full Text
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Cited by: 10 works
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