Scalable Heuristics for Planning, Placement and Sizing of Flexible AC Transmission System Devices
Abstract
Aiming to relieve transmission grid congestion and improve or extend feasibility domain of the operations, we build optimization heuristics, generalizing standard AC Optimal Power Flow (OPF), for placement and sizing of Flexible Alternating Current Transmission System (FACTS) devices of the Series Compensation (SC) and Static VAR Compensation (SVC) type. One use of these devices is in resolving the case when the AC OPF solution does not exist because of congestion. Another application is developing a long-term investment strategy for placement and sizing of the SC and SVC devices to reduce operational cost and improve power system operation. SC and SVC devices are represented by modification of the transmission line inductances and reactive power nodal corrections respectively. We find one placement and sizing of FACTs devices for multiple scenarios and optimal settings for each scenario simultaneously. Our solution of the nonlinear and nonconvex generalized AC-OPF consists of building a convergent sequence of convex optimizations containing only linear constraints and shows good computational scaling to larger systems. The approach is illustrated on single- and multi-scenario examples of the Matpower case-30 model.
- Authors:
-
- Skolkovo Institute of Science and Technology, Skolkovo (Russia)
- Los Alamos National Lab. (LANL), Los Alamos, NM (United States)
- Publication Date:
- Research Org.:
- Los Alamos National Laboratory (LANL), Los Alamos, NM (United States)
- Sponsoring Org.:
- USDOE
- OSTI Identifier:
- 1191123
- Report Number(s):
- LA-UR-15-24981
- DOE Contract Number:
- AC52-06NA25396
- Resource Type:
- Technical Report
- Country of Publication:
- United States
- Language:
- English
- Subject:
- Power Transmission & Distribution(24); Energy Sciences
Citation Formats
Frolov, Vladmir, Backhaus, Scott N., and Chertkov, Michael. Scalable Heuristics for Planning, Placement and Sizing of Flexible AC Transmission System Devices. United States: N. p., 2015.
Web. doi:10.2172/1191123.
Frolov, Vladmir, Backhaus, Scott N., & Chertkov, Michael. Scalable Heuristics for Planning, Placement and Sizing of Flexible AC Transmission System Devices. United States. https://doi.org/10.2172/1191123
Frolov, Vladmir, Backhaus, Scott N., and Chertkov, Michael. 2015.
"Scalable Heuristics for Planning, Placement and Sizing of Flexible AC Transmission System Devices". United States. https://doi.org/10.2172/1191123. https://www.osti.gov/servlets/purl/1191123.
@article{osti_1191123,
title = {Scalable Heuristics for Planning, Placement and Sizing of Flexible AC Transmission System Devices},
author = {Frolov, Vladmir and Backhaus, Scott N. and Chertkov, Michael},
abstractNote = {Aiming to relieve transmission grid congestion and improve or extend feasibility domain of the operations, we build optimization heuristics, generalizing standard AC Optimal Power Flow (OPF), for placement and sizing of Flexible Alternating Current Transmission System (FACTS) devices of the Series Compensation (SC) and Static VAR Compensation (SVC) type. One use of these devices is in resolving the case when the AC OPF solution does not exist because of congestion. Another application is developing a long-term investment strategy for placement and sizing of the SC and SVC devices to reduce operational cost and improve power system operation. SC and SVC devices are represented by modification of the transmission line inductances and reactive power nodal corrections respectively. We find one placement and sizing of FACTs devices for multiple scenarios and optimal settings for each scenario simultaneously. Our solution of the nonlinear and nonconvex generalized AC-OPF consists of building a convergent sequence of convex optimizations containing only linear constraints and shows good computational scaling to larger systems. The approach is illustrated on single- and multi-scenario examples of the Matpower case-30 model.},
doi = {10.2172/1191123},
url = {https://www.osti.gov/biblio/1191123},
journal = {},
number = ,
volume = ,
place = {United States},
year = {Thu Jul 02 00:00:00 EDT 2015},
month = {Thu Jul 02 00:00:00 EDT 2015}
}