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Error Bounds on Power Flow Linearizations: A Convex Relaxation Approach Molzahn, Daniel
Description
The power flow equations model the relationship between the voltages phasors and power flows in an electric power system. The nonlinearity of the power flow equations results in algorithmic and theoretical challenges, including non-convex feasible spaces for optimization problems constrained by these equations. Accordingly, many practical approaches for solving power system optimization and control problems employ linearizations of the power flow equations. By leveraging developments in convex relaxation techniques, this presentation describes recent progress regarding a method for bounding the worst-case errors resulting from power flow linearizations. Specifically, with a focus on the DC power flow approximation, this presentation characterizes the worst-case error in the line flows over a specified range of operational conditions.
Item Metadata
Title |
Error Bounds on Power Flow Linearizations: A Convex Relaxation Approach
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Creator | |
Publisher |
Banff International Research Station for Mathematical Innovation and Discovery
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Date Issued |
2017-03-07T10:10
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Description |
The power flow equations model the relationship between the voltages phasors and power flows in an electric power system. The nonlinearity of the power flow equations results in algorithmic and theoretical challenges, including non-convex feasible spaces for optimization problems constrained by these equations. Accordingly, many practical approaches for solving power system optimization and control problems employ linearizations of the power flow equations. By leveraging developments in convex relaxation techniques, this presentation describes recent progress regarding a method for bounding the worst-case errors resulting from power flow linearizations. Specifically, with a focus on the DC power flow approximation, this presentation characterizes the worst-case error in the line flows over a specified range of operational conditions.
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Extent |
30 minutes
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Subject | |
Type | |
File Format |
video/mp4
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Language |
eng
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Notes |
Author affiliation: Argonne National Laboratory
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Series | |
Date Available |
2017-09-04
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Provider |
Vancouver : University of British Columbia Library
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Rights |
Attribution-NonCommercial-NoDerivatives 4.0 International
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DOI |
10.14288/1.0355386
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URI | |
Affiliation | |
Peer Review Status |
Unreviewed
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Scholarly Level |
Other
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Rights URI | |
Aggregated Source Repository |
DSpace
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Item Media
Item Citations and Data
Rights
Attribution-NonCommercial-NoDerivatives 4.0 International