Details
| Original language | English |
|---|---|
| Title of host publication | Proceedings - 2020 International Conference on Smart Grids and Energy Systems, SGES 2020 |
| Place of Publication | Los Alamitos, CA, USA |
| Publisher | IEEE Computer Society |
| Pages | 261-266 |
| Number of pages | 6 |
| ISBN (electronic) | 9781728185507 |
| Publication status | Published - 2020 |
Abstract
In comparison to state of the art relaxation and approximation approaches an enhanced convexificated quadratic approximation for the Security Constrained Optimal Power Flow (SCOPF) is reasoned and derived. The detailed graphic interpretations have a focus on convexity and accuracy. First, variables are divided into different types and nonlinear equality constraints of the SCOPF are eliminated by implementing a distributed slack. Second, the nonconvex parts of the resulting quadratically approximated functions are identified by eigenvalue analysis and convexificated with piecewise linearizations. Additionally new algorithms for fast calculation of the required Hessians are derived.
Keywords
- Convexification, Eigenvalue, Quadratic approximation, Relaxation, Security constrained optimal power flow
ASJC Scopus subject areas
- Computer Science(all)
- Artificial Intelligence
- Energy(all)
- Energy Engineering and Power Technology
- Engineering(all)
- Automotive Engineering
- Engineering(all)
- Electrical and Electronic Engineering
- Mathematics(all)
- Control and Optimization
- Social Sciences(all)
- Transportation
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Proceedings - 2020 International Conference on Smart Grids and Energy Systems, SGES 2020. Los Alamitos, CA, USA: IEEE Computer Society, 2020. p. 261-266 9364447.
Research output: Chapter in book/report/conference proceeding › Conference contribution › Research › peer review
}
TY - GEN
T1 - Detailed reasoning and derivation of a convexificated quadratic approximation approach for the Security Constrained Optimal Power Flow
AU - Leveringhaus, T.
AU - Hofmann, L.
PY - 2020
Y1 - 2020
N2 - In comparison to state of the art relaxation and approximation approaches an enhanced convexificated quadratic approximation for the Security Constrained Optimal Power Flow (SCOPF) is reasoned and derived. The detailed graphic interpretations have a focus on convexity and accuracy. First, variables are divided into different types and nonlinear equality constraints of the SCOPF are eliminated by implementing a distributed slack. Second, the nonconvex parts of the resulting quadratically approximated functions are identified by eigenvalue analysis and convexificated with piecewise linearizations. Additionally new algorithms for fast calculation of the required Hessians are derived.
AB - In comparison to state of the art relaxation and approximation approaches an enhanced convexificated quadratic approximation for the Security Constrained Optimal Power Flow (SCOPF) is reasoned and derived. The detailed graphic interpretations have a focus on convexity and accuracy. First, variables are divided into different types and nonlinear equality constraints of the SCOPF are eliminated by implementing a distributed slack. Second, the nonconvex parts of the resulting quadratically approximated functions are identified by eigenvalue analysis and convexificated with piecewise linearizations. Additionally new algorithms for fast calculation of the required Hessians are derived.
KW - Convexification
KW - Eigenvalue
KW - Quadratic approximation
KW - Relaxation
KW - Security constrained optimal power flow
UR - http://www.scopus.com/inward/record.url?scp=85102746376&partnerID=8YFLogxK
U2 - 10.1109/sges51519.2020.00053
DO - 10.1109/sges51519.2020.00053
M3 - Conference contribution
SP - 261
EP - 266
BT - Proceedings - 2020 International Conference on Smart Grids and Energy Systems, SGES 2020
PB - IEEE Computer Society
CY - Los Alamitos, CA, USA
ER -