528. The application of SDP-based relaxation for the nordic day-ahead energy market
Invited abstract in session MD-11: Applications of conic optimization, stream Conic Optimization.
Monday, 16:30-18:30Room: B100/5017
Authors (first author is the speaker)
| 1. | Shudian Zhao
|
| Department of Mathematics, KTH Royal Institute of Technology | |
| 2. | Jan Kronqvist
|
| Mathematics, KTH Royal Institute of Technology |
Abstract
Social welfare maximization problems in the day-ahead energy market can be formulated as large-scale mixed-integer programming (MIP) problems. These problems are computationally challenging due to the integrality constraints and the high dimensionality introduced by temporal coupling across time periods. Standard linear relaxations often provide weak bounds, limiting the efficiency of branch-and-bound algorithms.
In this talk, we present a semidefinite programming (SDP)-based relaxation approach for these MIP problems. We analyze the modeling power of various classes of valid inequalities and demonstrate, through numerical results, how they contribute to tightening the relaxation and improving computational performance.
Keywords
- Optimization in industry, business and finance
- Conic and semidefinite optimization
Status: accepted
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