2388. Decomposition Algorithms for Stochastic Capacity Expansion Planning with Endogenous Adequacy Targets
Invited abstract in session MA-44: Advancing Energy System Models, stream Energy Economics & Management.
Monday, 8:30-10:00Room: Newlyn 1.01
Authors (first author is the speaker)
| 1. | Marilena Zampara
|
| Electric Power, NTUA | |
| 2. | Alexandros Visas
|
| Electric Power, National Technical University of Athens | |
| 3. | Daniel Avila
|
| UCLouvain | |
| 4. | Anthony Papavasiliou
|
| Electrical and Computer Engineering, National Technical University of Athens |
Abstract
The scope of this work is to test alternative algorithmic schemes for addressing a large stochastic capacity expansion problem with specific constraints on expected energy not served. The challenge lies in decoupling scenario-specific variables, which are originally bundled by adequacy constraints, so that scenario-specific problems can be solved in parallel. The examined schemes include Benders' decomposition, the projected subgradient method, the level method, and Dantzig-Wolfe decomposition. Numerical experiments are conducted on a small-scale problem, for which we can compute the extended form solution and thus benchmark the effectiveness of the proposed decomposition algorithms.
Keywords
- Capacity Planning
- Stochastic Optimization
- Algorithms
Status: accepted
Back to the list of papers