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3170. Hybrid decomposition method for power system planning under uncertainty
Invited abstract in session TD-19: Decomposition techniques applied to energy problems, stream OR in Energy.
Tuesday, 14:30-16:00Room: 44 (building: 116)
Authors (first author is the speaker)
| 1. | Angela Flores
|
| Universidad de Chile |
Abstract
Integrating both short-term flexibility requirements and long-term uncertainty into a unified planning framework results in large-scale multi-stage stochastic mixed-integer programming problems. Consequently, efficient solution methodologies are needed to enable the planning of realistic-size power systems. This work investigates possible ways of combining column generation, lagrangian relaxation, and Benders decomposition in a hybrid decomposition method, aiming to enhance convergence by leveraging the strengths of diverse decomposition techniques. The proposed hybrid decomposition is implemented using distributed computing, allowing parallel initiation of each decomposition approach with the potential for exchanging bounds and solutions. Solutions from Benders decomposition and the bundle method at each iteration can be used to generate new columns for the column generation approach. Likewise, the columns obtained by column generation can be used to derive new cuts for Benders decomposition and the bundle method. The performance of the hybrid decomposition is analyzed through case studies applied to the NREL 118-bus power system.
Keywords
- OR in Energy
- Stochastic Optimization
- Column Generation
Status: accepted
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