Prototypical warm-starts for demand-robust LP-based energy system optimization
Please always quote using this URN: urn:nbn:de:0297-zib-101242
- The expressiveness of energy system optimization models (ESOMs) depends on a multitude of exogenous parameters. For example, sound estimates of the future energy demand are essential to enable qualified decisions on long-term investments. However, the enormous demand fluctuations even on a fine-grained scale diminish the computational performance of large-scale ESOMs. We therefore propose a clustering-and-decomposition method for linear programming based ESOMs that first identifies and solves prototypical demand scenarios with the dual simplex algorithm, and then composes dual optimal prototype bases to a warm-start basis for the full model. We evaluate the feasibility and computational efficiency our approach on a real-world case study, using a sector-coupled ESOM with hourly resolution for the Berlin-Brandenburg area in Germany, based on the oemof framework.
| Author: | Lukas Mehl, Niels LindnerORCiD, Karolina Bartoszuk, Janina ZittelORCiD |
|---|---|
| Document Type: | ZIB-Report |
| MSC-Classification: | 90-XX OPERATIONS RESEARCH, MATHEMATICAL PROGRAMMING |
| CCS-Classification: | J. Computer Applications |
| Date of first Publication: | 2025/08/25 |
| Series (Serial Number): | ZIB-Report (25-15) |
| ISSN: | 1438-0064 |

