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2909. Modeling long-term energy transition pathways: Algorithmic approaches and their properties
Invited abstract in session TD-9: Long-term energy system planning, stream Energy Markets.
Tuesday, 14:30-16:00Room: 10 (building: 116)
Authors (first author is the speaker)
| 1. | Stefan Strömer
|
| Center of Energy - Integrated Energy Systems & Technology, Policy and Management, AIT Austrian Institute of Technology GmbH & Delft University of Technology | |
| 2. | Kenneth Bruninx
|
| TU Delft | |
| 3. | Stefan Pfenninger
|
| TU Delft |
Abstract
Recently, challenges related to climate change have increased the need for ever more complex energy system models, covering more sectors, more technological detail, as well as high spatial and temporal resolution. Furthermore, step-wise decarbonisation goals (e.g., for the heat sector) may require contradictory system designs for different future years. Similarly, anticipated, but only slowly implemented, developments of the hydrogen system may necessitate certain transition technologies. With the inherent risks for lock-in effects or stranded assets, the timing of infrastructure investment decisions has increasingly gained importance. Current energy system models often focus either on designing this sector-coupled energy system in great detail, lacking knowledge of the pathway to achieve it, or on designing pathways to a decarbonised energy system, lacking a detailed consideration of the system's operation.
We give an overview of algorithms that help depict complex transition paths together with high operational details, e.g., adaptive temporal resolutions and ways to account for seasonal storage, classical decomposition algorithms (e.g., Benders), closely related algorithms such as stochastic dual dynamic programming (including extensions), as well as approaches based on simulation. We further discuss requirements and features, potential (dis)advantages, and present test cases to illustrate how these algorithms can be applied to a wide range of energy system models.
Keywords
- OR in Energy
- Energy Policy and Planning
- Large Scale Optimization
Status: accepted
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