2140. Applying regularized Benders decomposition to efficiently optimize power grid expansion in large-scale energy system models
Invited abstract in session MD-55: Network Optimization 4, stream Network Optimization.
Monday, 14:30-16:00Room: Liberty 1.09
Authors (first author is the speaker)
| 1. | Lene Marie Grübler
|
| Department of Strategic Grid Planning / Chair of Energy Economics, 50Hertz Transmission GmbH / BTU Cottbus-Senftenberg | |
| 2. | Felix Muesgens
|
| Chair of Energy Economics, BTU Cottbus-Senftenberg |
Abstract
Decarbonizing the European economy requires a substantial increase in renewable energy generation capacities across the continent. As their capacity factors are time and site dependent, the importance of transmission grid expansion on national and international scale rises. Grid expansion projects rely on standardized components. In capacity expansion models of energy systems, investments in grid expansion projects therefore require binary investment decision variables, resulting in complex mixed-integer optimization models to be solved. Complexity of such expansion models is additionally driven by a high number of linking variables on the temporal and spatial scale. To keep such problems computationally tractable and efficiently solvable, we apply regularized Benders decomposition and implement different strategies to handle binary decision variables. Furthermore we explore different variants of modelling operating constraints of power grids by means of optimal power flow constraints and analyze their impact on solving times and solution quality.
Keywords
- OR in Energy
- Network Design
- Programming, Mixed-Integer
Status: accepted
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