1693. Exploring near-optimal-solutions of energy system models to increase energy system resilience
Invited abstract in session MC-44: Multi-criteria energy systems modelling, stream Energy Economics & Management.
Monday, 12:30-14:00Room: Newlyn 1.01
Authors (first author is the speaker)
| 1. | Tino Mitzinger
|
| Resilient Energy Systems, University of Bremen |
Abstract
A comparative assessment of the resilience of different future energy concepts is crucial to provide a basis for decision-making and to identify reliable transition paths. To address the question of improving the resilience of energy systems under near cost-optimal conditions, a methodology has been developed. The initially step entailed the optimization of the heat supply for an urban district. The immediate vicinity of the optimal solution was then examined in order to localize near-optimal alternatives. Therefore, the Modeling to Generate Alternative (MGA) optimization approach was used.
These near-optimal solutions were then analysed in terms of diversity, redundancy and buffer capacity in order to identify more resilient system configurations. The methodology was applied to a linear optimization model based on the Open Energy Modelling Framework (oemof).
The analysis of the heat supply scenarios has shown that resilience, measured by the indicators used, could be increased at a low additional cost (diversity by 37%, redundancy by 6%, and buffer capacity by 160%).
In conclusion, this research employs a methodology that provides a comprehensive framework for optimizing future energy systems based on multiple criteria. The integration of resilience considerations in the decision-making process ensures that energy systems become not only cost-efficient but also reliable in the face of unpredictable challenges.
Keywords
- Optimization Modeling
- Risk Analysis and Management
Status: accepted
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