Abstract
Congestion is one of the major system risks for transmission system operators. At the same time, topological remedial actions still represent a largely unexploited form of non-costly exibility due to the combinatorial explosion in the number of possible actions. The GridOptions Tool recommends to operators topological remedial actions to mitigate congestion in the day-ahead/intraday timeframe. The underlying optimization approach is based on two pillars: (i) very fast load ow computations enable screening of the full set of relevant topologies, and (ii) multi-objective quality-diversity optimization enables the generation of a set of strategies which satisfy different trade-offs between various objectives and are behaviourally diverse. The considered objectives are related to both physical security constraints and the complexity of the strategies. As a result, the tool generates topological strategies that are a signi cant improvement compared to both the situation in which no topological remedial actions are applied and the known operator strategies. Moreover, the GridOptions Tool offers a simple user interface which is developed in interaction with operators to satisfy their cognitive needs. Finally, the GridOptions Tool is largely based on open-source tooling, and all components can run as a Docker container on a Kubernetes platform.
| Original language | English |
|---|---|
| Number of pages | 15 |
| Journal | CIGRE Science and Engineering |
| Volume | 2024-December |
| Issue number | 35 |
| Publication status | Published - 2024 |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 7 Affordable and Clean Energy
Keywords
- Arti cial Intelligence
- Congestion Management
- DC Load Flow
- Decision Support
- Human-Machine Interface
- Multi-Objective Quality-Diversity Optimization
- Topological Remedial Actions
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