Power Grid Congestion Management via Topology Optimization with AlphaZero
November 10, 2022 Β· Declared Dead Β· π arXiv.org
"No code URL or promise found in abstract"
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Authors
Matthias Dorfer, Anton R. FuxjΓ€ger, Kristian Kozak, Patrick M. Blies, Marcel Wasserer
arXiv ID
2211.05612
Category
cs.AI: Artificial Intelligence
Cross-listed
cs.LG
Citations
25
Venue
arXiv.org
Last Checked
4 months ago
Abstract
The energy sector is facing rapid changes in the transition towards clean renewable sources. However, the growing share of volatile, fluctuating renewable generation such as wind or solar energy has already led to an increase in power grid congestion and network security concerns. Grid operators mitigate these by modifying either generation or demand (redispatching, curtailment, flexible loads). Unfortunately, redispatching of fossil generators leads to excessive grid operation costs and higher emissions, which is in direct opposition to the decarbonization of the energy sector. In this paper, we propose an AlphaZero-based grid topology optimization agent as a non-costly, carbon-free congestion management alternative. Our experimental evaluation confirms the potential of topology optimization for power grid operation, achieves a reduction of the average amount of required redispatching by 60%, and shows the interoperability with traditional congestion management methods. Our approach also ranked 1st in the WCCI 2022 Learning to Run a Power Network (L2RPN) competition. Based on our findings, we identify and discuss open research problems as well as technical challenges for a productive system on a real power grid.
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