SYSYMay 7

Herd Behavior in Decentralized Balancing Models: A Case Study in Belgium

arXiv:2602.1735278.01 citationsh-index: 31
AI Analysis

For TSOs and BRPs, it highlights the risk of overshoots in implicit balancing, which is an incremental insight for grid balancing policy.

This study analyzes the effect of increased participation in Belgium's decentralized balancing model, finding that while implicit balancing initially reduces costs for the TSO, overshoots can outweigh benefits when total capacity is high, yet BRPs still benefit.

In a decentralized balancing model, Balance Responsible Parties (BRPs) are encouraged by the Transmission System Operator (TSO) to deviate from their schedule to help the system restore balance, also referred to as implicit balancing. This could reduce balancing costs for the grid operator and lower the entry barrier for flexible assets compared to explicit balancing services. However, these implicit reactions may overshoot when their total capacity is high, potentially requiring more explicit activations. This study analyses the effect of increased participation in the decentralized balancing model in Belgium. To this end, we develop a market simulator that produces price signals on minute-level and simulate the implicit reactions for battery assets with different risk profiles. Besides the current price formula, we also study two potential candidates for the near-term presented by the TSO. A simulation study is conducted using Belgian market data for the year 2023. The findings indicate that, while having a significant positive effect on the balancing costs at first, the risk of overshoots can outweigh the potential benefits when the total capacity of the implicit reactions becomes too large. Furthermore, even when the balancing costs start to increase for the TSO, BRPs were still found to benefit from implicit balancing.

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