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欧洲电力交易中AI的受治理架构

文章 arXiv papers · 作者: Walter Kurz et al.
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总结

本文介绍欧洲电力市场中由AI支持的交易功能设计。文章将远期、日前、日内和平衡市场视为相互关联的层级，这些层级受监管、交易所规则、市场耦合、跨境输电限制和电网物理规律共同影响。提议的规范包括决策状态表示、剩余敞口核算、约束优化、许可操作门控，以及带可审计记录的故障关闭控制。

分析梳理了主要指定电力市场运营商的交易场所，并指出接口时序、权限差异及与平衡市场的连接所带来的操作摩擦。文章的主要观点是，应将AI纳入有边界、受治理的决策流程，而非依赖不受约束的预测。本文提供架构和操作分析，没有实测交易表现证据或经过验证的实现。因此，其适用性取决于具体市场规则、交易场所接口和监管义务。

核心观点

  • 欧洲电力交易的多个期限受到共同的电网和监管约束。
  • AI交易系统可通过明确状态、敞口核算和约束目标来定义。
  • 操作许可门控和故障关闭控制可限制自动化决策的范围。
  • 交易场所时序、权限不一致和平衡市场连接可能妨碍跨境协调。
  • 所提框架是架构规范，不是已验证的表现结果。

标签

大宗商品机器学习风险管理交易执行市场微观结构
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# Functional Architecture of European Electricity Trading Markets: Requirements for AI Supported Trading Systems under Regulatory Constraints









European electricity trading in the EU operates as a constrained multi-layer system in which legal design, exchange microstructure, and network physics are executed jointly across forward, day-ahead, intraday, and balancing horizons. This paper develops a functional architecture for AI-supported trading that is aligned with market-coupling mechanics, cross-zonal transfer constraints, and compliance obligations under REMIT, MiFID II, MiFIR, and EMIR. The contribution is a formal system specification composed of a decision-state vector, residual-exposure accounting, constrained optimization objective, executable-action permission gate, and fail-closed AI control logic with auditable records. The analysis maps major Nominated Electricity Market Operator (NEMO) venues and related exchange operators into an operational venue topology and identifies where cross-border coordination fails in practice: interface-level timing, permission heterogeneity, and balancing-layer coupling. The resulting framework proposes how AI can be deployed as a bounded decision component inside regulated market operation with explicit governance, rather than as an unconstrained prediction layer.

在遵守原作品许可的前提下，附作者信息全文展示。 许可协议: abstract CC0

此摘要由 Stratmill 研究智能体根据原文撰写，并非原文副本。