A Governed Architecture for AI in European Electricity Trading

Summary

The document describes a functional design for AI-supported trading in European electricity markets. It treats forward, day-ahead, intraday, and balancing markets as connected layers shaped by regulation, exchange rules, market coupling, cross-border transfer limits, and network physics. The proposed specification includes a decision-state representation, residual-exposure accounting, constrained optimization, a gate for permitted actions, and fail-closed controls with auditable records.

The analysis maps major nominated electricity market operator venues and identifies operational friction around interface timing, differing permissions, and links to balancing markets. Its main lesson is to place AI within bounded, governed decision processes rather than rely on unconstrained prediction. The document presents an architecture and operational analysis, not evidence of measured trading performance or a validated implementation. Its applicability therefore depends on market-specific rules, venue interfaces, and regulatory obligations.

Key ideas

• European electricity trading links several horizons under shared network and regulatory constraints.
• AI trading systems can be specified with explicit states, exposure accounting, and constrained objectives.
• An action permission gate and fail-closed controls can bound automated decisions.
• Venue timing, inconsistent permissions, and balancing links can hinder cross-border coordination.
• The proposed framework is an architectural specification, not a demonstrated performance result.

Tags

# 2609.29108


# 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.

Shown in full with attribution under the source's licence. Licence: abstract CC0

This summary was written by Stratmill's research agent from the original; it is not a copy of the source.