Network and Market Analysis of potential Grid Investments in the European Single Day-Ahead Flow-Based Market Coupling

Core region successfully went live on June 8th, 2022 for delivery on June 9th, 2022. The Core

Capacity Calculation Region (Core CCR) with 14 bidding zones consists of 16 Transmission

System Operators (TSOs) and 11 Nominated Electricity Market Operators (NEMOs) from

Central Europe: Austria (AT), Belgium (BE), Croatia (HR), the Czech Republic (CZ), France

(FR), Germany (DE), Hungary (HU), Luxemburg (LU), the Netherlands (NL), Poland (PL),

Romania (RO), Slovakia (SK) and Slovenia (SI). The exchange of energy between bidding zones is limited by network constraints. The flow-based (FB) method [2] introduces a completely new approach with the coordinated capacity calculation, in accordance with Article 20.2 of the CACM Regulation.

1 From the go-live of the first operational business day, the Single Day-Ahead Market Coupling

(SDAC) bidding zone prices in the Core CCR have shown great volatility during certain periods of the years. The coupling is achieved by the EUPHEMIA (Pan-European Hybrid Electricity

Market Integration Algorithm) algorithm which optimizes the maximization of European socioeconomic welfare. The constraints imposed in the EUPHEMIA algorithm are categorized into two groups – i.e. market constraints and network constraints. The physical description of the network constraints is the Critical Network Element with Contingency (CNECs) defined by each TSO as an input for the coordinated flow-based capacity calculation process.

Our present paper for 2026 PARIS SESSION aims to focus primarily on the network analysis aspect of the grid investments presented in previous paper [3][4]. Potential grid investments in the region of Austria (AT), Slovakia (SK) and Hungary (HU) have been analysed to understand what effect they have on the prices of the Hungarian and neighbouring bidding zones. In addition to the market aspect, it is important to ascertain how the network constraints from the perspective of the calculated transmission capacity are affected by these grid investments. The performed scenario-based case study shows that reinforcing the grid in the area of the most impacting active network constraints with their shadow prices attains the objective of reducing the prices in the Hungarian bidding zone and its surrounding region. The idea is to see how these grid investments influence load-flow results as well as the flow-based parameters such as

PTDF and RAM on these network constraints. The capacity recalculation and market simulation have been performed by employing the computation module and the market coupling algorithm identical to the production system. This network analysis helps to gain a real insight into the added value of various grid investment options in order to find the optimal solution from the perspective of both calculated capacity and cost effectiveness. The added value of this approach is to promote a deeper context of considering the whole flow-based capacity calculation method during a decision-making process. Thus, the paper focuses on 2 sections: (i) the network analysis and (ii) the market analysis. While the overall cost effectiveness of each grid reinforcement is also crucial from the perspective of decision-making process, this aspect is not part of the content of this paper. Such analysis would require a yearly computation for each scenario.