The EUPHEMIA algorithm, developed within the Price Coupling of Regions (PCR) project, aims to establish a unified European electricity market. By integrating diverse order types and considering cross-border interconnections, EUPHEMIA fosters price convergence, enhances market transparency, and facilitates efficient energy trading. To demonstrate the algorithm’s flexibility and applicability, this study presents a simplified EUPHEMIA model applied to real-world data from the Iberian, Italian, and Greek electricity markets. The model incorporates hourly order types and network constraints, simulating the day-ahead market. Through rigorous analysis of market clearing prices and traded energy volumes, we evaluate the model’s performance in replicating market dynamics. Additionally, to underscore the flexibility of the developed model, another case study focusing solely on the Iberian market is included to demonstrate the code’s ability to easily adapt to different input data while maintaining efficiency for local markets. Our findings contribute to a deeper understanding of day-ahead market behavior, highlighting the potential of EUPHEMIA as a foundation for advanced market analysis and forecasting tools. To promote further research and development, we plan to release an open-source version of the model, enabling the broader research community to explore its capabilities and contribute to the evolution of electricity market coupling.
Pan-European Electricity Market Integration framework
COLA, DAVIDE
2024/2025
Abstract
The EUPHEMIA algorithm, developed within the Price Coupling of Regions (PCR) project, aims to establish a unified European electricity market. By integrating diverse order types and considering cross-border interconnections, EUPHEMIA fosters price convergence, enhances market transparency, and facilitates efficient energy trading. To demonstrate the algorithm’s flexibility and applicability, this study presents a simplified EUPHEMIA model applied to real-world data from the Iberian, Italian, and Greek electricity markets. The model incorporates hourly order types and network constraints, simulating the day-ahead market. Through rigorous analysis of market clearing prices and traded energy volumes, we evaluate the model’s performance in replicating market dynamics. Additionally, to underscore the flexibility of the developed model, another case study focusing solely on the Iberian market is included to demonstrate the code’s ability to easily adapt to different input data while maintaining efficiency for local markets. Our findings contribute to a deeper understanding of day-ahead market behavior, highlighting the potential of EUPHEMIA as a foundation for advanced market analysis and forecasting tools. To promote further research and development, we plan to release an open-source version of the model, enabling the broader research community to explore its capabilities and contribute to the evolution of electricity market coupling.| File | Dimensione | Formato | |
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https://hdl.handle.net/20.500.12608/90298