Extending Data-Driven Merit Order Models for Multi-Country Electricity Price Forecasting with Flow and Storage Integration
The recent paper by Ghelasi and Ziel proposes a hybrid approach that learns fundamental electricity market parameters from historical data, bridging the gap between classical fundamental models and pure data-driven methods like machine learning. However, its current scope is limited to a single-country market and does not explicitly model cross-border flows or storage operation.
About the thesis:
Objectives
This project aims to extend the existing framework in two key directions:
* Multi-Country Modelling: Include multiple EPEX SPOT SDAC countries; shift from regression-based import/export to implicit flow modelling.
* Storage Integration: Add pumped hydro and other storage as market players; use deterministic/stochastic optimization with a price-forward curve.
Research Questions
* Can the hybrid model outperform Axpo's operational model on price and flow forecasts?
* How accurate can it capture inter-country flows and storage operation without explicitly modelling FBMC like EUPHEMIA?
* What is the value-add of integrated storage optimization for forecast accuracy and realism?
Methodology
* Extend to a multi-node framework with transmission constraints and flow variables.
* Integrate storage dispatch via optimization using price-forward curves.
* Benchmark against Axpo's operational model used in asset-backed trading with out-of-sample backtests and error metrics for prices and flows.
Expected Impact
* Demonstrate feasibility and benefits of the models for interconnected European markets.
* Provide actionable insights for Axpo's traders and analysts on price and flow forecasting.
Your profile:
* Master's student with experience in Energy Markets or a related field (e.g. Engineering, Mathematics, Energy Science, Data Science), enrolled at a Swiss university or university of applied sciences (FH)
* Proficient in Python
* Solid understanding of optimization methods
Starting Date: As soon as possible