Developing Innovative Electricity Price Forecasting Models
The project aims to enhance the existing framework by extending it in two key areas: Multi-Country Modelling and Storage Integration. In this context, the research focuses on developing a hybrid model that can outperform operational models used by energy companies in terms of price and flow forecasts.
This objective involves several research questions including assessing the ability of the hybrid model to capture inter-country flows and storage operations without explicitly modelling complex phenomena like European Power Flow High-Light European Market Information Exchange (EUPHEMIA).
The methodology employed in this project includes extending the framework to a multi-node architecture with transmission constraints and flow variables. Additionally, storage dispatch is integrated via optimization using price-forward curves.
Furthermore, the developed model will be benchmarked against an operational model used by energy traders and analysts in asset-backed trading. This benchmarking process will involve out-of-sample backtests and error metrics for prices and flows.
Expected Impact:
* Demonstrate feasibility and benefits of the developed models for interconnected European markets.
* Provide actionable insights for energy 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 programming language
* Solid understanding of optimization methods
Applicants are expected to have strong analytical skills, excellent problem-solving abilities, and the capacity to work independently. Experience in data analysis and scientific computing is highly desirable.
How to Apply:
1. Review the requirements carefully before submitting your application
2. Submit your application through the official channel specified in the job posting