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| Detailed information |
| Original study plan |
Master's programme Digital Energy Solutions 2026W |
| Learning Outcomes |
Competences |
| Students can analyze, design, and evaluate digital trading solutions for modern energy markets. They understand the mechanisms of day-ahead, intraday, and balancing markets and are able to apply data-driven methods such as forecasting models, analytics, and algorithmic trading strategies. They can assess digital infrastructures, system architectures, and blockchain-based approaches for energy trading, as well as apply portfolio optimization and risk management techniques. Students are able to evaluate case studies and design innovative energy trading systems that integrate renewable generation, storage, and demand flexibility.
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| Skills |
Knowledge |
- Understand the structure and mechanisms of day-ahead, intraday, and balancing markets (K5)
- Analyze digital infrastructures and system architectures that support energy trading (K5)
- Apply forecasting models and analytics for trading decisions in renewable, storage, and demand flexibility contexts (K6)
- Understand and implement algorithmic trading strategies for automated market participation (K6)
- Evaluate the role of digital platforms and blockchain-based approaches in enabling secure and transparent energy trading (K5)
- Apply portfolio optimization methods to balance risks and returns in energy trading (K5)
- Understand and evaluate risk management concepts in trading operations (K5)
- Analyze and assess case studies of digital energy trading solutions for their applicability in practice (K6)
- Position trading solutions with respect to market efficiency, integration of renewables, and regulatory compliance (K5)
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- Trading mechanisms in day-ahead, intraday, and balancing markets
- Digital infrastructures and system architectures for trading
- Data-driven solutions:
- Forecasting models
- Analytics
- Algorithmic trading strategies
- Integration of renewable generation, storage, and demand flexibility
- Digital platforms and blockchain-based approaches for energy trading
- Portfolio optimization methods
- Risk management in energy trading
- Case studies of innovative trading systems
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| Criteria for evaluation |
Final exam
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| Methods |
Lecture, discussion, course material, exercise examples
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| Language |
English |
| Study material |
Course materials (presentation slides) are made available via Moodle
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| Changing subject? |
No |
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