The missing money problem, linear programming, power system and electricity market operations, introduction to math programming languages, economic dispatch, capacity expansion, beyond electricity (natural gas, oil, biofuels, non-renewable resources), risk management
- Teacher: Παντελής Κάπρος
- Teacher: Αντώνης Παπαβασιλείου
ECTS : 4
Study Load : theory 3, lab 0
Language : el, en
Learning Outcomes : Knowledge & Understanding
By the end of the course, students will be able to:
1. Describe the fundamental economic principles governing electricity markets, including scarcity pricing, the “missing money” problem, and market failures in energy systems
2. Explain how linear programming is used in energy systems modeling and how mathematical programming tools such as AMPL, Python, and Julia support optimization in energy applications
3. Discuss the operation of power systems and electricity markets
4. Identify the main drivers, constraints, and methodologies behind generation capacity expansion models and sectors beyond electricity (e.g., gas, coal, non-renewable resources)
5. Recognize key concepts in risk management for energy markets, including hedging, derivatives and financial risk measures
Application & Analysis
Students completing the course will be able to:
6. Formulate energy system optimization problems (e.g., dispatch, capacity expansion) as linear programming models or complementarity problems using AMPL or Python/Julia
7. Analyze how economic dispatch decisions are derived from marginal cost principles and how they affect market clearing and pricing
8. Evaluate long-term investment decisions under uncertainty using capacity expansion frameworks and scenario-based modeling
9. Apply risk management tools to assess and mitigate the financial exposure of energy producers, consumers, or market operators
10. Examine the implications of market power, imperfect competition, and regulatory interventions on energy market outcomes
Synthesis & Evaluation
Upon successful completion, students will be able to:
11. Integrate technical, economic, and regulatory aspects to evaluate real-world energy market designs and propose improvements.
12. Construct complete optimization-based analyses for energy problems, including model formulation and interpretation of results in policy and market contexts
13. Develop, document, and present a fully realized energy economics project using modeling tools and quantitative methods, communicating both methodology and conclusions effectively during project presentations