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| Detailinformationen |
| Quellcurriculum |
Masterstudium Digital Energy Solutions 2026W |
| Lernergebnisse |
Kompetenzen |
| (*)Students can analyse, design, and evaluate meteorological and climatological data in relation to renewable energy systems according to international and national standards. They understand the physical and statistical fundamentals of atmospheric processes, including air pressure, wind speed, temperature, radiation, aerosols, clouds, and atmospheric dynamics, as well as the timescales of weather-related variability from diurnal to climate-related fluctuations. They are able to select, implement, and monitor statistical analyses, simulation models, and forecasting techniques, apply climate databases and numerical weather prediction tools including downscaling, post-processing, and ensemble approaches, and continuously improve renewable energy yield assessment, planning, and operational strategies while considering uncertainty and limits of predictability.
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| Fertigkeiten |
Kenntnisse |
(*)- Understand the fundamentals and interactions of meteorological variables including air pressure, wind speed, temperature, radiation, atmospheric structure, aerosols, clouds, and atmospheric dynamics (K2)
- Analyse the role of different timescales of weather-related variability, including diurnal, synoptic, seasonal, and climate-related fluctuations, on renewable energy production (K4)
- Understand and apply statistical methods for weather data analysis and interpretation, including trend detection, distribution fitting, and variability assessment (K3)
- Evaluate and simulate weather-related variability for wind, photovoltaic, and solar thermal energy systems using numerical models, Monte Carlo simulations, and scenario analysis (K5)
- Understand the structure and application of climate databases for assessing renewable energy potential worldwide and integrate numerical weather prediction, downscaling, post-processing, and ensemble forecast techniques (K2, K6)
- Analyse and assess the impact of forecast accuracy, predictability limits, and chaos theory on energy system planning and operational decision-making (K4, K5)
- Understand the influence of climatology, climate variability, and long-term trends on renewable energy yield and system reliability (K2)
- Apply principles of integrating meteorological and climatological knowledge into the design, planning, and optimization of renewable energy systems (K3, K6)
- Evaluate and interpret ensemble predictions and probabilistic forecasts to support operational and strategic energy management decisions (K5)
- Understand the state of current knowledge in weather prediction and renewable energy meteorology and apply it to enhance system performance and planning (K2, K6)
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(*)- Meteorological fundamentals: air pressure, wind speed, temperature, radiation, atmospheric structure, aerosols, clouds, and atmospheric dynamics
- Timescales of weather-related variability: diurnal cycles, synoptic systems, seasonal fluctuations, and climate-related variability
- Impact of weather and climate variability on renewable energy production: wind energy, photovoltaic systems, and solar thermal technologies
- Methods for statistical analysis of meteorological data and interpretation of variability patterns
- Simulation techniques for weather-related variability in renewable energy generation scenarios
- Climatology and climate variability: concepts, influencing factors, and current state of scientific knowledge
- Global climate and meteorological databases for assessing renewable energy potentials
- Weather forecasting: historical evolution, state-of-the-art approaches, and prediction accuracy
- Forecasting methods for different temporal and spatial scales, including numerical models and statistical approaches
- Advanced concepts in forecasting: downscaling techniques, post-processing methods, chaos theory, ensemble prediction, and predictability limits
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| Beurteilungskriterien |
(*)Final exam
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| Lehrmethoden |
(*)Lecture, discussion, course material, exercise examples
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| Abhaltungssprache |
Englisch |
| Literatur |
(*)Course materials (presentation slides) are made available via Moodle
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| Lehrinhalte wechselnd? |
Nein |
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