Modelling of highly dynamic generation profiles for wind and PV parks based on regional reanalysis and stochastic models
Gandini Figueroa, Octavio · RI ITBA · 2026
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The transition to renewable energy sources is reshaping energy systems globally. Germany is a leading example of this shift, having significantly increased its renewable energies (RE) generation in recent years, particularly wind and photovoltaic (PV). However, integrating RE into the grid presents unique challenges due to their unpredictable dynamic generation and decentral installation.
Accurate analysis of RE integration requires high-resolution meteorological data at generation sites, which is often unavailable. Current sources include historical weather data from reanalysis weather models, which provide a maximum temporal resolution of 15 minutes and only mean and maximum parameters that fail to capture the dynamic nature of real weather conditions. Alternatively, stochastic models generate high-resolution profiles based on reference scenarios and incorporate necessary dynamics, but they do not reflect historical conditions.
This master’s thesis proposes a methodology to generate realistic high-resolution generation profiles by interfacing low-resolution reanalysis weather models with existing stochastic models through a parameter translation. In a subsequent step, realistic generation is simulated using simplified but dynamic models for PV and wind turbines, tailored to the specific generation sites. The reanalysis model used (CERRA), covering Europe at a 5x5 km resolution, combined with data from the official German register of energy system units (Markstammdatenregister), allows the modeling of generic German RE generation sites with realistic dynamic generation profiles.
The methodology is applied to an exemplary PV and wind park, revealing distinct dynamic behaviors under various weather conditions. For the wind farm, high-resolution profiles can result in generation losses compared to low-resolution profiles due to dynamic changes that prevented the generator from tracking the optimal operation point. Conversely, gains were observed in scenarios benefiting from the cubic relationship between wind speed and power. For PV the occurrence of clipping effects is demonstrated. Finally, in a case study the implementation of a battery energy storage system (BESS) with a wind turbine and a conventional gas power plant is analysed, showcasing the difference it makes when dynamic generation profiles are used to study the efficiency of energy storage systems.
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APA 7
Gandini Figueroa, O. (2026). Modelling of highly dynamic generation profiles for wind and PV parks based on regional reanalysis and stochastic models. RI ITBA. https://hdl.handle.net/20.500.14769/5285
MLA
Gandini Figueroa, Octavio. Modelling of highly dynamic generation profiles for wind and PV parks based on regional reanalysis and stochastic models. RI ITBA, 2026. https://hdl.handle.net/20.500.14769/5285.
Chicago
Gandini Figueroa, Octavio. 2026. Modelling of highly dynamic generation profiles for wind and PV parks based on regional reanalysis and stochastic models. RI ITBA. https://hdl.handle.net/20.500.14769/5285.
Harvard
Gandini Figueroa, O. 2026, Modelling of highly dynamic generation profiles for wind and PV parks based on regional reanalysis and stochastic models, RI ITBA, available at: https://hdl.handle.net/20.500.14769/5285 [Accessed 21 Jun. 2026].
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- Título
- Modelling of highly dynamic generation profiles for wind and PV parks based on regional reanalysis and stochastic models
- Autor / colaboradores
- Gandini Figueroa, Octavio
- Editorial
- RI ITBA
- Año de publicación
- 2026
- Idioma
- es
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