Adequacy of time-series reduction for renewable energy systems
| Autor: | Leonard Göke, Mario Kendziorski |
|---|---|
| Jazyk: | angličtina |
| Rok vydání: | 2021 |
| Předmět: |
Mathematical optimization
General Economics (econ.GN) Computational complexity theory Computer science 020209 energy 02 engineering and technology 7. Clean energy Industrial and Manufacturing Engineering Reduction (complexity) FOS: Economics and business 0202 electrical engineering electronic engineering information engineering Electrical and Electronic Engineering Civil and Structural Engineering Economics - General Economics Sequence Series (mathematics) business.industry Mechanical Engineering Building and Construction 021001 nanoscience & nanotechnology Pollution Renewable energy General Energy Renewable energy system Positive bias 0210 nano-technology business |
| Popis: | To reduce computational complexity, macro-energy system models commonly implement reduced time-series data. For renewable energy systems dependent on seasonal storage and characterized by intermittent renewables, like wind and solar, adequacy of time-series reduction is in question. Using a capacity expansion model, we evaluate different methods for creating and implementing reduced time-series regarding loss of load and system costs. Results show that adequacy greatly depends on the length of the reduced time-series and how it is implemented into the model. Implementation as a chronological sequence with re-scaled time-steps prevents loss of load best but imposes a positive bias on seasonal storage resulting in an overestimation of system costs. Compared to chronological sequences, grouped periods require more time so solve for the same number of time-steps, because the approach requires additional variables and constraints. Overall, results suggest further efforts to improve time-series reduction and other methods for reducing computational complexity. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
|