An autopilot for energy models – Automatic generation of renewable supply curves, hourly capacity factors and hourly synthetic electricity demand for arbitrary world regions
| Autor: | Vilhelm Verendel, Niclas Mattsson, Fredrik Hedenus, Lina Reichenberg |
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| Rok vydání: | 2021 |
| Předmět: |
Renewable energy
Physics - Physics and Society Geospatial analysis Computer science 020209 energy FOS: Physical sciences Energy system modelling Physics and Society (physics.soc-ph) 02 engineering and technology 010501 environmental sciences lcsh:HD9502-9502.5 computer.software_genre 01 natural sciences Concentrated solar power 0202 electrical engineering electronic engineering information engineering Hydropower 0105 earth and related environmental sciences Wind power business.industry Photovoltaic system GIS Solar energy Industrial engineering lcsh:Energy industries. Energy policy. Fuel trade Offshore wind power business computer Energy (miscellaneous) |
| Zdroj: | Energy Strategy Reviews, Vol 33, Iss, Pp 100606-(2021) |
| ISSN: | 2211-467X |
| DOI: | 10.1016/j.esr.2020.100606 |
| Popis: | Energy system models are increasingly being used to explore scenarios with large shares of variable renewables. This requires input data of high spatial and temporal resolution and places a considerable preprocessing burden on the modeling team. Here we present a new code set with an open source license for automatic generation of input data for large-scale energy system models for arbitrary regions of the world, including sub-national regions, along with an associated generic capacity expansion model of the electricity system. We use ECMWF ERA5 global reanalysis data along with other public geospatial datasets to generate detailed supply curves and hourly capacity factors for solar photovoltaic power, concentrated solar power, onshore and offshore wind power, and existing and future hydropower. Further, we use a machine learning approach to generate synthetic hourly electricity demand series that describe current demand, which we extend to future years using regional SSP scenarios. Finally, our code set automatically generates costs and losses for HVDC interconnections between neighboring regions. The usefulness of our approach is demonstrated by several different case studies based on input data generated by our code. We show that our model runs of a future European electricity system with high share of renewables are in line with results from more detailed models, despite our use of global datasets and synthetic demand. 23 pages, 8 figures, 1 table, submitted to Energy Strategy Reviews |
| Databáze: | OpenAIRE |
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