Comparison of SpineOpt and PyPSA in Hydro Power System Modelling
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| Title: | Comparison of SpineOpt and PyPSA in Hydro Power System Modelling |
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| Authors: | Yi Liu, Mikael Amelin, Topi Rasku |
| Source: | 2024 20th International Conference on the European Energy Market (EEM). :1-6 |
| Publisher Information: | IEEE, 2024. |
| Publication Year: | 2024 |
| Subject Terms: | PyPSA, Other Electrical Engineering, Electronic Engineering, Information Engineering, 0211 other engineering and technologies, 02 engineering and technology, Linear optimization, 7. Clean energy, SpineOpt, 0202 electrical engineering, electronic engineering, information engineering, Annan elektroteknik och elektronik, SDG 7 - Affordable and Clean Energy, Hydro power modelling, Energy Systems, Open-source tools, Energisystem |
| Description: | Hydro power modelling is important to facilitate the integration of large amounts of variable renewable energy. However, appropriately modelling hydro power presents challenges due to its interconnections with both electricity and river systems. The aim of this paper is to investigate the performance of two selected open-source energy modelling tools for hydro power planning, SpineOpt and PyPSA, with a focus on user-friendliness, accuracy and execution time. In this study, a small river system with two hydro power plants is modelled to maximize the revenue using both tools. At the same time, this linear optimization problem is implemented by Gurobi directly, such that results and execution times from SpineOpt and PyPSA are compared with this baseline. In conclusion, both open-source tools can appropriately model the hydro power system, with SpineOpt having a unique graphical interface and PyPSA has a good performance in execution speed. |
| Document Type: | Article Conference object |
| File Description: | application/pdf |
| DOI: | 10.1109/eem60825.2024.10608896 |
| Access URL: | https://cris.vtt.fi/en/publications/8dff2420-28b4-4bcb-99ca-ac9f92e84404 https://doi.org/10.1109/EEM60825.2024.10608896 http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-352374 |
| Rights: | STM Policy #29 |
| Accession Number: | edsair.doi.dedup.....81f7a05c6e915398950d4e5fdedd7455 |
| Database: | OpenAIRE |
Nájsť tento článok vo Web of Science | Abstract: | Hydro power modelling is important to facilitate the integration of large amounts of variable renewable energy. However, appropriately modelling hydro power presents challenges due to its interconnections with both electricity and river systems. The aim of this paper is to investigate the performance of two selected open-source energy modelling tools for hydro power planning, SpineOpt and PyPSA, with a focus on user-friendliness, accuracy and execution time. In this study, a small river system with two hydro power plants is modelled to maximize the revenue using both tools. At the same time, this linear optimization problem is implemented by Gurobi directly, such that results and execution times from SpineOpt and PyPSA are compared with this baseline. In conclusion, both open-source tools can appropriately model the hydro power system, with SpineOpt having a unique graphical interface and PyPSA has a good performance in execution speed. |
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| DOI: | 10.1109/eem60825.2024.10608896 |