SOWISP—A retrospective high spatial and temporal resolution database of the installed wind and solar PV power in Spain
The proposal of new energy systems based on renewable energies requires thorough research in order to derive technically reliable and economically sustainable systems. One of the key inputs of such research is constituted by reliable databases of renewable resources. Despite the great effort of the...
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| Published in: | Solar energy Vol. 256; pp. 44 - 54 |
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| Main Authors: | , , , |
| Format: | Journal Article |
| Language: | English |
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Elsevier Ltd
15.05.2023
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| ISSN: | 0038-092X, 1471-1257 |
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| Abstract | The proposal of new energy systems based on renewable energies requires thorough research in order to derive technically reliable and economically sustainable systems. One of the key inputs of such research is constituted by reliable databases of renewable resources. Despite the great effort of the scientific community in recent years, most current databases are far from optimal. Although some databases are based on real data, they lack adequate spatial resolution and/or temporal coverage. Other databases are obtained by estimating renewable energy potential from meteorological reanalysis; however, these estimates are subject to high uncertainty. One of the main problems when building these renewable resource databases is the lack of actual values of installed capacity. In this study we present the SOlar and Wind Installed Spanish Power (SOWISP) database. SOWISP provides the actual installed capacity of wind and photovoltaic solar energy in each Spanish town, with a monthly resolution, and covering the period of 2015–2020. SOWISP has been developed and validated based on a careful and thorough compilation of different public databases. It covers the need for a publicly available database with sufficient spatial and temporal resolution suitable for the analysis of energy systems. Moreover, SOWISP, along with other freely available datasets, supports many modern applications. In addition, a Python package (available on GitHub) was developed for managing this database.
•Publicly available database of the wind/solar PV installed power at the Spanish towns.•Information from 59386 solar PV plants and 1205 wind farms are included.•Dataset validation conducted at regional (coarser) scale.•Allows for energy system modeling and regional solar/wind power generation modeling.•Python code for managing the database is publicly available on GitHub. |
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| AbstractList | The proposal of new energy systems based on renewable energies requires thorough research in order to derive technically reliable and economically sustainable systems. One of the key inputs of such research is constituted by reliable databases of renewable resources. Despite the great effort of the scientific community in recent years, most current databases are far from optimal. Although some databases are based on real data, they lack adequate spatial resolution and/or temporal coverage. Other databases are obtained by estimating renewable energy potential from meteorological reanalysis; however, these estimates are subject to high uncertainty. One of the main problems when building these renewable resource databases is the lack of actual values of installed capacity. In this study we present the SOlar and Wind Installed Spanish Power (SOWISP) database. SOWISP provides the actual installed capacity of wind and photovoltaic solar energy in each Spanish town, with a monthly resolution, and covering the period of 2015–2020. SOWISP has been developed and validated based on a careful and thorough compilation of different public databases. It covers the need for a publicly available database with sufficient spatial and temporal resolution suitable for the analysis of energy systems. Moreover, SOWISP, along with other freely available datasets, supports many modern applications. In addition, a Python package (available on GitHub) was developed for managing this database.
•Publicly available database of the wind/solar PV installed power at the Spanish towns.•Information from 59386 solar PV plants and 1205 wind farms are included.•Dataset validation conducted at regional (coarser) scale.•Allows for energy system modeling and regional solar/wind power generation modeling.•Python code for managing the database is publicly available on GitHub. |
| Author | López-Cuesta, Miguel Jiménez-Garrote, Antonio Sánchez-Hernández, Guadalupe Pozo-Vázquez, David |
| Author_xml | – sequence: 1 givenname: Antonio orcidid: 0000-0002-6957-0015 surname: Jiménez-Garrote fullname: Jiménez-Garrote, Antonio – sequence: 2 givenname: Guadalupe orcidid: 0000-0001-6736-8799 surname: Sánchez-Hernández fullname: Sánchez-Hernández, Guadalupe – sequence: 3 givenname: Miguel surname: López-Cuesta fullname: López-Cuesta, Miguel – sequence: 4 givenname: David orcidid: 0000-0002-1135-4926 surname: Pozo-Vázquez fullname: Pozo-Vázquez, David email: dpozo@ujaen.es |
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| Cites_doi | 10.5194/essd-14-2749-2022 10.1016/j.apenergy.2017.08.217 10.1016/j.apenergy.2021.116726 10.1016/j.solener.2019.07.016 10.1002/pip.3126 10.1029/2022EF002673 10.1016/j.apenergy.2018.04.048 10.1016/j.solener.2018.06.107 10.1016/j.renene.2014.03.006 10.1038/s41597-020-00739-0 10.1016/j.rser.2018.08.002 10.1016/j.solener.2020.02.061 10.1016/j.apenergy.2018.11.097 10.1016/j.solener.2021.09.050 10.1016/j.energy.2016.08.068 10.1016/j.solener.2019.11.087 10.1016/j.esr.2018.03.006 10.1016/j.renene.2022.03.041 10.1016/j.rser.2018.03.003 10.1016/j.solener.2021.04.002 10.1016/j.energy.2016.08.060 10.1016/j.solener.2015.07.024 10.1016/j.rser.2022.112348 |
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