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ZENODO
Dataset . 2022
License: CC BY
Data sources: Datacite
image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
ZENODO
Dataset . 2022
License: CC BY
Data sources: ZENODO
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OSMOSE WP1 dataset

Authors: BOURMAUD Jean-Yves; GÖKE Leonard; GRISEY Nathalie; KOSTIC Matija; LHUILLIER Nicolas; ORLIC Dragana; WEIBEZAHN Jens;

OSMOSE WP1 dataset

Abstract

# OSMOSE WP1 DATASET This dataset has been compiled within the OSMOSE project, from the European Union’s Horizon 2020 research and innovation program, to support adequacy studies performed in Work-Package 1. Original data originate from two main sources : Plan4Res EU project and ENTSOE Pan European Common Database. ## Content The dataset contains 35 weather years (1982-2016) of data for 33 EU countries. General data granularity is country level. Some RES data are provided at the granularity of the 99-clusters of the e-Highway2050 project. - non-thermosensitive load profile (1 profile per country). Profiles sum to 1. (Source: Plan4Res and OSMOSE) - electric heating profiles (1 profile per country, 1 file per weather year). Profiles sum to 1 on average but not individually. (Source: Plan4Res and OSMOSE) - electric vehicles profiles (1 profile per country, 1 file per weather year). Profiles sum to slightly more than 1, depending on the weather scenario used. The difference to 1 corresponds to the thermo-sensitive effect due to the heating and the air-conditioning necessary for the well-functioning of the motor and the comfort of the passengers in this weather scenario. Its varies from country to country. (Source : OSMOSE, JRC for daily profiles, CS3 for weather and annual vehicle usage profiles) - onshore wind power-factor profiles (1 profile per country, 1 file per weather year and 1 profile per cluster, 1 file per weather year). (Source: PECD) - offshore wind power-factor profiles (1 profile per country per weather year and 1 profile per cluster per weather year). (Source: PECD) - solar pv power-factor profiles (1 profile per country, 1 file per weather year and 1 profile per cluster, 1 file per weather year). (Source: PECD) - hydro data (installed capacities (Run-of-River - ror, reservoir, Pump Storage Plants - PSP), volumes of the reservoirs and PSP, annual energies (ror and reservoir), per country and per cluster. Source: (OSMOSE based on MAF2018 and MAF2019) - hydro energies in GWh (ror - daily, reservoir - weekly, per country, 1 file per weather year). (Source: OSMOSE based on PECD) Full details of data processing performed by OSMOSE WP1 can be found in appendix B of OSMOSE deliverable D1.3 (available at https://www.osmose-h2020.eu/resource-center). ## AntaresSimulator studies The dataset also contains 2 study skeletons (country and cluster granulariry) and R scripts allowing to build studies to be run with AntaresSimulator (https://antares-simulator.org). To run these studies, unzip the archives "OSMOSE_DATASET" (which actually contains the dataset) and "ANTARES_R" (which contains R scripts) and follow the instructions in "ANTARES_R/README.md". ## Forecast data The dataset also comprises 10 weather years (1982-1991) of AntaresSimulator imput time-series corresponding to day-ahead forecast data for demand, solar and wind for 2030 and 2050. These forecast data have been computed based on the installed capacities defined in OSMOSE CGA scenario. Details of the computation process can be found in the report included in this distribution. ## Licences Data is published under the terms of the "Creative Commons Attribution 4.0 International" licence (https://creativecommons.org/licenses/by/4.0) R code is published under the terms of the "MIT" licence (https://opensource.org/licenses/MIT) ## Acknowledgements The OSMOSE project(https://www.osmose-h2020.eu) received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 773406. Plan4Res EU project (https://zenodo.org/record/3802550) C3S (https://cds.climate.copernicus.eu) ENTSOE Pan European Common Database (https://zenodo.org/record/3702418 and https://zenodo.org/record/3985078) and MAF (https://www.entsoe.eu/outlooks/midterm/previous-maf-versions) e-Highway2050 project (https://cordis.europa.eu/project/id/308908/reporting)

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This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
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