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WILIAM Task 7.4

Name: WILIAM Task 7.4
Keywords: permutations, IAM, regression

Research datakeyboard_double_arrow_right Dataset 18 Oct 2021 English Publisher:Zenodo

Authors: Parrado-Hernando, Gonzalo; Pfeifer, Antun; Herc, Luka; Gjorgievski, Vladimir; Batas Bjelic, Ilija; Duić, Neven; Frechoso Escudero, Fernando; +2 Authors

doi: 10.5281/zenodo.5820401 , 10.5281/zenodo.5575961 , 10.5281/zenodo.5582611 , 10.5281/zenodo.5602814

WILIAM Task 7.4

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Abstract

This is the official repository of the Task 7.4 of H2020 Locomotion project. Feel free to use our data by citing this work and comment about our work by referencing the main authors of it. The article explaining this work is under revision. it will be referenced as soon as posible. Text files ("create_inputs.txt" and "run_simulations.txt") --> The first Python script creates the input files for EnergyPLAN. The second one runs iteratively EnergyPLAN to generate the outputs of combinations. Hourly distributions required to run the energy model are contained in the RAR file ("EUdist.rar"). The PowerPoint file ("EnergyPLAN_instructions.pptx") explains the procedure to carry out the runs of combinations in Python/Excel. In case you couldn't properly do the combinations, the Excel file ("EU.xlsx") saves this information, so the steps of the approach could be followed from this point with the Excel file. We have used Power Query (Excel) to prepare the data for the next step of building the regression models. The Matlab file ("CreateRegressionModels.m") automatically generates the regression models for the European region of WILIAM (official model of the Locomotion project).

Related Organizations

University of Belgrade
Serbia
Saints Cyril and Methodius University of Skopje
Former Yugoslav Republic of Macedonia
University of Zagreb
Croatia
University of Valladolid
Spain

Keywords

permutations, IAM, regression

1 Research products, page 1 of 1

Capturing features of hourly-resolution energy models through statistical annual indicators
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