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dc.contributor.authorMey, Oliver-
dc.contributor.authorSchneider, André-
dc.contributor.authorEnge-Rosenblatt, Olaf-
dc.contributor.authorYesnier, Bravo-
dc.contributor.authorStenzel, Pit-
dc.date.accessioned2021-08-06T11:42:36Z-
dc.date.available2021-08-06T11:42:36Z-
dc.date.issued2021-
dc.identifier.urihttps://fordatis.fraunhofer.de/handle/fordatis/215-
dc.identifier.urihttp://dx.doi.org/10.24406/fordatis/142-
dc.description.abstractPredictions of energy consumption are crucial for energy retailers to minimize deviations from energy acquired in the day-ahead market and the actual consumption of their customers. The increasing spread of smartmeters means that retailers have access to hourly consumption values of all their contracted customers in realtime. Using machine learning algorithms, these hourly values can be used to calculate predictions for the future energy consumption of the customers. The present data set allows the training and validation of AI-based prediction models.en
dc.language.isoenen
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/en
dc.subjectenergy consumptionen
dc.subjecthourly consumptionen
dc.subjectdifferent customer profilesen
dc.subjectprivate householdsen
dc.subject.ddcDDC::600 Technik, Medizin, angewandte Wissenschaftenen
dc.titleEnergy Consumption Curves of 499 Customers from Spainen
dc.typeTabular Dataen
dc.contributor.funderBundesministerium für Verkehr und digitale Infrastruktur BMVI (Deutschland)en
dc.description.technicalinformationThe dataset contains the measured energy consumption of 499 customers in Spain. The file 20201015_consumption.xlsx contains time series with an hourly resolution for each of the customers. The energy consumption is measured in kWh. In addition to energy consumption weather data is available. The file 20201015_weather.xlsx contains the outside temperature for the region of each customer as time series with an hourly resolution. The file 20201015_profiles.xlsx contains the meta data for the 499 customers. Each customer is assigned to one of the 68 customer profiles (such as private households, shops, bakeries).en
dc.title.translatedEnergieverbrauchskurven von 499 Kunden aus Spaniende
fordatis.groupEnergietechnologien und Klimaschutzen
fordatis.instituteIIS Fraunhofer-Institut für Integrierte Schaltungen - Institutsteil Entwicklung Adaptiver Systeme EASen
fordatis.project.fhgid290157en
fordatis.rawdatatrueen
fordatis.sponsorship.FundingProgrammeEurostars-2 Horizon 2020en
fordatis.sponsorship.projectidE!113348en
fordatis.sponsorship.projectnameEnergy Saving by Blockchainen
fordatis.sponsorship.projectacronymESBen
fordatis.sponsorship.ResearchFrameworkProgrammEurostars Horizon 2020en
fordatis.date.start2019-01-01-
fordatis.date.end2019-12-30-
Appears in Collections:IIS Fraunhofer-Institut für Integrierte Schaltungen - Institutsteil Entwicklung Adaptiver Systeme EAS

Files in This Item:
File Description SizeFormat 
20201015_consumption.xlsxenergy consumption curves of the 499 customers (time series, hourly resolution)21,06 MBMicrosoft Excel XMLDownload/Open
20201015_profiles.xlsxprofiles of the 499 customers19,21 kBMicrosoft Excel XMLDownload/Open
20201015_weather.xlsxweather data (outside temperature) of the customer's regions (time series, hourly resolution)18 MBMicrosoft Excel XMLDownload/Open
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