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REEDD-CR: Residential electricity end-use demand dataset from Costa Rican households.
Angulo-Paniagua, Jam; Victor-Gallardo, Luis; Alfaro-Corrales, Ignacio; Quirós-Tortós, Jairo.
Afiliação
  • Angulo-Paniagua J; School of Electrical Engineering, University of Costa Rica, San José, Costa Rica.
  • Victor-Gallardo L; School of Electrical Engineering, University of Costa Rica, San José, Costa Rica.
  • Alfaro-Corrales I; School of Electrical Engineering, University of Costa Rica, San José, Costa Rica.
  • Quirós-Tortós J; School of Electrical Engineering, University of Costa Rica, San José, Costa Rica.
Data Brief ; 46: 108829, 2023 Feb.
Article em En | MEDLINE | ID: mdl-36591381
End-use demand data availability is a catalyst for improving energy efficiency measures and upgrading electricity demand studies. Nevertheless, residential end-use public datasets are limited, and end-use monitoring is costly. The lack of electricity end-use data is even more profound in Latin America, where there are no public end-use datasets as far as the authors are concerned. Hence, we present the Residential Electricity End-use Demand Dataset of Costa Rica (REEDD-CR), containing the results of monitoring 51 Costa Rican households. The data set includes the aggregated and branch circuit measurements for every home with a sample time of 1 min for at least an entire week. The measurements were distributed all around the country. In addition, based on these sub-measurements, REEDD-CR includes a dataset of 197 load signatures composed of seven consumption and demand features for eight high-consuming appliances: refrigerator, stove, dryer, lighting, water heating, air conditioning, microwave, and washing machine. The features included on each load signature are average power, peak power, average daily events, average daily energy, day-use factor, night-use factor, and time of use. The single-appliance measurements used to calculate these load signatures are also part of the dataset. The release of REEDD-CR can serve as a tool for appliance modeling, demand disaggregation testing, feedback for energy demand models, and the overall upgrade of electricity supply and demand simulation studies with realistic and disaggregated data.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Prognostic_studies Idioma: En Revista: Data Brief Ano de publicação: 2023 Tipo de documento: Article País de afiliação: Costa Rica País de publicação: Holanda

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Prognostic_studies Idioma: En Revista: Data Brief Ano de publicação: 2023 Tipo de documento: Article País de afiliação: Costa Rica País de publicação: Holanda