An electricity smart meter dataset of Spanish households: insights into consumption patterns

被引:0
|
作者
Carlos Quesada
Leire Astigarraga
Chris Merveille
Cruz E. Borges
机构
[1] University of Deusto,Deusto Institute of Technology, Faculty of Engineering
[2] GoiEner,undefined
来源
Scientific Data | / 11卷
关键词
D O I
暂无
中图分类号
学科分类号
摘要
Smart meters are devices that provide detailed information about the energy consumed by specific electricity supply points, such as homes, offices, and businesses. Data from smart meters are useful for modeling energy systems, predicting electricity consumption, and understanding human behavior. We present the first smart meter dataset from Spanish electricity supply points, expanding the geographic diversity of available data on energy consumption at the household level and reducing biases in existing data, which typically come from a limited number of countries. The dataset consists of 25,559 raw hourly time series with an average length of nearly three years, spanning from November 2014 to June 2022. It also includes three subsets obtained by segmenting and cleaning the raw time series data, each focusing on the periods before, during, and after the COVID-19 lockdowns in Spain. This dataset is a valuable resource for studying electricity consumption patterns and behaviors that emerge in response to different natural experiments, such as nationwide and regional lockdowns, nighttime curfews, and changes in electricity pricing.
引用
收藏
相关论文
共 50 条
  • [31] HALT Study on Smart Electricity Meter
    Wang Xiaoming
    Xie Jinzhe
    Xiong Jiulong
    2017 2ND INTERNATIONAL CONFERENCE ON SYSTEM RELIABILITY AND SAFETY (ICSRS), 2017, : 255 - 260
  • [32] Reliability Study on Smart Electricity Meter
    Wang Xiaoming
    2016 INTERNATIONAL CONFERENCE ON SYSTEM RELIABILITY AND SCIENCE (ICSRS 2016), 2016, : 162 - 166
  • [33] Development of electricity consumption profiles of residential buildings based on smart meter data clustering
    Czetany, Laszlo
    Vamos, Viktoria
    Horvath, Miklos
    Szalay, Zsuzsa
    Mota-Babiloni, Adrian
    Deme-Belafi, Zsofia
    Csoknyai, Tamas
    ENERGY AND BUILDINGS, 2021, 252
  • [34] Modeling and disaggregating hourly electricity consumption in Norwegian dwellings based on smart meter data
    Kipping, A.
    Tromborg, E.
    ENERGY AND BUILDINGS, 2016, 118 : 350 - 369
  • [35] Investigating the Appliance Use Patterns on the Households' Electricity Load Shapes from Smart Meters
    Afzalan, Milad
    Jazizadeh, Farrokh
    COMPUTING IN CIVIL ENGINEERING 2019: SMART CITIES, SUSTAINABILITY, AND RESILIENCE, 2019, : 154 - 161
  • [36] Detection of Energy Theft in Smart Grids using Electricity Consumption Patterns
    Syed, Dabeeruddin
    Abu-Rub, Haitham
    Refaat, Shady S.
    Xie, Le
    2020 IEEE INTERNATIONAL CONFERENCE ON BIG DATA (BIG DATA), 2020, : 4059 - 4064
  • [37] Big Data Analytics for Discovering Electricity Consumption Patterns in Smart Cities
    Perez-Chacon, Ruben
    Luna-Romera, Jose M.
    Troncoso, Alicia
    Martinez-Alvarez, Francisco
    Riquelme, Jose C.
    ENERGIES, 2018, 11 (03)
  • [38] Smart grids and renewable electricity generation by households
    Dato, Prudence
    Durmaz, Tunc
    Pommeret, Aude
    ENERGY ECONOMICS, 2020, 86
  • [39] A Dedicated Mixture Model for Clustering Smart Meter Data: Identification and Analysis of Electricity Consumption Behaviors
    Melzi, Fateh Nassim
    Same, Allou
    Zayani, Mohamed Haykel
    Oukhellou, Latifa
    ENERGIES, 2017, 10 (10)
  • [40] Residential electricity consumption and household characteristics: An econometric analysis of Danish smart-meter data
    Andersen, F. M.
    Gunkel, P. A.
    Jacobsen, H. K.
    Kitzing, L.
    ENERGY ECONOMICS, 2021, 100