Electrical demand/consumption and climatological data of a small Mexican community

Published: 21 November 2023| Version 4 | DOI: 10.17632/vsjtbzjttb.4
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Description

The present dataset contains electricity demand/consumption and meteorological data measured in a small community within the Mexican State of Puebla. The data is contained in two separate folders named electrical_demand_consumption and weather. The first one contains electricity demand (i.e. kW) data in 15-minute resolution, as well as data regarding the hourly and daily electricity consumption (i.e. kWh) for five different households. The data is contained within .csv files that have the following name convention: houseteh(household number) _(resolution).csv. All data was measured from May 2022 to May 2023 and is represented as a time series. In other words, each measurement is linked to a specific time, which is given using the format dd/mm/yyyy HH:MM and is contained in the first column of every .csv file. Please note that missing values are represented with a –1; these values were added by the authors to facilitate the identification of missing values. The second folder contains---as the name suggests—the weather measured within the community. This data is contained in two separate .csv files. The first one (weather_outdoor variables.csv) contains the outdoor variables: Outdoor Temperature (°C), Feels Like (°C), Dew Point (°C), Wind Speed (m/s), Wind Gust (m/s), Max Daily Gust (m/s), Wind Direction (°), Hourly Rain (mm/h), Event Rain (mm), Daily Rain (mm), Weekly Rain (mm), Monthly Rain (mm), Yearly Rain (mm), Absolute Pressure (hPa), Relative Pressure (hPa), Humidity (%), Ultra-Violet Radiation Index, Solar Radiation (W/m^2), Avg Wind Direction (10 min) (°), Avg Wind Speed (10 min) (m/s). The second one (weather_indoor variables.csv) contains indoor measurements: Indoor Temperature (°C), Indoor Humidity (%), Indoor Feels Like (°C), and Indoor Dew Point (°C). All data was measured from May 2022 to March 2023, with an irregular time interval sampling, using the format dd/mm/yyyy HH:MM in the first column of the .csv file. For these files, missing values are not included.

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Institutions

Universidad Iberoamericana

Categories

Energy Consumption, Weather

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