Albanian national electricity consumption and weather conditions for 2016-2019
The following dataset is published as part of the following paper " Sevdari, K., Islami, A., Haxhiraj, E. and Voshtina, E., 2022. A Data-Driven Assessment of the Electricity Demand-the Case of Albania. In 2022 International Conference on Renewable Energies and Smart Technologies. IEEE." Please cite the paper when using this dataset. Link of the paper: https://ieeexplore.ieee.org/document/10022956
The dataset is in Excel file format.
There are 14 columns that represent:
1-Time: Month/Day/Year Hour (calendar format)
2-Time_double: hours for 1 year (double format)
3-Load: The hourly electricity consumption in MWh for Albania
4-full_temp: The hourly temperature values in degrees Celsius taken from a weather station in the capital, Tirana.
5-full_humid: The hourly humidity values in % taken from a weather station in the capital, Tirana.
6-full_rain: The hourly rain conditions taken from a weather station in the capital, Tirana. 1 means a rainy hour and 0 means a clear (no rain) hour.
7-Muaj: Muaj (Albanian) or Months (English). This variable counts the months each hour belongs to.
8-Ditet: Ditet (Albanian) or Days (English). This variable counts the days each hour belongs to.
9-Ore: Ore (Albanian) or Hours (English). This variable counts the hours of each day and repeats itself.
10-Pushimet: Pushimet (Albanian) or Holidays-weekends (English). This variable identifies the weekend hours. 1 means a weekend hour and 0 means a week hour.
11-Oret e nates: Night hours (English). This variable distinguishes between night and day hours.
12- Pushimet vjetore: Yearly official holidays (English). This variable identifies the hours that fall under official yearly holidays in Albania.
13-Oret e nates_2 : Night hours _ 2 (English). This variable distinguishes between night and day hours.
14- Oret e pikut: Peak consumption hours (English). This variable identifies the hours of peak consumption.
History
Topic
- Other
Models
- Electrical;>Other
Activities
- Other
External conditions
- Other
Data category
- Meteorological data
- Other data