Urban energy load dataset of Chattogram: Peak and off-peak variability insights

This article presents a comprehensive dataset regarding the power demand for the period from January 1, 2021 to June 30, 2023, for the Chattogram region of Bangladesh. Chattogram is one of the country's fastest-growing industrial and residential regions where the demand for electricity and power is rapidly increasing. This is proportionate to urbanization, industries and residential power consumption. This dataset captures demand on a daily basis for the Day Peak (9AM-5PM), Evening Peak (6PM-9PM) and Off-Peak (10PM-8AM) hours and captures demand for industrial, residential and basal load during each period. To enhance the analysis, demand was further correlated to weather data obtained from the NASA POWER database which included temperature, dew-point, wet bulb temperature, skin temperature, humidity, air moisture and precipitation. Correlation analysis indicates strong, demand predictors, which are thermal features and specific humidity demand, whereas, relative humidity and precipitation were found to affect demand poorly. Integrated and automated data collection was performed via substation equipment resulting in cleaned and normalized data for model processing. This dataset allows the use of machine learning to accurately forecast real-world scenarios. By combining meteorological and load data, this resource supports research on energy efficiency, climate resilience and grid reliability in rapidly urbanizing regions.

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Publication Details

Journal
Data in Brief
Published
2025-11-06
DOI
https://doi.org/10.1016/j.dib.2025.112245
Primary Topic
Energy Load and Power Forecasting
Type
article
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article

Urban energy load dataset of Chattogram: Peak and off-peak variability insights

Arnab Barua, Steve Austin, Shah Nawaz Haider, Sarowar Morshed Shawon
Data in Brief
Energy Load and Power Forecasting
article

Urban energy load dataset of Chattogram: Peak and off-peak variability insights

Arnab Barua, Steve Austin, Shah Nawaz Haider, Sarowar Morshed Shawon
article en

Abstract

This article presents a comprehensive dataset regarding the power demand for the period from January 1, 2021 to June 30, 2023, for the Chattogram region of Bangladesh. Chattogram is one of the country's fastest-growing industrial and residential regions where the demand for electricity and power is rapidly increasing. This is proportionate to urbanization, industries and residential power consumption. This dataset captures demand on a daily basis for the Day Peak (9AM-5PM), Evening Peak (6PM-9PM) and Off-Peak (10PM-8AM) hours and captures demand for industrial, residential and basal load during each period. To enhance the analysis, demand was further correlated to weather data obtained from the NASA POWER database which included temperature, dew-point, wet bulb temperature, skin temperature, humidity, air moisture and precipitation. Correlation analysis indicates strong, demand predictors, which are thermal features and specific humidity demand, whereas, relative humidity and precipitation were found to affect demand poorly. Integrated and automated data collection was performed via substation equipment resulting in cleaned and normalized data for model processing. This dataset allows the use of machine learning to accurately forecast real-world scenarios. By combining meteorological and load data, this resource supports research on energy efficiency, climate resilience and grid reliability in rapidly urbanizing regions.

Data in BriefVol. 63
University of Science and Technology Chittagong (BD)
Openalex Percentile: Top 67%
Energy Load and Power Forecasting
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