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Urban energy load dataset of Chattogram: Peak and off-peak variability insights
Arnab Barua1, Shah Nawaz Haider2, Steve Austin2
1Department of Electrical and Electronic Engineering, University of Science and Technology Chittagong, Chattogram 4202, Bangladesh.
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.
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