Power spectrum: A detailed dataset on electric demand and environmental interplays

• Main Authors: Jawad, M.S., Dhawale, Chitra, Al Ali, Abdel Rahman, Ramli, Azizul Azhar
• Format: Article
• Language: English
• Published: Elsevier 2024
• Subjects: TK Electrical engineering. Electronics Nuclear engineering
• Online Access: http://eprints.uthm.edu.my/11769/1/J17266_1594162e564c48282331c84a630fc1fd.pdf; http://eprints.uthm.edu.my/11769/

This dataset provides detailed electricity demand forecasting metrics for the Sharjah Electricity and Water Authority (SEWA) over 2020 and 2021. Data encompasses both hourly and daily demand patterns, enriched with specific environmental parameters such as temperature, humidity, and solar irradiance. Additionally, SEWA’s unique load metrics and lagged demand values, representing previous hour demand, are included. Data was procured using advanced electrical load meters and standardized weather data acquisition systems. Preliminary and advanced data processing was conducted via Excel tool. This comprehensive dataset is invaluable for stakeholders in electricity provisioning and policy-making. Its granular detail makes it a pivotal resource for modelling and forecasting electricity demand, aiding in infrastructure planning, renewable energy considerations, and demand-side management. The potential applications span across academic, policy, and industry domains, rendering it a versatile tool for future electricity demand research.