Dataset on electricity usage measurement for lower-to-middle-income primary and secondary schools in Western Cape, South AfricaMendeley Data - Jason Avron Samuels; Terhemba Michael-Ahile; M. J. (Thinus) Booysen (Data in Brief)
As lower- and middle-income countries strive for greater energy efficiency, they encounter challenges such as rapid urban growth, limited resources, and restricted access to reliable and affordable energy services. High energy usage, resulting from inadequate building designs, outdated technologies, and poor practices, further complicates these efforts. Unfortunately, there has been limited focus on examining these issues within the context of developing countries. This dataset comprises electricity usage data collected every 30 min from 53 lower- to middle-income public primary and secondary schools in the Western Cape, South Africa, offering a detailed view of usage patterns. Public primary and secondary schools in South Africa are categorized into quintiles from Q1 (least economically advantaged) to Q5 (most affluent), a system designed to address economic disparities by considering the economic status of the surrounding community and the existing school infrastructure. With over 24,000 public primary and secondary schools using an estimated 3.5 TWh annually, the collective utility expense amounts to ZAR 5.0 billion (approximately US$ 330 million). Given this substantial financial burden, a comprehensive dataset to support the sustainability and financial viability of these schools is essential, ensuring that more resources can be directed toward their core educational missions. The data was collected using smart meters installed in the schools over one year, from December 1, 2022, to November 30, 2023. The dataset has undergone a multi-stage improvement process, resulting in three distinct versions: v1: The raw dataset directly extracted from the smart meters; v2: A clean version with imputed missing timestamps and values to address gaps caused by “load shedding”, and v3: An enhanced version built on the cleaned dataset (v2) by adding several new features to provide richer context and facilitate more detailed analysis, including an indication of the season, school terms, and holidays.This dataset is invaluable for understanding electricity usage behaviours in educational institutions within a developing country context. It enables the analysis of usage trends, the impact of academic schedules and holidays, and the effects of load shedding on school operations. Researchers and policymakers can leverage this dataset to develop strategies for energy efficiency, cost reduction, and sustainable energy management in schools. This includes exploring usage patterns, peak demands, and the integration of alternative energy sources. The dataset holds significant value for stakeholders in the educational and energy sectors, providing detailed insights into energy usage trends that are crucial for strategic planning, policy development, and operational adjustments in similar socioeconomic environments.