Abstract
Optimizing District Heating Systems (DHS) to achieve sustainability objectives and minimize costs requires access to comprehensive real-world datasets. This paper introduces a dataset comprising field data collected from a DHS system featuring five heating substations installed in residential buildings within the city of Niš, Serbia. Spanning a period of up to five years (2019-2024), the dataset originates from a SCADA system, capturing critical parameters such as heating fluid temperatures in the supply and return lines of both primary and secondary flows, energy transmission measurements, and outdoor temperatures from a local meteorological station. All measured data underwent comprehensive pre-processing using established methodologies, resulting in uniformly spaced hourly data free of errors or missing values. Furthermore, a preliminary exploratory data analysis was conducted to uncover insights into the underlying relationships and distributions within the data. We contend that this dataset is of considerable relevance to researchers and practitioners in the fields of smart cities, energy efficiency, and district heating.