Cvetković Stevica, Zdravković Milan, Ignjatović Marko
Faculty of Electronic Engineering, University of Niš, Aleksandra Medvedeva 4, 18104 Niš, Serbia.
Faculty of Mechanical Engineering, University of Niš, Aleksandra Medvedeva 4, 18104 Niš, Serbia.
Data Brief. 2025 Jan 22;59:111320. doi: 10.1016/j.dib.2025.111320. eCollection 2025 Apr.
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.
优化区域供热系统（DHS）以实现可持续发展目标并将成本降至最低，需要获取全面的真实世界数据集。本文介绍了一个数据集，该数据集包含从一个DHS系统收集的现场数据，该系统有五个安装在塞尔维亚尼什市住宅楼内的供热变电站。该数据集跨度长达五年（2019 - 2024年），源自一个SCADA系统，记录了关键参数，如一次和二次水流的供回水管线中的供热流体温度、能量传输测量数据以及当地气象站的室外温度。所有测量数据都使用既定方法进行了全面预处理，生成了等间隔的每小时数据，无错误或缺失值。此外，还进行了初步的探索性数据分析，以揭示数据中潜在的关系和分布情况。我们认为，该数据集对智慧城市、能源效率和区域供热领域的研究人员和从业者具有相当重要的意义。
