Exploring district heating systems: A SCADA dataset for enhanced explainabilityMendeley Data
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 buildi...
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| Format: | Article |
| Language: | English |
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Elsevier
2025-04-01
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| Series: | Data in Brief |
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| Online Access: | http://www.sciencedirect.com/science/article/pii/S2352340925000526 |
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| author | Stevica Cvetković Milan Zdravković Marko Ignjatović |
| author_facet | Stevica Cvetković Milan Zdravković Marko Ignjatović |
| author_sort | Stevica Cvetković |
| collection | DOAJ |
| description | 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. |
| format | Article |
| id | doaj-art-9c88c269b29749bfac463822c752f367 |
| institution | Kabale University |
| issn | 2352-3409 |
| language | English |
| publishDate | 2025-04-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Data in Brief |
| spelling | doaj-art-9c88c269b29749bfac463822c752f3672025-01-30T05:14:23ZengElsevierData in Brief2352-34092025-04-0159111320Exploring district heating systems: A SCADA dataset for enhanced explainabilityMendeley DataStevica Cvetković0Milan Zdravković1Marko Ignjatović2Faculty of Electronic Engineering, University of Niš, Aleksandra Medvedeva 4, 18104 Niš, Serbia; Corresponding author.Faculty of Mechanical Engineering, University of Niš, Aleksandra Medvedeva 4, 18104 Niš, SerbiaFaculty of Mechanical Engineering, University of Niš, Aleksandra Medvedeva 4, 18104 Niš, SerbiaOptimizing 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.http://www.sciencedirect.com/science/article/pii/S2352340925000526District heating systemTime seriesReal-time dataExplainable artificial intelligence |
| spellingShingle | Stevica Cvetković Milan Zdravković Marko Ignjatović Exploring district heating systems: A SCADA dataset for enhanced explainabilityMendeley Data Data in Brief District heating system Time series Real-time data Explainable artificial intelligence |
| title | Exploring district heating systems: A SCADA dataset for enhanced explainabilityMendeley Data |
| title_full | Exploring district heating systems: A SCADA dataset for enhanced explainabilityMendeley Data |
| title_fullStr | Exploring district heating systems: A SCADA dataset for enhanced explainabilityMendeley Data |
| title_full_unstemmed | Exploring district heating systems: A SCADA dataset for enhanced explainabilityMendeley Data |
| title_short | Exploring district heating systems: A SCADA dataset for enhanced explainabilityMendeley Data |
| title_sort | exploring district heating systems a scada dataset for enhanced explainabilitymendeley data |
| topic | District heating system Time series Real-time data Explainable artificial intelligence |
| url | http://www.sciencedirect.com/science/article/pii/S2352340925000526 |
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