PaSTS An Operational Dataset for Domestic Solar Thermal Systems
Pages 529 - 534
Abstract
Solar thermal systems play an important role in the decarbonization of the domestic heating sector, yet there exist no publicly available datasets of such systems. Therefore, this paper presents the PaSTS dataset, a unique collection of operational data from domestic Solar Thermal Systems (STS) manufactured by Ritter Energie and marketed under the Paradigma brand. Unlike previous research that primarily relied on simulated or unpublished experimental data, this dataset is derived from the service team at Ritter Energie, offering a realistic reflection of the challenges commonly faced in the field. This paper provides a comprehensive dataset overview, emphasizing its application in anomaly and fault detection tasks within STS and establishes the dataset as the first of its kind.
Given the inherent complexities of fault detection in STS, we elaborate on the expert system-based fault detection mechanism currently in use and advocate for applying semi-supervised or unsupervised anomaly detection techniques tailored to the dataset’s characteristics.
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Published In
June 2024
704 pages
ISBN:9798400704802
DOI:10.1145/3632775
Copyright © 2024 Owner/Author.
This work is licensed under a Creative Commons Attribution International 4.0 License.
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Association for Computing Machinery
New York, NY, United States
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Published: 31 May 2024
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e-Energy '24
e-Energy '24: The 15th ACM International Conference on Future and Sustainable Energy Systems
June 4 - 7, 2024
Singapore, Singapore
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Overall Acceptance Rate 160 of 446 submissions, 36%
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