JOAMS 2023 Vol.11(4): 144-150
doi: 10.18178/joams.11.4.144-150
doi: 10.18178/joams.11.4.144-150
Big Data Pipeline for Building Energy Management
Zhiyu Pan 1,
Panagiotis Kapsalis 2,
Konstantinos Alexakis 2,
Georgios Korbakis 2,
and
Antonello Monti 3
1.
Institute for Automation of Complex Power Systems, RWTH Aachen University, Aachen, Germany
2. Decision Support Systems Laboratory, National Technical University of Athens, Athens, Greece
3. Institute for Automation of Complex Power Systems, RWTH Aachen University, Aachen, Germany
*Correspondence: zhiyu.pan@eonerc.rwth-aachen.de (Z.P.)
2. Decision Support Systems Laboratory, National Technical University of Athens, Athens, Greece
3. Institute for Automation of Complex Power Systems, RWTH Aachen University, Aachen, Germany
*Correspondence: zhiyu.pan@eonerc.rwth-aachen.de (Z.P.)
Manuscript received June 2, 2023; revised August 22, 2023; accepted October 5, 2023; published December 4, 2023.
Abstract—The increasing of heterogeneous data in the building domain brings a huge challenge to data integration. With the combination of ontology and data model, a building energy domain common data model is developed and provides a uniform data schema to guide the data integration process. Additionally, a cloud data pipeline is proposed and developed, which includes the common data model, data harmonization, data storage and data querying. The requirement and possible use cases for the big data pipeline for building energy management are described. This work provides guidelines for big data management in building energy domain. Furthermore, our data pipeline is evaluated with 11 large pilots and shows a significant improvement in the data governance process.
Keywords—big data, building Life-Cycle, data model, data pipeline, ontology
Cite: Zhiyu Pan, Panagiotis Kapsalis, Konstantinos Alexakis, and Georgios Korbakis, and Antonello Monti, "Big Data Pipeline for Building Energy Management," Journal of Advanced Management Science, Vol. 11, No. 4, pp. 144-150, 2023.
Copyright © 2023 by the authors. This is an open access article distributed under the Creative Commons Attribution License (CC BY-NC-ND 4.0), which permits use, distribution and reproduction in any medium, provided that the article is properly cited, the use is non-commercial and no modifications or adaptations are made.
Cite: Zhiyu Pan, Panagiotis Kapsalis, Konstantinos Alexakis, and Georgios Korbakis, and Antonello Monti, "Big Data Pipeline for Building Energy Management," Journal of Advanced Management Science, Vol. 11, No. 4, pp. 144-150, 2023.
Copyright © 2023 by the authors. This is an open access article distributed under the Creative Commons Attribution License (CC BY-NC-ND 4.0), which permits use, distribution and reproduction in any medium, provided that the article is properly cited, the use is non-commercial and no modifications or adaptations are made.