Clustering River Basins Using Time-Series Data Mining on Hydroelectric Energy Generation.

Date

2018-09-14

Author

Arslan, Yusuf
Kucuk, Dilek
Eren, Sinan
Birtürk, Ayşe Nur

Metadata

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Hydropower is a significant renewable energy type with a considerable share in energy generation worldwide. As with the other common means of energy generation, hydropower is critical for the reliability and quality of electricity supply. Maintaining the reliability and quality of supply enables meeting the electricity demand of the loads adequately and efficient use of the energy resources, in addition to decreasing the related financial and environmental losses. In this paper, we target at the problem of basin clustering which is crucial for hydrological and electrical analyses regarding hydropower plants. We propose an approach based on time-series data mining on generation data of a large number of run-of-river type plants as well as of a number of representative storage type plants, in order to cluster the river basins in Turkey and present the clustering results with the related discussions. Based on these results, a new basin map is proposed which will be beneficial for enhanced hydrological and electrical analyses on hydropower and thereby for the maintenance of supply reliability and quality.

Subject Keywords

Hydropower, Renewable energy, Time-series clustering, River basins, Data mining, Energy informatics

URI

https://hdl.handle.net/11511/73864
https://link.springer.com/chapter/10.1007/978-3-030-04303-2_8

DOI

https://doi.org/10.1007/978-3-030-04303-2_8

Conference Name

DARE@PKDD/ECML 2018

Collections

Department of Computer Engineering, Conference / Seminar

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Citation Formats

Y. Arslan, D. Kucuk, S. Eren, and A. N. Birtürk, “Clustering River Basins Using Time-Series Data Mining on Hydroelectric Energy Generation.,” Dublin, İrlanda, 2018, p. 103, Accessed: 00, 2021. [Online]. Available: https://hdl.handle.net/11511/73864.