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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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BibTeX
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.