K-Nearest Neighbor Regression for Forecasting Electricity Demand

Atanasovski, Metodija and Kostov, Mitko and Arapinoski, Blagoja and Spirovski, Mile (2020) K-Nearest Neighbor Regression for Forecasting Electricity Demand. In: 2020 55th International Scientific Conference on Information, Communication and Energy Systems and Technologies (ICEST), September, 10-12, 2020, Niš, Serbia, Serbia.

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Official URL: https://doi.org/10.1109/ICEST49890.2020.9232768

Abstract

Power system load forecasting plays a vital role in all aspects of power system planning, operation and control. It is a basic function for reliable and economical operation of power systems. This paper analyses the power system load forecast performed by applying k-nearest neighbour machine learning model, which is for the first time applied on real data of North Macedonia power system. The results are compared with polynomial and sinuses regressions.

Item Type: Conference or Workshop Item (Paper)
Additional Information: This research is supported by the EU H2020 project TRINITY (Grant Agreement no. 863874) This paper reflects only the author’s views and neither the Agency nor the Commission are responsible for any use that may be made of the information contained therein.
Subjects: Scientific Fields (Frascati) > Engineering and Technology > Electrical engineering, electronic engineering,information engineering
Divisions: Faculty of Technical Sciences
Depositing User: Prof. d-r. Metodija Atanasovski
Date Deposited: 22 Oct 2020 09:18
Last Modified: 22 Oct 2020 09:18
URI: http://eprints.uklo.edu.mk/id/eprint/5821

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