Short-Term Load Forecast in Power Systems: A Comparison of Different Practical Algorithms

Metodija, Atanasovski and Mitko, Kostov and Goran, Veljanovski and Pande, Popovski (2022) Short-Term Load Forecast in Power Systems: A Comparison of Different Practical Algorithms. In: 2022 18th International Conference on the European Energy Market (EEM), 13-15.09.2022, Ljubljana, Slovenia.

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Abstract

Electricity demand forecasting has significant impact
on planning and operation of a power system. Parameters that
affect short and long-term load forecasting are the temperature, calendar day, geographical variations, gross national product, socio-demographic trends, energy efficiency etc. The weather conditions seriously affect load demand on short term. This paper
focuses on a comparison of different practical methodologies for short-term load forecast and their application and
implementation on real load demand and temperature data for
Republic of North Macedonia. The paper provides detailed
comparison of several practical algorithms for short-term load forecast: polynomial and sinuses regression, machine learning and artificial neural networks. The power load is considered from the aspect of two variables – temperature and calendar date. A case study is presented and results are discussed and analysed. Finally, conclusion and recommendations are presented.

Item Type:	Conference or Workshop Item (Paper)
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:	31 Oct 2022 10:17
Last Modified:	31 Oct 2022 10:17
URI:	https://eprints.uklo.edu.mk/id/eprint/7298

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