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Energies
Volume 14
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10.3390/en14112983
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Article

High Precision LSTM Model for Short-Time Load Forecasting in Power Systems

by
Tomasz Ciechulski
1,* and
Stanisław Osowski
1,2
1
Institute of Electronic Systems, Faculty of Electronics, Military University of Technology, ul. gen. Sylwestra Kaliskiego 2, 00-908 Warsaw, Poland
2
Faculty of Electrical Engineering, Warsaw University of Technology, pl. Politechniki 1, 00-661 Warsaw, Poland
*
Author to whom correspondence should be addressed.
Energies 2021, 14(11), 2983; https://doi.org/10.3390/en14112983
Submission received: 26 March 2021 / Revised: 7 May 2021 / Accepted: 17 May 2021 / Published: 21 May 2021
(This article belongs to the Special Issue Computational Intelligence and Load Forecasting in Power Systems)
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Abstract

The paper presents the application of recurrent LSTM neural networks for short-time load forecasting in the Polish Power System (PPS) and a small region of a power system in Central Poland. The objective of the present work was to develop an efficient and accurate method of forecasting the 24-h pattern of power load with a 1-h and 24-h horizon. LSTM showed effectiveness in predicting the irregular trends in time series. The final forecast is estimated using an ensemble consisted of five independent predictions. Numerical experiments proved the superiority of the ensemble above single predictor resulting in a reduction of the MAPE the RMSE error by more than 6% in both forecasting tasks.
Keywords: recurrent LSTM network; load forecasting; prediction systems; power systems; demand-side management recurrent LSTM network; load forecasting; prediction systems; power systems; demand-side management

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MDPI and ACS Style

Ciechulski, T.; Osowski, S. High Precision LSTM Model for Short-Time Load Forecasting in Power Systems. Energies 2021, 14, 2983. https://doi.org/10.3390/en14112983

AMA Style

Ciechulski T, Osowski S. High Precision LSTM Model for Short-Time Load Forecasting in Power Systems. Energies. 2021; 14(11):2983. https://doi.org/10.3390/en14112983

Chicago/Turabian Style

Ciechulski, Tomasz, and Stanisław Osowski. 2021. "High Precision LSTM Model for Short-Time Load Forecasting in Power Systems" Energies 14, no. 11: 2983. https://doi.org/10.3390/en14112983

APA Style

Ciechulski, T., & Osowski, S. (2021). High Precision LSTM Model for Short-Time Load Forecasting in Power Systems. Energies, 14(11), 2983. https://doi.org/10.3390/en14112983

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