ELECTRICITY CONSUMPTION PREDICTION USING LGBM ALGORITHM IN ML.NET AND PYTHON
DOI:
https://doi.org/10.24867/23BE25SimicKeywords:
LGBM, ML.NET, Python, Machine Learning, AlgorithmAbstract
By predicting electricity consumption, electricity distribution companies can more efficiently plan the mode of use of generating plants, regular maintenance of network elements, as well as potential trade on the electricity market. Machine learning algorithms can serve as a tool for accurate consumption forecasting in power systems. Through this work, two software solutions for forecasting electricity consumption based on weather data were implemented using the LGBM algorithm in ML.NET and Python, while the prediction results were described and analyzed.
References
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[5] Gama João, Rodrigues Pedro, „Stream-Based Electricity Load Forecast“, 446-453. 10.1007/978-3-540-74976-9_45, 2007.
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[7] J. W. Taylor, „An evaluation of methods for very short-term load forecasting using minute-by-minute British data“, International Journal of Forecasting, vol. 24, no. 4, pp. 645-658, 2008.
[8] G. Gross, F.D. Galiana, „Short-term load forecasting“, Proceedings of the IEEE, vol. 75, no.12, pp. 1558-1572, 1987.
[9] N. Amjady, F. Keynia, „Mid-term load forecasting of power systems by a new prediction method“, Energy Conversion and Management, vol. 49, no. 10, pp. 2678-2687, 2008.
[10] H. Daneshi, M. Shahidehpour, A. L. Choobbar, „Long-term load forecasting in electricity market“, IEEE International Conference on Electro/Information Technology, USA, 2008.
[11] Harsh H. Patel, Purvi Prajapati, „Study and Analysis of Decision Tree Base Classification Algorithms“, Dept. Of Information Technology, CSPIT, Charotar University of Science and Technology, Changa, Gujarat, India.
[12] Lior Rokach, Oded Maimon, „The Data Mining and Knowledhe Discovery Handbook Chapter:Decision Trees“, DOI:10.1007/-387-25465-X_9.
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[17] https://lightgbm.readthedocs.io/en/latest/index.html (pristupljeno u martu 2023.)
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Published
2023-07-08
Issue
Section
Electrotechnical and Computer Engineering
