Е-Публикации
Технически университет - София

Abstract: The report provides a brief summary of the most commonly used methods for short-term forecasting of electrical loads. A methodology is presented, using the method of autoregressive integrated moving averages, the model with artificial neural networks, and the hybrid combination of the two above-mentioned models for making a day-ahead prognosis of energy production from wind farms, connected to a common node of the electricity grid. Calculations have been made using the three proposed methods for the 24-hour load schedule of a distribution network with three wind farms included in a common connection node. The obtained results are compared and useful conclusions are drawn about choosing a method for short-term forecasting of energy yield from wind farms.

References

1. P. I. Tsvetkova. "Optimal short-term planning in smart electricity networks, " Monograph. ISBN 978-619-167-587-6, Sofia, The Publishing House of the Technical University of Sofia, 2025.
2. S. I. Nedelcheva, E. P. Vasileva, D. Vasilev, B. S. Bakardzhiev, S. Bayraktarov. "Economic analysis of the construction of decentralized energy sources, " ISSN 1312-3920, Proceedings of TU-Sliven, No. 1, 2017.
3. S. I. Nedelcheva, M. I. Matsankov. "Analysis of the methods for forecasting electrical loads in electrical networks, " ISSN 1312-3920, Proceedings of TU-Sliven, 1, 2019
4. P. I. Tsvetkova, M. S. Mladenov, A. B. Hristov. "Application of the ARIMA model for short-term forecasting of electrical loads in a distribution network with decentralized sources, " Proceedings of TUSliven, ISSN 1312-3920, No. 6, 2024. Pp.22-29.
5. E. P. Vasileva. "Optimization of technological systems by redundancy of the main structural elements, " 2023 58th International Scientific Conference on Information, Communication and Energy Systems and Technologies (ICEST). 10.1109/ICEST58410.2023.10187351.
6. G. E. Box, G. M. Jenkins, G. C. Reinsel and G. M. Ljung, "Time series analysis: forecasting and control, " 4th ed, John Wiley & Sons, 2016.
7. A. Hussan, K. Yamur, A. Douri, J. Lundberg. "Time Series Forecasting using ARIMA Model, " ADVCOMP 2018: The Twelfth International Conference on Advanced Engineering Computing and Applications in Sciences. ISBN: 978-1-61208-677-4, 2018.
8. S. I. Nedelcheva. "Forecasting of electrical loads through iterative correction of systematic error, " ISSN 1312-3920, Proceedings of TUSliven, 4, 2010
9. S. I. Nedelcheva, M. I. Matsankov. "Application of artificial neural networks in forecasting electrical loads in the nodes of distribution networks, " Journal of Energy, ISSN 0324-1521, No 6-7, 2007, pp.45-51.
10. H. S. Ilchev. "Risk assessment of a base power deficit in the electric power system, " 2024 9th International Conference on Energy Efficiency and Agricultural Engineering (EE&AE). DOI: 10.1109/EEAE60309.2024.10600622.
11. E. P. Vasileva. "Methodology for reliability assessment of distribution networks with decentralized energy resources connected, " 2022 57th International Scientific Conference on Information, Communication and Energy Systems and Technologies (ICEST). 10.1109/ICEST55168.2022.9828731.
12. P. Harry. "Automated Machine Learning (AutoML): The Future of Model Selection and Tuning, " University of Belgrade, June 2025.
13. Y. Liang. "Research on intelligent upgrade strategy of digital platform based on machine learning, " In International Conference on Mechatronics and Intelligent Control (ICMIC 2024) (Vol. 13447, pp. 1395-1401). SPIE. 2025.
14. I. Hatzakis, D. Wallace, "Dynamic multi-objective optimization with evolutionary algorithms: a forward-looking approach, " in Proceedings of the 8th annual conference on Genetic and evolutionary computation, July 2006, pp. 1201-1208.
15. P. I. Tsvetkova. "Methodology for optimal short-term day-ahead planning with application of Price's genetic algorithm, " Proceedings of TU-Sliven, ISSN 1312-3920, No. 1, 2025. Pp.28-33.
16. P. I. Tsvetkova. "Optimal short-term day-ahead planning using Price's genetic algorithm in a multi-loop network, " Proceedings of the Technical University of Sliven, ISSN 1312-3920, No. 1, 2025. Pp.34-37.
17. G. P . Zhang, "Time series forecasting using a hybrid ARIMA and neural network model, " Neurocomputing, vol. 50, 2003, pp. 159-175.
18. P. I. Tsvetkova, N.V.Savov. "Application of fuzzy logic to short-term planning of electric loads, " 2024 9th International Conference on Energy Efficiency and Agricultural Engineering, (EE&AE), 2024, https://doi.org/10.1109/EEAE60309.2024.10600493.
19. E. Vasileva "Optimization of Electricity Losses During Electricity Transmission and Distribution, " 2024 59th International Scientific Conference on Information, Communication and Energy Systems and Technologies (ICEST). 10.1109/ICEST62335.2024.10639640.
20. M. K. Hassan. "Development Trends in Hydrogen Power Engineering, " 2024 Ninth Junior Conference on Lighting (Lighting). DOI: 10.1109/Lighting62260.2024.10590675.
21. H. S. Ilchev H. "Induced Voltage in a Disconnected Grounded Conductor of a Three-Phase Electric Power Line, " 2025 Tenth Conference on Lighting (Lighting). DOI: 10.1109/Lighting64836.2025.11081753.
22. M. K. Hassan. "Optimum regime parameters in electrical networks with connected decentralized energy sources, " 2024 9th International Conference on Energy Efficiency and Agricultural Engineering (EE&AE). DOI: 10.1109/EEAE60309.2024.10600522.
23. K. V. Raykov. "Operational reliability of connection schemes of photovoltaic systems with three single-phase grid inverters, " 2024 9th International Conference on Energy Efficiency and Agricultural Engineering (EE&AE). DOI: 10.1109/EEAE60309.2024.10600608.

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