Short-Term Prediction of the Wind Speed Based on a Learning Process Control Algorithm in Isolated Power Systems
Электронный научный архив УРФУ
Информация об архиве | Просмотр оригинала| Поле | Значение | |
| Заглавие |
Short-Term Prediction of the Wind Speed Based on a Learning Process Control Algorithm in Isolated Power Systems
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| Автор |
Manusov, V.
Matrenin, P. Nazarov, M. Beryozkina, S. Safaraliev, M. Zicmane, I. Ghulomzoda, A. |
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| Тематика |
ISOLATED POWER SYSTEM
NEURAL NETWORKS PREDICTION WIND SPEED ALGORITHM ARTIFICIAL NEURAL NETWORK ENERGY EFFICIENCY FUEL CONSUMPTION PREDICTION WIND VELOCITY AFGHANISTAN BADAKHSHAN |
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| Описание |
Predicting the variability of wind energy resources at different time scales is extremely important for effective energy management. The need to obtain the most accurate forecast of wind speed due to its high degree of volatility is particularly acute since this can significantly improve the planning of wind energy production, reduce costs and improve the use of resources. In this study, a method for predicting the speed of wind flow in an isolated power system of the Gorno-Badakhshan Autonomous Oblast (GBAO), based on the use of a neural network with a learning process control algorithm, is proposed. Predicting is performed for four seasons of the year, based on hourly retrospective meteorological data of wind speed observations. The obtained wind speed average error forecasting ranged from 20–28% for a day ahead. The prediction results serve as a basis for optimizing the energy consumption of individual generating consumers to minimize their financial and technical costs. In addition, this study takes into account the possibility of exporting electricity to a neighboring country as an additional income line for the isolated GBAO power system during periods of excess energy from hydropower plants (March–September), which is a systematic vision of solving the problem of improving energy efficiency in the conditions of autonomous power supply. © 2023 by the authors. Licensee MDPI, Basel, Switzerland.
Ministry of Education and Science of the Russian Federation, Minobrnauka The contribution of P.V. Matrenin to the research funding from the Ministry of Science and Higher Education of the Russian Federation (Ural Federal University Program of Development within the Priority-2030 Program) is gratefully acknowledged. |
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| Дата |
2024-04-05T16:19:03Z
2024-04-05T16:19:03Z 2023 |
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| Тип |
Article
Journal article (info:eu-repo/semantics/article) |info:eu-repo/semantics/publishedVersion |
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| Идентификатор |
Manusov, V, Matrenin, P, Nazarov, M, Beryozkina, S, Safaraliev, M, Zicmane, I & Ghulomzoda, A 2023, 'Short-Term Prediction of the Wind Speed Based on a Learning Process Control Algorithm in Isolated Power Systems', Sustainability, Том. 15, № 2, 1730. https://doi.org/10.3390/su15021730
Manusov, V., Matrenin, P., Nazarov, M., Beryozkina, S., Safaraliev, M., Zicmane, I., & Ghulomzoda, A. (2023). Short-Term Prediction of the Wind Speed Based on a Learning Process Control Algorithm in Isolated Power Systems. Sustainability, 15(2), [1730]. https://doi.org/10.3390/su15021730 2071-1050 Final All Open Access, Gold https://www.scopus.com/inward/record.uri?eid=2-s2.0-85151942779&doi=10.3390%2fsu15021730&partnerID=40&md5=1a8681950dc55de7c7b0f66bf59b5532 https://www.mdpi.com/2071-1050/15/2/1730/pdf?version=1674006146 http://elar.urfu.ru/handle/10995/130372 10.3390/su15021730 85151942779 000925094400001 |
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| Язык |
en
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| Права |
Open access (info:eu-repo/semantics/openAccess)
cc-by https://creativecommons.org/licenses/by/4.0/ |
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| Формат |
application/pdf
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| Издатель |
MDPI
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| Источник |
Sustainability
Sustainability (Switzerland) |
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