SYSTEM OF SHORT-TERM FORECASTING OF WIND TURBINE OUTPUT POWER CONSUMPTION
Fazylova A.R. Balbayev G. Tultayev B.
2022National Academy of Sciences of the Republic of Kazakhstan
News of the National Academy of Sciences of the Republic of Kazakhstan, Series of Geology and Technical Sciences
2022#2022Issue 3243 - 252 pp.
When solving the problems of increasing the efficiency, reliability and optimization of the operation of wind turbines, it is necessary to consider the problems of forecasting and calculating electricity consumption. The stage of forecasting the consumption of electrical energy will increase the efficiency of the wind turbine by adjusting the process of automating the storage, load, accumulation and analysis of data necessary for building and training a system for predicting the consumption of electrical energy based on artificial intelligence. This article considers a system for predicting the consumption of the output power of a wind turbine, taking into account various parameters. In order to increase the speed of forecasting the consumption of output power, the method of artificial neural networks was applied. To develop a high-quality forecast database, a static base of output power consumption of the past period was created. This will allow you to find coefficients that characterize the change in power consumption depending on various conditions (seasonal changes, weekends and holidays, time of day, etc.). Thus, in this work, not only weather conditions, time of year, but also day parameters are taken into account (working, weekend, first day of the week, last, etc.).
neural network , power consumption , power output , short-term forecasting , wind turbine
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Institute of Automation and Information Technologies, Satbayev University, Almaty, Kazakhstan
Academy of Logistics and Transport, Almaty, Kazakhstan
Institute of Automation and Information Technologies
Academy of Logistics and Transport
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