E3S Web Conf.
Volume 124, 2019International Scientific and Technical Conference Smart Energy Systems 2019 (SES-2019)
|Number of page(s)||5|
|Published online||10 February 2020|
Development of methods for the formation of operation modes of hydropower systems using machine learning
JSC Tatenergo, 420021, Salimzhanova 1, Kazan, Russian Federation
2 Kazan State Power Engineering University, 420066, Krasnoselskaya str., 51, Kazan, Russian Federation
* Corresponding author: email@example.com
The paper describes the method for finding a compromise solution during formation of operation modes of hydropower systems (cascade of hydropower plants). The software solution “Energy system of the HPP cascade” (http://hydrocascade.com) was implemented based on the developed methodology. In the existing model, in order to improve the accuracy of forecasting the parameters of the generating equipment of hydroelectric power plants and hydraulic structures, machine learning methods were used. The new forecast model has increased the accuracy of the forecasts by an average of 3.67%.
© The Authors, published by EDP Sciences, 2020
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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