Development of methods for the formation of operation modes of hydropower systems using machine learning

Abstract

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%.