Abstract
Methods and technologies for analyzing and modeling the operation of a solar power plant using artificial neural networks are presented, the prospects for their application are discussed. Examples of solving the problems of forecasting the generation of electrical energy by solar power plants in various conditions are given. A comparison is made of the accuracy of a neural network model based on twelve parameters of meteorological conditions recorded by a special meteorological station and a less accurate neural network based on five parameters that can be taken from the data of the Hydrometeocenter.
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