A neural network model for short-term PV - energy forecasting

Nowadays, energy consumption in the world is growing becomes relevant to solve the problem of replacing traditional sources with alternative ones. The solution to this problem is impossible without preliminary forecasting of energy production by alternative sources. In this paper, we consider the problem of solving the problem forecasting electric energy by solar power plants, considering the influence of external factors (weather conditions) using a model implemented on the basis a neural network.

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A neural network model for short-term PV - energy forecasting

Semantic Scholar · Engineering · 2020

Abstract

Nowadays, energy consumption in the world is growing becomes relevant to solve the problem of replacing traditional sources with alternative ones. The solution to this problem is impossible without preliminary forecasting of energy production by alternative sources. In this paper, we consider the problem of solving the problem forecasting electric energy by solar power plants, considering the influence of external factors (weather conditions) using a model implemented on the basis a neural network.

References (6)

04Gritsay A S and Tyunkov D A 2017 Dynamics of Systems, Mechanisms and Machines: conference proceeding p 78190631906
05As a training sample, retrospective data on the generation of electric energy at the annual preceding the predicted day are usedFigures 8 and 9 show the forecast data for 1 and 2 solar power plants located on Hokaydo Island
06At the second stage of constructing a short-term prognostic modelFigure 5

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