NEURAL NETWORK FOR PREDICTING THE ENERGY GENERATED BY SOLAR RADIATION Cover Image

НЕВРОННА МРЕЖА ЗА ПРОГНОЗИРАНЕ НА КОЛИЧЕСТВОТО ГЕНЕРИРАНА ОТ СЛЪНЧЕВА РАДИАЦИЯ ЕНЕРГИЯ
NEURAL NETWORK FOR PREDICTING THE ENERGY GENERATED BY SOLAR RADIATION

Author(s): Penka Georgieva
Subject(s): Economy, Energy and Environmental Studies
Published by: Бургаски свободен университет
Keywords: artificial neural network; micro PV system; intelligent building management.
Summary/Abstract: This article proposes an approach for short-term forecasting of electricity production from a micro grid connected PV system using the means of artificial intelligence. An artificial neural network is used to create the model. The forecasting model has three input variables: solar radiation, wind speed and air temperature, and one output variable - the amount of electricity produced by the installed photovoltaic panels in the microsystem. This study is a part of a project for optimization of the energy consumption of a building in case that independent alternative renewable energy sources are used. The model is implemented and tested on real data collected in 5 minutes from a specially designed meteorological station installed in the building of the Burgas Free University.

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