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One Day Ahead Forecasting of Generating Power for Photovoltaic Power System

Authors:
Hyang-A Park
Jong-yul Kim
Eung-Sang Kim
Sung-shin Kim

Keywords: Solar irradiation; Neural network; Photovoltaic; Forecasting model.

Abstract:
Photovoltaic power generation is affected much by weather and temperature, so the amount of power generation is not constant and there are many difficulties in predicting. Thus, the accurate prediction of the photovoltaic power due to climate change is critical to stable electricity supply. In this paper, in order to create a power generation forecast model, the data, such as power generation, temperature, Daily Mean Cloud Amount (DMCA) data has been collected from April 2016 to September 2016. Using the neural network, the peak solar irradiation forecasting model was created, solar irradiation was calculated from the peak solar irradiation predicted, and finally the model to predict power generation was made. In this paper, the peak solar irradiation is predicted using the maximum temperature and the peak solar irradiation data, and ultimately the solar power generation is predicted through the predicted peak solar irradiation.

Pages: 12 to 15

Copyright: Copyright (c) IARIA, 2017

Publication date: May 21, 2017

Published in: conference

ISSN: 2308-4154

ISBN: 978-1-61208-561-6

Location: Barcelona, Spain

Dates: from May 21, 2017 to May 25, 2017