Please use this identifier to cite or link to this item: http://www.repository.rmutt.ac.th/xmlui/handle/123456789/1102
Title: Forecasting power output of PV grid connected system in Thailand without using solar radiation measurement
Authors: Charnon Chupong
Boonyang Plangklang
Keywords: Neural network
PV power forecasting
Solar radiation
Issue Date: 2011
Publisher: Rajamangala University of Technology Thanyaburi. Faculty of engineering
Abstract: PV systems have been increasingly installed worldwide in recent years. Because it produces clean energy, moreover the development of technology is continued therefore the reliability is increasing and the price is decreasing in opposite. To implement the PV system, however, a significant limitation of PV system is the uncertainty of power from the sun. This will affect the quality' of the electrical system that connected. Therefore, this article will present the power forecasting of a PV system by calculating the solar radiation, collecting data from weather forecasting, and using Elman neural network to forecast by using data from PV system installed al roof top of Faculty Science and Technology Rajamangala University of Technology Thanyaburi. The results of study found that the tendency to apply this method any further
URI: http://www.repository.rmutt.ac.th/dspace/handle/123456789/1102
Appears in Collections:บทความ (Article - EN)

Files in This Item:
File Description SizeFormat 
Forecasting power output of PV grid connected system in Thailand....pdf1.08 MBAdobe PDFView/Open


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.