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dc.contributor.authorC. Chupong
dc.contributor.authorB. Plangklang
dc.description.abstractPV 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 at 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 furtheren_US
dc.publisherRajamangala University of Technology Thanyaburien_US
dc.subjectNeural Networken_US
dc.subjectPV Power Forecastingen_US
dc.subjectSolar Radiationen_US
dc.titleForecasting Power output of PV Grid Connected System in Thailand without using Solar Radiation Measurementen_US
Appears in Collections:ประชุมวิชาการ (Proceedings)

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