Please use this identifier to cite or link to this item:
Title: Photovoltaic power forecasting using total sky imager
Authors: Ye, Penghao
Keywords: DRNTU::Engineering::Electrical and electronic engineering::Electric power::Auxiliaries, applications and electric industries
Issue Date: 2014
Abstract: Fluctuation and intermittent are existed in photovoltaic (PV) power generation. Massive PV grid-connection may bring adverse effect to the running of power system. The forecast of output power of the PV power plant, will balance the dispatch of the conventional energy (thermal power, hydropower, etc) and the photovoltaic power, thereby ensures the power quality. Irradiance, the main factor that affects the output power of PV power generation, leads to the fluctuation of the output power due to its sudden change, and brings huge difficulty to the PV power prediction. The traditional forecasting method, which is largely based on physical and statistical models, may bring about the lag of the prediction results. Thus it is unable to provide accurate prediction results continuously. Relevant researches have indicated that the main reason for the sudden change of irradiance is the cloud coverage against the sunlight. The prediction of cloud coverage above the solar panel can be achieved. This is done by all-day sky observation and image acquisition using a ground-based remote sensing cloud detection equipment. Through the image analysis technique, it is possible to extract the feature of the clouds’ future movement. One meteorological instrument, Total Sky ImagerTM, is designed to capture the cloud coverage images. Once the images acquired, they can be used for correcting the irradiance data. Then the corrected data may be input to train a specialized artificial neural network (ANN) model. When the input data accumulated to a certain amount, the well-trained model can be applied in the forecast of the solar power output.
Rights: Nanyang Technological University
Fulltext Permission: restricted
Fulltext Availability: With Fulltext
Appears in Collections:EEE Student Reports (FYP/IA/PA/PI)

Files in This Item:
File Description SizeFormat 
FYP W1094-132 Final Report_Ye Penghao.pdf
  Restricted Access
Main article1.77 MBAdobe PDFView/Open
  Restricted Access
Reference844.43 kBAdobe PDFView/Open

Google ScholarTM


Items in DR-NTU are protected by copyright, with all rights reserved, unless otherwise indicated.