Short Term Prediction of Photovoltaic Generation Output Based on Similar Days
Science Discovery
Volume 4, Issue 6, December 2016, Pages: 380-386
Received: Nov. 29, 2016; Published: Dec. 1, 2016
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Authors
Cui Hanjun, Institute of Water Resources and Hydro-Electric Engineering, Xi'an University of Technology, Xi'an, China
Yao Lixiao, Institute of Water Resources and Hydro-Electric Engineering, Xi'an University of Technology, Xi'an, China
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Abstract
Based on the analysis of the main weather factors that affect the output of the PV generation, a feedback based neural network prediction model based on similar days is proposed. From the historical data of the weather, the weather similar days are selected, the Elman neural network prediction model is established to predict the output power of the photovoltaic power generation combined with the similar days of the power generation and the similar days and the weather data.
Keywords
Photovoltaic Power Generation, Power Prediction, Neural Network
To cite this article
Cui Hanjun, Yao Lixiao, Short Term Prediction of Photovoltaic Generation Output Based on Similar Days, Science Discovery. Vol. 4, No. 6, 2016, pp. 380-386. doi: 10.11648/j.sd.20160406.16
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