Power generation forecasting model for photovoltaic array based on generic algorithm and BP neural network

High concentration photovoltaic is a new type of solar power generation mode, which has better photoelectric conversion rate but is more vulnerable to weather factors. Therefore, accurate and efficient forecasting methods have important significance of increasing the security and stability of the so...

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Bibliographic Details
Main Authors: Zhengqiu Yang, Yapei Cao, Jiapeng Xiu
Format: Conference Proceeding
Language:English
Subjects:
BP Neural network
Forecasting
Genetic algorithm
Genetic algorithms
Neural networks
Photovoltaic generation (PV)
Photovoltaic systems
Predictive models
Short-term forecasting
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Summary:High concentration photovoltaic is a new type of solar power generation mode, which has better photoelectric conversion rate but is more vulnerable to weather factors. Therefore, accurate and efficient forecasting methods have important significance of increasing the security and stability of the solar power station. This paper focuses on the short-term forecasting method which aims at forecasting power generation in five minutes. This paper uses BP neural network(BP-NN) as the basic forecasting model and applies generic algorithm(GA) to optimize the weights and thresholds of BP-NN. The experimental results show that, the prediction effect of this method is ideal.
ISSN:2376-5933
2376-595X
DOI:10.1109/CCIS.2014.7175764