Enhancement of photovoltaic power farms using a new power prediction approach

2021 ◽  
Author(s):  
Ibrahim M. Ibrahim ◽  
Jacques Belanger ◽  
Ahmed S. Shehata ◽  
Ali I. Shehata ◽  
Andrew Davol
Keyword(s):  
Power Prediction ◽  
Photovoltaic Power ◽  
Prediction Approach

scholarly journals A Short-Term Photovoltaic Power Prediction Model Based on an FOS-ELM Algorithm

2017 ◽  
Vol 7 (4) ◽  
pp. 423 ◽  
Author(s):  
Jidong Wang ◽  
Ran Ran ◽  
Yue Zhou
Keyword(s):  
Prediction Model ◽  
Power Prediction ◽  
Short Term ◽  
Model Based ◽  
Photovoltaic Power

scholarly journals Photovoltaic Power Prediction Based on Scene Simulation Knowledge Mining and Adaptive Neural Network

2013 ◽  
Vol 2013 ◽  
pp. 1-6
Author(s):  
Dongxiao Niu ◽  
Yanan Wei ◽  
Yanchao Chen
Keyword(s):  
Neural Network ◽  
Prediction Model ◽  
Power Prediction ◽  
Adaptive Neural Network ◽  
Scene Simulation ◽  
Knowledge Mining ◽  
Photovoltaic Power ◽  
Model Combining ◽  
Neural Network Prediction ◽  
Network Prediction

Influenced by light, temperature, atmospheric pressure, and some other random factors, photovoltaic power has characteristics of volatility and intermittent. Accurately forecasting photovoltaic power can effectively improve security and stability of power grid system. The paper comprehensively analyzes influence of light intensity, day type, temperature, and season on photovoltaic power. According to the proposed scene simulation knowledge mining (SSKM) technique, the influencing factors are clustered and fused into prediction model. Combining adaptive algorithm with neural network, adaptive neural network prediction model is established. Actual numerical example verifies the effectiveness and applicability of the proposed photovoltaic power prediction model based on scene simulation knowledge mining and adaptive neural network.

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