scholarly journals Development of a System for Predicting Photovoltaic Power Generation and Detecting Defects Using Machine Learning

2016 ◽  
Vol 5 (10) ◽  
pp. 353-360 ◽  
Author(s):  
Seungmin Lee ◽  
Woo Jin Lee
Keyword(s):  
Machine Learning ◽  
Power Generation ◽  
Photovoltaic Power

scholarly journals Review on forecasting of photovoltaic power generation based on machine learning and metaheuristic techniques

2019 ◽  
Vol 13 (7) ◽  
pp. 1009-1023 ◽  
Author(s):  
Muhammad Naveed Akhter ◽  
Saad Mekhilef ◽  
Hazlie Mokhlis ◽  
Noraisyah Mohamed Shah
Keyword(s):  
Machine Learning ◽  
Power Generation ◽  
Photovoltaic Power ◽  
Metaheuristic Techniques

scholarly journals Research on Photovoltaic power prediction technology Based on Machine Learning

2021 ◽  
Vol 2087 (1) ◽  
pp. 012004
Author(s):  
Hongxia Li ◽  
Jianlin Li ◽  
Yang Mi
Keyword(s):  
Machine Learning ◽  
Power Generation ◽  
Prediction Method ◽  
Meteorological Factor ◽  
Power Prediction ◽  
Advantages And Disadvantages ◽  
Photovoltaic Power ◽  
Huge Impact ◽  
Basic Technology ◽  
Safety And Stability

Abstract In recent years, the photovoltaic power generation has obvious intermittent, randomness and volatility, and high permeability photovoltaic will have a huge impact on the safety and stability of the grid. The prediction of photovoltaic power generation is to improve the quality of photovoltaic grid, optimize grid scheduling, and ensure the basic technology of power grid safety and stability. In order to improve the prediction accuracy of photovoltaic power generation, this article will comprehensively carding and compare from 3 dimensions: photovoltaic power generation and meteorological factor correlation analysis, similar day selection, prediction method based on machine learning, and summarize the advantages and disadvantages of various methods. Further research has been put forward accordingly.

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