scholarly journals Evaluating neural network and linear regression photovoltaic power forecasting models based on different input methods

2021 ◽  
Vol 7 ◽  
pp. 7601-7614
Author(s):  
Mutaz AlShafeey ◽  
Csaba Csáki
Keyword(s):  
Neural Network ◽  
Linear Regression ◽  
Forecasting Models ◽  
Photovoltaic Power ◽  
Power Forecasting

Linear Regression for Forecasting Photovoltaic Power Generation

2014 ◽  
Vol 494-495 ◽  
pp. 1771-1774 ◽  
Author(s):  
Hua Ping Guo ◽  
Shuang Hui Wu ◽  
Zhao Qing Wang ◽  
Chang An Wu
Keyword(s):  
Neural Network ◽  
Linear Regression ◽  
High Performance ◽  
Simple Structure ◽  
Power Station ◽  
Data Set ◽  
Photovoltaic Power ◽  
New Energy ◽  
Interpretable Model ◽  
Power Forecasting

One key issue for knowledge discovery is to build a model with simple structure, high performance and interpretability. Linear regression is simple and interpretable model comparing to other models such as neural network. This paper introduces linear regression into photovoltaic power forecasting. Experimental results on the data set collected by Zhongwei third photovoltaic power station of Ningxia Jinyang new energy Co., Ltd. show that, compared with neural network, linear regression performs better generated power forecasting.

Error analysis of hybrid photovoltaic power forecasting models: A case study of mediterranean climate

2015 ◽  
Vol 100 ◽  
pp. 117-130 ◽  
Author(s):  
Maria Grazia De Giorgi ◽  
Paolo Maria Congedo ◽  
Maria Malvoni ◽  
Domenico Laforgia
Keyword(s):  
Error Analysis ◽  
Mediterranean Climate ◽  
Forecasting Models ◽  
Photovoltaic Power ◽  
Power Forecasting
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