Based on meteorological factors and short-term load forecasting genetic programming

2010 ◽  
Author(s):  
Zhu Huan-rong ◽  
Li Ya-min ◽  
Meng Ia-mei
Keyword(s):  
Genetic Programming ◽  
Meteorological Factors ◽  
Load Forecasting ◽  
Short Term ◽  
Short Term Load Forecasting

scholarly journals Short-term Load Forecasting Model Considering Meteorological Factors

2019 ◽  
Vol 118 ◽  
pp. 02050
Author(s):  
Xi Yunhua ◽  
Zhu Haojun ◽  
Dong Nan
Keyword(s):  
Decision Tree ◽  
Meteorological Factors ◽  
Load Forecasting ◽  
Forecasting Model ◽  
Analysis Method ◽  
Decision Tree Algorithm ◽  
Characteristic Analysis ◽  
Short Term ◽  
Tree Algorithm ◽  
Short Term Load Forecasting

Because of the limitation of basic data and processing methods, the traditional load characteristic analysis method can not achieve user-level refined prediction. This paper builds a user-level short-term load forecasting model based on algorithms such as decision trees and neural networks in big data technology. Firstly, based on the grey relational analysis method, the influence of meteorological factors on load characteristics is quantitatively analyzed. The key factors are selected as input vectors of decision tree algorithm. This paper builds a category label for each daily load curve after clustering the user’s historical load data. The decision tree algorithm is used to establish classification rules and classify the days to be predicted. Finally, Elman neural network is used to predict the short-term load of a user, and the validity of the model is verified.

Research for Short-Term Load Forecasting Based on Linearization Meteorological Factors

2014 ◽  
Vol 596 ◽  
pp. 700-703
Author(s):  
Shun Hua Zhang
Keyword(s):  
Factor Model ◽  
Meteorological Factors ◽  
Load Forecasting ◽  
Meteorological Factor ◽  
Short Term ◽  
Power Load ◽  
Short Term Load Forecasting ◽  
Electricity Load ◽  
Heating Load ◽  
The Impact

With the development of economy in recent years, rapid growth of electricity demand, the cooling and heating load gets more and more big proportion of the total electricity load; the power load is influenced by meteorological factors which become more and more big. This topic will be based on short-term load forecasting in ANN (Artificial Neural Networks), conduct further research on the relationship between meteorological factors and power load, find the impact of the core meteorological factors of power load, and linear core meteorological factor model to establish the suitable for load forecasting based on ANN, make the forecasting to correctly reflect the meteorological conditions, improve the prediction accuracy of short-term load forecasting.

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