Application of Grey LS-SVM in Mid and Long Term Power Load Forecasting

2009 ◽  
Author(s):  
Fuwei Zhang ◽  
Wei Chen
Keyword(s):  
Load Forecasting ◽  
Power Load ◽  
Power Load Forecasting

Study on Medium and Long Term Power Load Forecasting in Cold Regions

2012 ◽  
Vol 170-173 ◽  
pp. 3472-3477
Author(s):  
Jian Li ◽  
Zhen Huan Jiang
Keyword(s):  
Yellow River ◽  
Load Forecasting ◽  
Qinling Mountains ◽  
Affecting Factors ◽  
Cold Regions ◽  
Road Map ◽  
Power Load ◽  
Power Load Forecasting ◽  
Northeast Of China

A large part of Qinling Mountains and north of the Yellow River in China belongs to cold regions, so accurate forecasting of power load in cold regions plays an important role in economic development. This article summarizes the basic theory of power load, power load forecasting and medium and long term load forecasting power load forecasting in cold regions, studies on the affecting factors of the medium and long term power load in cold regions, proposes the study road map on the affecting factors of the medium and long term load in cold regions and analyzes empirically the medium and long term power load forecasting in the northeast of China.

The Optimization Selection of Input Variables for Mid-Term Power Load Forecasting Based on Gradually Similar Method

2014 ◽  
Vol 610 ◽  
pp. 274-278
Author(s):  
Ji Ping Zhu
Keyword(s):  
Load Forecasting ◽  
Economic Indicators ◽  
Shanxi Province ◽  
Forecasting Accuracy ◽  
Power Load ◽  
Power Load Forecasting ◽  
Simulation Results ◽  
Input Variables ◽  
Selection Of

Gradually similar method is putted forward in the paper. The rules of selecting the independents are analyzed. And the foundations of that the variable has been permitted to enter to or eliminate from the model are described. The idea is to forecast medium and long term load of shanxi Province with using this method, and reasonable to select the economic indicators having influence on the power load. Then, these economic indicators were screened by the gradually similar method. Gradually similar method new putted forward is used for the optimization selection of the model input variables, and forecasting accuracy is discussed .Simulation results show that the method brought forward is right and feasible.

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