Medium and long term load forecasting method of "coal to electricity" based on optimal combination forecasting

2021 ◽  
Author(s):  
Zeyuan Shen ◽  
Song Wei ◽  
Zhao Haibo ◽  
Zuo Zuowen ◽  
Huang He ◽  
...  
Keyword(s):  
Load Forecasting ◽  
Optimal Combination ◽  
Combination Forecasting ◽  
Forecasting Method

scholarly journals Application of Combination Forecast Model in the Medium and Long Term Power Load Forecast

2012 ◽  
Vol 490-495 ◽  
pp. 1362-1366 ◽  
Author(s):  
Ke Zhao ◽  
Lin Gan ◽  
Zhong Wang ◽  
Yan Xiong
Keyword(s):  
Load Forecasting ◽  
Forecast Model ◽  
Combination Forecast ◽  
Combination Forecasting ◽  
Power Load ◽  
Forecasting Method ◽  
Model Predictions ◽  
High Prediction ◽  
Predicted Values

For seasonal and long-term power load forecasting problem, this paper presents an optimal combination forecasting method, which can optimize the combination of multiple predictive models. Optimize the combination of the two model predictions with two models as an example, which are the gray GM(1,1) model and linear regression model, and finally compare the predicted values of combination with the real values. The results show that: the combination forecasting method has a high prediction accuracy, and the error is very small.

A Multi-Dimensional Method for Nodal Load Forecasting

2014 ◽  
Vol 1070-1072 ◽  
pp. 708-717
Author(s):  
Zhi Yuan Pan ◽  
Chao Nan Liu ◽  
Jing Wang ◽  
Yong Wang
Keyword(s):  
Energy Flow ◽  
Load Forecasting ◽  
Least Square ◽  
Support Vector ◽  
Forecasting Accuracy ◽  
Combination Forecasting ◽  
Forecasting Method ◽  
Load Pattern ◽  
And Control

The intelligent dispatch and control of future smart grid demands grasping of any nodal load pattern in the general great grid, therefore to realize the load forecasting of any nodal load is quite important. To solve this problem, focusing on overcoming the weakness of isolated nodal load forecasting and based on the correlation analysis, this paper proposes a multi-dimensional nodal load forecast system and corresponding method for effective prediction of any nodal load of the grid. This system includes topology partitioning of the grid energy flow according to layers and regions, basic forecasting unit composed of each layer’s total amount of load and its nodal loads, and combination forecasting for any node. The forecasting method is based on techniques including the multi-output least square support vector machine, Kalman filtering and the approximate optimal prediction. A case study shows that the multi-dimensional nodal load forecasting model helps to improve the forecasting accuracy, and has practical prospects.

Mid-Long Term Load Forecasting Based on Fuzzy Soft Set and D-S Evidence Theory

2013 ◽  
Vol 732-733 ◽  
pp. 682-685
Author(s):  
Dong Xiao Niu ◽  
Lei Lei Fan ◽  
Qiao Ling Wu ◽  
Qing Guo Ma ◽  
Qin Liang Tan
Keyword(s):  
Load Forecasting ◽  
Evidence Theory ◽  
Soft Set ◽  
Forecasting Model ◽  
Fuzzy Soft Set ◽  
Combination Forecasting ◽  
Proposed Model ◽  
Combination Forecasting Model ◽  
Predicted Values

According to errors between the predicted values and the actual values, this paper establishes a fuzzy soft set in the form of membership function, then utilizes Dempster combination rule in evidence theory to synthesize the prediction results to obtain the weights of each single model, and thus builds a new hybrid combination forecasting model. The example shows that the proposed model can effectively improve the accuracy of mid-long term load forecasting, and is more accurate and credible than the combination forecasting model based on entropy or simply fuzzy soft set theory.

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