An efficient power load forecasting model based on the optimized combination

Author:

Fang Jicheng1,Shen Dongqin2,Li Xiuyi3,Li Huijia4

Affiliation:

1. College of Electronics and Information Engineering, Shanghai University of Electric Power, Shanghai 200090, China

2. School of Computer Science and Engineering, Nanjing University of Science and Technology, Nanjing 210094, China

3. School of Information Engineering, Nanjing University of Finance and Economics, Nanjing 210003, China

4. School of Management Science and Engineering, Central University of Finance and Economics, Beijing 100080, China

Abstract

The new energy industry gains more and more attention since the problem of resource scarcity and utilization of the renewable energy has become a global highlight issue. In this paper, we propose a new load forecasting model under the development of new energy industry by choosing the typical wind power as the key subject, which is also an important reference for other energy industries. The wind power load forecasting model is built based on optimized combination, which is forecasted and analyzed by the time series, the Markov and the gray forecasting models individually, and then combined by the optimized weighting coefficients. The method has overcome the limitations of poor adaptability of the single forecasting models and come out with an ideal result. Experimental results show our method has better performance compared with other related algorithms in different datasets.

Funder

National Key Research and Development Project

Beijing Natural Science Foundation of China

National Natural Science Foundation of China

Publisher

World Scientific Pub Co Pte Lt

Subject

Condensed Matter Physics,Statistical and Nonlinear Physics

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