E3S Web Conf.
Volume 213, 20202nd International Conference on Applied Chemistry and Industrial Catalysis (ACIC 2020)
|Number of page(s)||4|
|Section||Environmental Chemical Research and Energy-saving Technology Application|
|Published online||01 December 2020|
Power Load Forecasting Model Based on Grey Neural Network Regression Combination
Economic and Technological Research Institute of State Grid Hebei Electric Power Co., Ltd, No. 27, Fuqiang Street, Yuhua District, Shijiazhuang, Hebei, 050022, China
2 North China Electric Power University, Beijing, 102206, China
* Corresponding author: NCEPUliuchen@163.com
Due to the limitations of a single power load forecasting model, the power load forecasting cannot be performed well. In order to obtain a greater closeness to predict results with actual data, this paper presents the power load forecasting model based on gray neural network combined return to Guangzhou, 2010 - 2019 on actual data for example, the results show that: As used herein, the combined model method has high accuracy and strong use value.
© The Authors, published by EDP Sciences, 2020
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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