Using a self-adaptive grey fractional weighted model to forecast Jiangsu's electricity consumption in China
Using a self-adaptive grey fractional weighted model to forecast Jiangsu's electricity consumption in China
复制标题
利用自适应灰色分数加权模型预测江苏省用电量
DOI：
10.1016/j.energy.2019.116417
复制
发表时间：
2020
期刊：
影响因子：
9
通讯作者：
Ding Song
中科院分区：
文献类型：
--
作者：
Zhu Xiaoyue;Dang Yaoguo;Ding Song
The remarkable prediction performance of electricity consumption has always assumed particular importance for electric power utility planning and economic development. On account of the complexity and uncertainty of the electricity system, this paper establishes a self-adaptive grey fractional weighted model to predict Jiangsu's electricity consumption, which efficiently enhances the prediction quality of electricity consumption. This newly constructed grey model introduces the fractional weighted coefficients to design a novel initial condition. Compared with the old one in the conventional grey models, the newly optimized initial condition has a flexible structure, which has advantages in capturing the dynamic characteristics of the electricity consumption observations. In addition, to further promote the forecasting precision, the adjustable fractional weighted coefficients and corresponding time parameter of the initial condition are estimated by utilizing the Particle Swarm Algorithm (PSO). Furthermore, five competing models are employed to forecast Jiangsu's electricity consumption in China, which certifies the validity of the established model. Experimental results illustrate that the newly designed model has significant advantages over other five competing models. According to the forecasted results, electricity consumption in Jiangsu Province is expected to reach 6778 billion kilowatt-hours in 2020, while the growth rate will fall down by 1.11%. Therefore, several proposals are made for decision-makers. (C) 2019 Elsevier Ltd. All rights reserved.
