[Chen, Xiaoqiao] CALTECH, Comp & Math Sci Dept, Pasadena, CA 91125 USA.
通讯机构：
[Xiaoqiao Chen] C
Computing and Mathematical Science Department, California Institute of Technology, United States
语种：
英文
关键词：
Demand side management;Electric power plant loads;Electric power utilization;Forecasting;Predictive analytics;Regression analysis;Sales;Adaptive decomposition;Bayesian optimization algorithms;Electrical energy;Electrical energy management;Electricity-consumption;Industrial customer;Load forecasting;Short term load forecasting;Electric load forecasting
期刊：
International Journal of Electrical Power & Energy Systems
This work is supported by the National Natural Science Foundation of China (No. 51777014). Hunan Provincial Key Research and Development Program (No. 2018GK2057). Research projects funded by Department of Education of Hunan Province of China (18A124). Changsha Science and Technology Project (kq1901104). Hunan Graduate Research and Innovation Project (CX20190686).
机构署名：
本校为第一机构
院系归属：
电气与信息工程学院
摘要：
The electricity consumption by industrial customers in the society accounts for a significant proportion of the total electrical energy. Thus, it is of great significance for demand-side electrical energy management to develop an accurate method for short-term load forecasting for industrial customers. Unlike traditional load forecasting on system-level, the load forecasting of individual industrial customer is more challenging due to its significant volatility and uncertainty. We propose an adaptive decomposition method based on VMD and SampEn...
