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电熔镁砂生产用电需量多步智能预报方法
张菁雯; 柴天佑; 李慷
Source Publication自动化学报
ISSN0254-4156
2023
Volume49Issue:9Pages:1868-1877
Abstract电熔镁砂生产(Fused magnesia smelting process, FMSP)用电需量会出现先升后降的尖峰现象,当峰值达到用电需量限幅值,会将电熔镁炉(Fused magnesia furnace, FMF)拉闸断电.为避免尖峰时刻的不必要拉闸需要对需量尖峰进行识别,因此需要进行需量多步预报.利用电熔镁砂生产过程熔化电流闭环控制系统方程建立了由线性模型和未知非线性动态系统组成的需量多步预报模型,将系统辨识与深度学习相结合提出了端边云协同的电熔镁砂生产用电需量多步智能预报方法.采用电熔镁砂生产过程的工业大数据的实验结果验证了所提的预报方法可以准确预报需量的变化趋势.
Keyword需量多步预报 需量尖峰 端边云协同 自适应深度学习
DOI10.16383/j.aas.c220659
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Document Type期刊论文
Identifierhttp://ir.ia.ac.cn/handle/173211/56066
Collection学术期刊_自动化学报
Recommended Citation
GB/T 7714
张菁雯,柴天佑,李慷. 电熔镁砂生产用电需量多步智能预报方法[J]. 自动化学报,2023,49(9):1868-1877.
APA 张菁雯,柴天佑,&李慷.(2023).电熔镁砂生产用电需量多步智能预报方法.自动化学报,49(9),1868-1877.
MLA 张菁雯,et al."电熔镁砂生产用电需量多步智能预报方法".自动化学报 49.9(2023):1868-1877.
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