电熔镁砂生产用电需量多步智能预报方法  

Multi-step Intelligent Forecasting Method for Electricity Demand of Fused Magnesia Production

作　　者：张菁雯 柴天佑 李慷 ZHANG Jing-Wen;CHAI Tian-You;LI Kang(State Key Laboratory of Synthetical Automation for Process Industries of Northeastern University,Shenyang 110819,China;School of Electronic and Electrical Engineering,University of Leeds,Leeds LS29JT,UK)

机构地区：[1]东北大学流程工业综合自动化国家重点实验室,中国沈阳110819 [2]利兹大学电子电气工程学院,英国利兹LS29JT

出　　处：《自动化学报》2023年第9期1868-1877,共10页Acta Automatica Sinica

基　　金：2020年度辽宁省科技重大专项计划(2020JH1/10100008);国家自然科学基金重大项目(61991404);一体化过程控制学科创新引智基地2.0(B08015);国家重点研发计划(2019YFB2006202)资助。

摘　　要：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.The electricity demand in a fused magnesia smelting process(FMSP)may first rise and then fall gradually,a phenomenon called demand peak.The fused magnesia furnace(FMF)will be switched off when the demand peak value reaches the limit.In order to avoid unnecessary FMF switching-off at the demand peak,it is necessary to identify the demand peak and predict next multi-step demand.In this paper,we develop a multi-step ahead demand forecasting model of the electricity demand based on the closed-loop control system of the smelting current in the FMSP.The multi-step ahead demand forecasting model combines an identifiable linear model with an unknown nonlinear dynamic system.A multi-step intelligent forecast method for electricity demand in the FMSP is proposed based on the system identification and deep learning with the edge-cloud coordination.The experimental results using real data of the FMSP in a fused magnesia factory verify that the proposed method can effectively predict the trend of demand.

关 键 词：需量多步预报 需量尖峰 端边云协同 自适应深度学习 

分 类 号：TQ175.4[化学工程—硅酸盐工业]