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	Prediction-based Manufacturing Center Self-adaptive Demand Side Energy Optimization in Cyber Physical Systems
	SUN Xinyao ; WANG Xue ; WU Jiangwei ; LIU Youda ; SUN Xinyao ; WANG Xue ; WU Jiangwei ; LIU Youda
	2016-03-30 ; 2016-03-30
关键词	cyber physical systems manufacturing center self-adaptive demand side management particle swarm optimization TM73 TP18
其他题名	Prediction-based Manufacturing Center Self-adaptive Demand Side Energy Optimization in Cyber Physical Systems
中文摘要	Cyber physical systems(CPS)recently emerge as a new technology which can provide promising approaches to demand side management(DSM),an important capability in industrial power systems.Meanwhile,the manufacturing center is a typical industrial power subsystem with dozens of high energy consumption devices which have complex physical dynamics.DSM,integrated with CPS,is an effective methodology for solving energy optimization problems in manufacturing center.This paper presents a prediction-based manufacturing center self-adaptive energy optimization method for demand side management in cyber physical systems.To gain prior knowledge of DSM operating results,a sparse Bayesian learning based componential forecasting method is introduced to predict24-hour electric load levels for specific industrial areas in China.From this data,a pricing strategy is designed based on short-term load forecasting results.To minimize total energy costs while guaranteeing manufacturing center service quality,an adaptive demand side energy optimization algorithm is presented.The proposed scheme is tested in a machining center energy optimization experiment.An AMI sensing system is then used to measure the demand side energy consumption of the manufacturing center.Based on the data collected from the sensing system,the load prediction-based energy optimization scheme is implemented.By employing both the PSO and the CPSO method,the problem of DSM in the manufacturing center is solved.The results of the experiment show the self-adaptive CPSO energy optimization method enhances optimization by 5%compared with the traditional PSO optimization method.; Cyber physical systems(CPS) recently emerge as a new technology which can provide promising approaches to demand side management(DSM), an important capability in industrial power systems. Meanwhile, the manufacturing center is a typical industrial power subsystem with dozens of high energy consumption devices which have complex physical dynamics. DSM, integrated with CPS, is an effective methodology for solving energy optimization problems in manufacturing center. This paper presents a prediction-based manufacturing center self-adaptive energy optimization method for demand side management in cyber physical systems. To gain prior knowledge of DSM operating results, a sparse Bayesian learning based componential forecasting method is introduced to predict 24-hour electric load levels for specific industrial areas in China. From this data, a pricing strategy is designed based on short-term load forecasting results. To minimize total energy costs while guaranteeing manufacturing center service quality, an adaptive demand side energy optimization algorithm is presented. The proposed scheme is tested in a machining center energy optimization experiment. An AMI sensing system is then used to measure the demand side energy consumption of the manufacturing center. Based on the data collected from the sensing system, the load prediction-based energy optimization scheme is implemented. By employing both the PSO and the CPSO method, the problem of DSM in the manufacturing center is solved. The results of the experiment show the self-adaptive CPSO energy optimization method enhances optimization by 5% compared with the traditional PSO optimization method.
语种	英语 ; 英语
内容类型	期刊论文
源URL	[http://ir.lib.tsinghua.edu.cn/ir/item.do?handle=123456789/144570]
专题	清华大学
推荐引用方式 GB/T 7714	SUN Xinyao,WANG Xue,WU Jiangwei,et al. Prediction-based Manufacturing Center Self-adaptive Demand Side Energy Optimization in Cyber Physical Systems[J],2016, 2016.
APA	SUN Xinyao.,WANG Xue.,WU Jiangwei.,LIU Youda.,SUN Xinyao.,...&LIU Youda.(2016).Prediction-based Manufacturing Center Self-adaptive Demand Side Energy Optimization in Cyber Physical Systems..
MLA	SUN Xinyao,et al."Prediction-based Manufacturing Center Self-adaptive Demand Side Energy Optimization in Cyber Physical Systems".(2016).

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