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 manufactur...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 manufac^ring 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.展开更多
Cyber physical system(CPS)provides more powerful service by cyber and physical features through the wireless communication.As a kind of social organized network system,a fundamental question of CPS is to achieve servi...Cyber physical system(CPS)provides more powerful service by cyber and physical features through the wireless communication.As a kind of social organized network system,a fundamental question of CPS is to achieve service self-organization with its nodes autonomously working in both physical and cyber environments.To solve the problem,the social nature of nodes in CPS is firstly addressed,and then a formal social semantic descriptions is presented for physical environment,node service and task in order to make the nodes communicate automatically and physical environment sensibly.Further,the Horn clause is introduced to represent the reasoning rules of service organizing.Based on the match function,which is defined for measurement between semantics,the semantic aware measurement is presented to evaluate whether environment around a node can satisfy the task requirement or not.Moreover,the service capacity evaluation method for nodes is addressed to find out the competent service from both cyber and physical features of nodes.According to aforementioned two measurements,the task semantic decomposition algorithm and the organizing matrix are defined and the service self-organizing mechanism for CPS is proposed.Finally,examinations are given to further verify the efficiency and feasibility of the proposed mechanism.展开更多
先进信息技术在智能配用电系统(Smart power distribution and utilization system,SPDUS)中的广泛应用,加深了系统信息侧与电力物理侧的耦合程度,智能配用电系统已逐渐转变为信息-物理空间高度融合、信息资源与物理资源相互结合与协调...先进信息技术在智能配用电系统(Smart power distribution and utilization system,SPDUS)中的广泛应用,加深了系统信息侧与电力物理侧的耦合程度,智能配用电系统已逐渐转变为信息-物理空间高度融合、信息资源与物理资源相互结合与协调的智能配用电信息物理系统(Smart power distribution and utilization cyber physical system,SPDU-CPS)。本文重点从面向SPDU-CPS的网络攻击入侵检测、网络攻击防御保护以及自愈控制三个角度,对国内外相关技术的发展与挑战进行总结、梳理。在网络攻击入侵检测方面,总结了基于偏差类、基于特征类以及混合类网络攻击检测方法的检测思路及实施路径;在网络攻击防御保护方面,总结了提升信息网络防御能力的信息侧保护方法、基于资源优化配置和数据校正保护的物理侧保护方法以及融合两侧信息及保护功能的信息物理协同保护方法;在自愈控制方面,对传统电力物理侧自愈控制以及基于信息物理协同的自愈控制现有研究进行了归纳和整理。最后,结合SPDU-CPS的特点及发展趋势,对未来研究方向进行了展望。展开更多
基金Supported by National Natural Science Foundation of China(Grant No.61272428)PhD Programs Foundation of Ministry of Education of China(Grant No.20120002110067)
文摘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 manufac^ring 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.
基金Supported by the National Natural Science Foundation of China(61103069,71171148)the National High-Tech Research and Development Plan of China(″863″ Plan)(2012BAD35B01)+2 种基金the Innovation Program of Shanghai Municipal Education Commission(13YZ052)the Shanghai Committee of Science and Technology(11DZ1501703,11dz12106001)the Program of Shanghai Normal University(DXL125,DCL201302)
文摘Cyber physical system(CPS)provides more powerful service by cyber and physical features through the wireless communication.As a kind of social organized network system,a fundamental question of CPS is to achieve service self-organization with its nodes autonomously working in both physical and cyber environments.To solve the problem,the social nature of nodes in CPS is firstly addressed,and then a formal social semantic descriptions is presented for physical environment,node service and task in order to make the nodes communicate automatically and physical environment sensibly.Further,the Horn clause is introduced to represent the reasoning rules of service organizing.Based on the match function,which is defined for measurement between semantics,the semantic aware measurement is presented to evaluate whether environment around a node can satisfy the task requirement or not.Moreover,the service capacity evaluation method for nodes is addressed to find out the competent service from both cyber and physical features of nodes.According to aforementioned two measurements,the task semantic decomposition algorithm and the organizing matrix are defined and the service self-organizing mechanism for CPS is proposed.Finally,examinations are given to further verify the efficiency and feasibility of the proposed mechanism.
文摘先进信息技术在智能配用电系统(Smart power distribution and utilization system,SPDUS)中的广泛应用,加深了系统信息侧与电力物理侧的耦合程度,智能配用电系统已逐渐转变为信息-物理空间高度融合、信息资源与物理资源相互结合与协调的智能配用电信息物理系统(Smart power distribution and utilization cyber physical system,SPDU-CPS)。本文重点从面向SPDU-CPS的网络攻击入侵检测、网络攻击防御保护以及自愈控制三个角度,对国内外相关技术的发展与挑战进行总结、梳理。在网络攻击入侵检测方面,总结了基于偏差类、基于特征类以及混合类网络攻击检测方法的检测思路及实施路径;在网络攻击防御保护方面,总结了提升信息网络防御能力的信息侧保护方法、基于资源优化配置和数据校正保护的物理侧保护方法以及融合两侧信息及保护功能的信息物理协同保护方法;在自愈控制方面,对传统电力物理侧自愈控制以及基于信息物理协同的自愈控制现有研究进行了归纳和整理。最后,结合SPDU-CPS的特点及发展趋势,对未来研究方向进行了展望。
