针对目前校园用电智能化管理的需求,设计了一种基于物联网技术的校园用电监控系统。系统无线传感网络以电能监测芯片CS5460A和ZigBee模块CC2530为核心,监测用电数据,定时将采集的电流、电压和电功率发送至上位机。上位机软件采用C#语言...针对目前校园用电智能化管理的需求,设计了一种基于物联网技术的校园用电监控系统。系统无线传感网络以电能监测芯片CS5460A和ZigBee模块CC2530为核心,监测用电数据,定时将采集的电流、电压和电功率发送至上位机。上位机软件采用C#语言在Visual studio 2012开发环境下设计而成,实现管理节点、处理数据以及根据监测结果向相应节点发送报警或通断电指令等功能。实践结果表明,该系统稳定可靠、精确度高、易于扩展和维护。展开更多
The Paris Agreement calls for maintaining a global temperature less than 2℃ above the pre-industrial level and pursuing efforts to limit the temperature increase even further to 1.5℃. To realize this objective and p...The Paris Agreement calls for maintaining a global temperature less than 2℃ above the pre-industrial level and pursuing efforts to limit the temperature increase even further to 1.5℃. To realize this objective and promote a low-carbon society, and because energy production and use is the largest source of global greenhouse-gas （GHG） emissions, it is important to efficiently manage energy demand and supply systems. This, in turn, requires theoretical and practical research and innovation in smart energy monitoring technologies, the identification of appropriate methods for detailed time-series analysis, and the application of these technologies at urban and national scales. Further, because developing countries contribute increasing shares of domestic energy consumption, it is important to consider the application of such innovations in these areas. Motivated by the mandates set out in global agreements on climate change and low-carbon societies, this paper focuses on the development of a smart energy monitoring system （SEMS） and its deployment in house- holds and public and commercial sectors in Bogor, Indonesia. An electricity demand prediction model is developed for each device using the Auto-Regression eXogenous model. The real-time SEMS data and time- series clustering to explore similarities in electricity consumption patterns between monitored units, such as residential, public, and commercial buildings, in Bogor is, then, used. These clusters are evaluated using peak demand and Ramadan term characteristics. The resulting energy- prediction models can be used for low-carbon planning.展开更多
文摘针对目前校园用电智能化管理的需求,设计了一种基于物联网技术的校园用电监控系统。系统无线传感网络以电能监测芯片CS5460A和ZigBee模块CC2530为核心,监测用电数据,定时将采集的电流、电压和电功率发送至上位机。上位机软件采用C#语言在Visual studio 2012开发环境下设计而成,实现管理节点、处理数据以及根据监测结果向相应节点发送报警或通断电指令等功能。实践结果表明,该系统稳定可靠、精确度高、易于扩展和维护。
文摘The Paris Agreement calls for maintaining a global temperature less than 2℃ above the pre-industrial level and pursuing efforts to limit the temperature increase even further to 1.5℃. To realize this objective and promote a low-carbon society, and because energy production and use is the largest source of global greenhouse-gas （GHG） emissions, it is important to efficiently manage energy demand and supply systems. This, in turn, requires theoretical and practical research and innovation in smart energy monitoring technologies, the identification of appropriate methods for detailed time-series analysis, and the application of these technologies at urban and national scales. Further, because developing countries contribute increasing shares of domestic energy consumption, it is important to consider the application of such innovations in these areas. Motivated by the mandates set out in global agreements on climate change and low-carbon societies, this paper focuses on the development of a smart energy monitoring system （SEMS） and its deployment in house- holds and public and commercial sectors in Bogor, Indonesia. An electricity demand prediction model is developed for each device using the Auto-Regression eXogenous model. The real-time SEMS data and time- series clustering to explore similarities in electricity consumption patterns between monitored units, such as residential, public, and commercial buildings, in Bogor is, then, used. These clusters are evaluated using peak demand and Ramadan term characteristics. The resulting energy- prediction models can be used for low-carbon planning.
