标题: | 基于非侵入式负载监测电表之电器状态与使用者行为对应 Mapping Appliance States to High-Level Users’ Behavior based on Nonintrusive Load Monitoring Meter |
作者: | 朱春梅 Chu, Chun-Mei 曹孝栎 Tsao, Shiao-Li 资讯科学与工程研究所 |
关键字: | 智慧电表;使用者行为;非侵入式电表;Smart Meter;Users’ Behavior;NILM Meter |
公开日期: | 2011 |
摘要: | 在这篇论文中,我们设计了一个能源管理系统,其中包含了非侵入式负载监测(nonintrusive load monitoring)电表,闸道器,伺服器与使用者界面装置。非侵入式负载量测电表可辨识出电器的种类与状态及量测其耗电资讯,以OSGi平台为基础的闸道器为伺服器与建立在Android平板上的使用者界面提供服务。Android应用程式包含了四个功能:设定电器的位置与资讯,展示电器的及时状态与以图表的方式呈现耗电的历史资讯,住户可设定每个月的最大耗电量以管理电器的使用,和及时或设定某个时间对电器执行开关的动作。 除此之外,我们在能源管理系统之上加入一个主动分享个人行为的应用服务。传统使用者行为的侦测大多仰赖大量的感测器与复杂的监控设备,价格昂贵、部建不易、且侵入式的方式让人较难接受。在此篇论文中,我们考虑以使用者用电(或是使用电器)的足迹加以侦测使用者行为,并透过非侵入式负载监测电表侦测电器状态改变,我们利用电器状态改变与使用者标记的行为时间点找出它们之间的序列模式(sequential patterns),并用此序列模式来侦测出使用者的行为。 In this paper, we design and implement an energy management system (EMS) consisting of a nonintrusive load monitoring (NILM) smarter meter, gateway, server and mobile device. The NILM smarter meter provides a low-cost solution to recognize the states of each appliance in the house and disaggregate the power consumptions of a house. The gateway is based on Open Service Gateway Initiative (OSGi) framework to provide services for servers and mobile devices such as Android pad. The Android application consists of four components: the settings set configuration of appliances and location, the monitor used to show the state of appliances in real-time and the charts of historic data, the management can set the maximum power consumption of a month by the inhabitants, and control used to control the appliances now or at the time that inhabitants configured. Based on the proposed EMS, we further implement a user behavior sharing service. Conventional user behavior detection relies on a large amount of sensors, complicated and expensive monitoring devices. However, such monitoring system suffers from deployment problem and intrusive monitoring concerns. Therefore, we consider detecting user behavior based on NILM smart meter which provides us a sequence of appliance usage patterns. We process sequential patterns of appliance usage and derive high level users’ behaviors. |
URI: | http://140.113.39.130/cdrfb3/record/nctu/#GT079955546 http://hdl.handle.net/11536/50462 |
显示于类别: | Thesis |