稀疏多元传感器网络跟踪用电设备状态的序列解码与部署优化关键问题研究

项目名称： 稀疏多元传感器网络跟踪用电设备状态的序列解码与部署优化关键问题研究

项目编号： No.61202360

项目类型： 青年科学基金项目

立项/批准年度： 2013

项目学科： 计算机科学学科

项目作者： 王永才

作者单位： 清华大学

项目金额： 25万元

中文摘要： 全面准确的感知建筑内大量用电设备的实时耗电状态是建筑节能的基本问题。由于建筑中用电设备数量大、分布广、耗电状态动态变化，现有密集部署传感器网络（电流或功率）监测用电设备耗电状态的方法，面临网络规模大、部署运营成本高、数据采集困难、系统难以实施等难题，而在入户总线上进行高频采样与信号处理的无干扰负载监测方法，面临设备造价高与可扩展性不足的问题。 本项目发掘用电设备状态变化事件的时域稀疏性特点，提出采用稀疏多元传感器网络跟踪大量用电设备状态的可行方法。研究检测高维用电设备耗电状态的低维检测模型以稀疏传感网检测用电设备实时状态变化；基于条件半隐马尔科夫模型提出快速解码大量用电设备状态序列的算法；研究稀疏多元传感网的优化部署算法；并研究稀疏多元传感器网络跟踪用电设备状态的系统，以建立全面、准确、低成本、实时跟踪大量用电设备状态的理论方法和关键技术。

中文关键词： 压缩采样；网络；状态检测；智能电网；传感器网络

英文摘要： Tracking and breaking down the energy consumptions of massive electrical appliances is the basic problem for building energy saving. Because currently the electrical appliances are massive in buildings, which are broadly distributed and change states dynamically, it is general very challenging to tracking their states. Current fidelity monitoring approaches deploy dense power meter networks (current or power meter) to collect the power consumption data, however, such solutions generally form a large scale metering network, which suffers high deployment and maintenance costs, high data collection costs, and the difficulties in system establishment. Another method which conducts high-frequency sampling at the main power entrance to disaggregate the on/off switching states of the electrical appliances by processing the transient signal and pattern recognition, which is called Non-instrusive Load Monitoring. But such approaches require expensive device and the disaggregation method is generally not scalable because ambiguities will be general when many appliances have similar on/off switching patterns. To solve these difficulties, this project exploits the temporal sparseness character of the ON/OFF switching events of the massive electrical appliances, providing a feasible solution to use sparse, low-cost sensor

英文关键词： compressive sensing；network；state monitoring；smart grid；sensor network