基于可穿戴设备感知的智能家居能源优化

发布时间：2018-01-13 01:27

  本文关键词：基于可穿戴设备感知的智能家居能源优化　出处：《计算机研究与发展》2016年03期 　论文类型：期刊论文

  更多相关文章： 智能家居 能源优化 用户行为分析 可穿戴设备 智能电网

【摘要】：智能家居能源优化作为智能电网在居民侧的延伸是智能家居领域的重要分支.智能家居能源优化的目标是通过优化调度家居用电设备,满足用户的舒适需求和降低用电费用.其中,用户舒适度与人的行为密切相关,具有很强的主观性和不确定性,对用户行为及舒适度需求的分析是智能家居能源管理系统中的难点.因此提出了一种基于可穿戴设备传感数据分析的智能家居能源优化方法,主要包括:基于可穿戴设备传感器数据实时分析用户行为;利用神经网络建立用户行为到舒适度需求的映射,更新用户的舒适度需求;建立家居系统动态模型,并基于智能家居环境传感器数据对模型参数进行动态估计;提出基于模型预测控制(model predictive control,MPC)的智能家居能源优化求解方法.同时开发了智能家居能源优化的原型系统,通过搭建的智能家居实验平台,设计了4种典型用户行为情景,验证了所提方法对智能家居经济性和舒适性的提升.
[Abstract]:Intelligent optimization Home Furnishing energy smart grid as extending in the side of the residents is an important branch of intelligent Home Furnishing field. The purpose of intelligent Home Furnishing energy optimization by optimizing the scheduling Home Furnishing electric equipment to meet the user's demand of comfort and reduce electricity costs. Among them, the user comfort and human behavior is closely related with strong subjectivity and uncertainty analysis of user behavior and comfort needs is the difficulty of intelligent energy management system Home Furnishing. This paper presents an energy optimization method of intelligent Home Furnishing analysis sensor data based on wearable devices, mainly including: user behavior analysis of real-time sensor data based on wearable devices built by neural network; user behavior mapping comfort needs and comfort needs updating users; the establishment of Home Furnishing system dynamic model, and based on the model reference Home Furnishing intelligent sensor data environment The number of dynamic estimation; put forward based on the model predictive control (model predictive control, MPC) method Home Furnishing intelligent energy optimization. At the same time, the development of a prototype system of intelligent Home Furnishing energy optimization, through the intelligent Home Furnishing experimental platform, designed 4 kinds of typical user behavior scenarios, the proposed method is validated on the intelligent Home Furnishing economy and comfort.

【作者单位】： 智能网络与网络安全教育部重点实验室(西安交通大学);机械制造系统工程国家重点实验室(西安交通大学);加州大学伯克利分校伯克利教育联盟新加坡研究所;
【基金】：国家自然科学基金项目(61473218,61221063,U1301254) 国家“八六三”高技术研究发展计划基金项目(2012AA011003)~~
【分类号】：TU855;TP212.9
【正文快照】： Smart Home Energy Optimization Based on Cognition of Wearable Devices SensorDataChen Siyun1,Liu Ting1,Shen Chao1,Su Man1,Gao Feng2,Xu Zhanbo3,Shi Jiayue1,and Jia Zhanpei 11(Key Laboratory for Intelligent Networks and Network Security(Xi，

本文编号：1416871