A New Method for Load Identification of Nonintrusive Energy Management System in Smart Home
In response to the governmental policy of savingenergy sources and reducing CO2, and carry out the residentquality of local; this paper proposes a new method for a nonintrusiveenergy management (NIEM) system in smart home toimplement the load identification of electric equipments andestablish the electric demand management. Non-intrusiveenergy management techniques were often based on powersignatures in the past, these techniques are necessary to beimproved for the results of reliability and accuracy ofrecognition. By using neural network (NN) in combinationwith genetic programming (GP) and turn-on transient energyanalysis, this study attempts to identify load demands andimprove recognition accuracy of non-intrusive energymanagingresults. The turn-on transient energy signature canimprove the efficiency of load identification and computationaltime under multiple operations.
smart home load identification artificial neural networks genetic programming NIEM
Hsueh-Hsien Chang Ching-Lung Lin
Dept. of Electronic Engineering Jin-Wen University of Science and Technology Taipei, Taiwan Dept. of Electrical Engineering Ming-Hsin University of Science and Technology Hsin-Chu, Taiwan
国际会议
2010 IEEE International Conference on e-Business Engineering(2010年电子商务工程国际研讨会 ICEBE 2010)
上海
英文
351-357
2010-11-10（万方平台首次上网日期，不代表论文的发表时间）