A New Method for Load Identification of Nonintrusive Energy Management System in Smart Home

Created by W.Langdon from gp-bibliography.bib Revision:1.3872

@InProceedings{Chang:2010:ICEBE,
  author =       "Hsueh-Hsien Chang and Ching-Lung Lin",
  title =        "A New Method for Load Identification of Nonintrusive
                 Energy Management System in Smart Home",
  booktitle =    "2010 IEEE 7th International Conference on e-Business
                 Engineering (ICEBE)",
  year =         "2010",
  month =        "10-12 " # nov,
  pages =        "351--357",
  abstract =     "In response to the governmental policy of saving
                 energy sources and reducing CO2, and carry out the
                 resident quality of local; this paper proposes a new
                 method for a non-intrusive energy management (NIEM)
                 system in smart home to implement the load
                 identification of electric equipments and establish the
                 electric demand management. Non-intrusive energy
                 management techniques were often based on power
                 signatures in the past, these techniques are necessary
                 to be improved for the results of reliability and
                 accuracy of recognition. By using neural network (NN)
                 in combination with genetic programming (GP) and
                 turn-on transient energy analysis, this study attempts
                 to identify load demands and improve recognition
                 accuracy of non-intrusive energy-managing results. The
                 turn-on transient energy signature can improve the
                 efficiency of load identification and computational
                 time under multiple operations.",
  keywords =     "genetic algorithms, genetic programming, GP, NIEM
                 system, electric demand management, electric
                 equipments, energy sources, governmental policy, load
                 demands, load identification, neural network,
                 non-intrusive energy management system, non-intrusive
                 energy management techniques, non-intrusive
                 energy-managing results, nonintrusive energy management
                 system, power signatures, recognition accuracy, smart
                 home, turn-on transient energy analysis, turn-on
                 transient energy signature, demand side management,
                 home automation, neural nets, power engineering
                 computing, power system transients",
  DOI =          "doi:10.1109/ICEBE.2010.24",
  notes =        "Also known as \cite{5704339}",
}

Genetic Programming entries for Hsueh-Hsien Chang Ching-Lung Lin

Citations