Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
8112569 | Renewable and Sustainable Energy Reviews | 2016 | 11 Pages |
Abstract
The development of home energy management have increased due to energy saving. Instead of Intrusive Load Monitoring (IALM) which requires individual sensor for each appliance, Non-Intrusive Appliance Load Monitoring (NIALM) is an advanced low-cost system that requires fewer sensors and disaggregates load data in a different way. NIALM is a study to determine energy consumption of individual appliances measured at a single power source point. This system disaggregates data from a total power load and analyses power consumption of an appliance so that consumer can monitor the total power usage of a building. This paper reviews several feature extractions, state-of-the-art load signatures and disaggregation algorithms used for appliance recognition in NIALM method.
Keywords
FSMFactorial hidden Markov modelHMMSMPSCPURBFMLPNon-intrusive appliance load monitoringROCUECliquid-crystal displayDSPFFTEMIEPULCDmitFast Fourier transformelectromagnetic interferenceFinite state machinesEnergy savingneural-networkPower factorRadial basis functionSVMSupport vector machinesHidden Markov modelDemand side managementMassachusetts Institute of TechnologyCentral Processor UnitDigital signal processingMultilayer perceptronHeLPreceiver operating characteristic
Related Topics
Physical Sciences and Engineering
Energy
Renewable Energy, Sustainability and the Environment
Authors
Nur Farahin Esa, Md Pauzi Abdullah, Mohammad Yusri Hassan,