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dc.contributor.authorDash, S.-
dc.contributor.authorSodhi, R.-
dc.contributor.authorSodhi, B.-
dc.date.accessioned2021-08-12T22:28:09Z-
dc.date.available2021-08-12T22:28:09Z-
dc.date.issued2021-08-13-
dc.identifier.urihttp://localhost:8080/xmlui/handle/123456789/2381-
dc.description.abstractAppliance-Load Monitoring (ALM) is essential for several demand-response (DR) programs. The techniques used for this purpose are broadly classified into two types: 1) Intrusive Load Monitoring (ILM), and 2) Non-Intrusive Load Monitoring (NILM). This paper proposes a semi-intrusive load monitoring (SILM) technique to exploit the bests of both. The method does not use any disaggregation algorithm; instead, it’s an instrumentation approach to monitor the power consumption of appliances. First, it groups all appliances of a residential house in some clusters and then monitors those, in near realtime, using only one sensing-unit per cluster. A lab-scale testbed is developed to verify the claims of the proposed method. Test results demonstrate the monitoring and controlling capability and prove the cost-effectiveness of the technique. Raspberry Pi is used as the programming platform along with Python programming language.en_US
dc.language.isoen_USen_US
dc.subjectNon-Intrusive Load Monitoringen_US
dc.subjectSemi-Intrusive Load Monitoringen_US
dc.subjectClustered sensingen_US
dc.subjectDemand Response Managementen_US
dc.subjectDirect Load Controlen_US
dc.titleA Semi-Intrusive load monitoring approach for demand response applicationsen_US
dc.typeArticleen_US
Appears in Collections:Year-2019

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