dc.contributor.author |
Dash, S. |
|
dc.contributor.author |
Sodhi, R. |
|
dc.contributor.author |
Sodhi, B. |
|
dc.date.accessioned |
2021-08-12T22:28:09Z |
|
dc.date.available |
2021-08-12T22:28:09Z |
|
dc.date.issued |
2021-08-13 |
|
dc.identifier.uri |
http://localhost:8080/xmlui/handle/123456789/2381 |
|
dc.description.abstract |
Appliance-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.iso |
en_US |
en_US |
dc.subject |
Non-Intrusive Load Monitoring |
en_US |
dc.subject |
Semi-Intrusive Load Monitoring |
en_US |
dc.subject |
Clustered sensing |
en_US |
dc.subject |
Demand Response Management |
en_US |
dc.subject |
Direct Load Control |
en_US |
dc.title |
A Semi-Intrusive load monitoring approach for demand response applications |
en_US |
dc.type |
Article |
en_US |