This paper presents a novel approach for identification of photovoltaic systems in the residential sector. This is needed in response to increasing embedded generation on distribution networks. To date non-intrusive load monitoring techniques have focused mostly on identifying conventional loads on the customer side. This paper demonstrates the application of non-intrusive load monitoring to identify residential distributed generation, thereby enabling techniques to improve system flexibility and stability. The demonstrated methodology combines basic statistics with the Support Vector Machine technique, to identify PV load signatures. PMU measurements from the residential sector are used to aggregate measurements based largely on electric current records. The methods presented have applications for network operators, both in real time control and generation scheduling.
|Title of host publication||2020 31st Irish Signals and Systems Conference (ISSC 2020): Proceedings|
|Publisher||Institute of Electrical and Electronics Engineers Inc.|
|Publication status||Published - 30 Sep 2020|
|Event||Irish Signals and Systems Conference (ISSC) 2020 - Letterkenny Institute of Technology, Letterkenny, Ireland|
Duration: 11 Jun 2020 → 12 Jun 2020
|Name||2020 31st Irish Signals and Systems Conference, ISSC 2020|
|Conference||Irish Signals and Systems Conference (ISSC) 2020|
|Period||11/06/2020 → 12/06/2020|
FingerprintDive into the research topics of 'Non-Intrusive Load Monitoring Algorithm for PV Identification in the Residential Sector'. Together they form a unique fingerprint.
Student thesis: Doctoral Thesis › Doctor of Philosophy