Abstract
As utility data, such as smart meter data, becomes more broadly available, there is general interest in using it to improve utility operations and enable adoption of other advanced technology - such as solar photovoltaics (PV), energy storage, and controls. We explore one such use case - identifying electric resistance water heaters from smart meter data, as well as characterizing their potential for load-shifting to support grid voltage stability under high-penetration PV adoption. This paper shows the limitation of typical 15-minute data, and how shortterm capture of additional 1-minute data is needed to enable the desired application. Results indicate about 4 kWh water heating load can be shifted to align with peak sun hours in a low use home. This methodology is an example, and can be adapted to other grid-integrated efficient building use cases.
| Original language | American English |
|---|---|
| Number of pages | 4 |
| State | Published - 2018 |
| Event | 4th International Workshop on Non-Intrusive Load Monitoring - Austin, Texas Duration: 7 Mar 2018 → 8 Mar 2018 |
Conference
| Conference | 4th International Workshop on Non-Intrusive Load Monitoring |
|---|---|
| City | Austin, Texas |
| Period | 7/03/18 → 8/03/18 |
Bibliographical note
Available online from the workshop website: http://nilmworkshop.org/2018/NREL Publication Number
- NREL/CP-5500-70891
Keywords
- load disaggregation
- non-intrusive load monitoring
- photovoltaics
- smart meter
