Abstract
The NREL Wattile extension, nrelWattileExt, provides an interface between SkySpark, an energy management and analytics software, and Wattile, an NREL-developed Python package for probabilistic prediction of building energy consumption. Wattile models predict discrete quantiles of the probability distribution of a target quantity (typically energy consumption) using the historical time series data from one or more predictors (typically weather data). Within SkySpark, predictions from Wattile models can be used for measurement & verification of building performance, detection of energy anomalies, and fault detection.
Related to: https://github.com/NREL/Wattile
- Developers:
-
Frank, Stephen [1] ; Smith, Joseph [1] ; Eslinger, Hannah [1] ; Donson, James [1]
- National Renewable Energy Laboratory (NREL), Golden, CO (United States)
- Release Date:
- 2024-06-13
- Project Type:
- Open Source, Publicly Available Repository
- Software Type:
- Scientific
- Programming Languages:
-
Dockerfile
Fantom
- Licenses:
-
BSD 3-clause "New" or "Revised" License
- Sponsoring Org.:
-
USDOEPrimary Award/Contract Number:AC36-08GO28308
- Code ID:
- 128854
- Site Accession Number:
- NREL SWR-24-73
- Research Org.:
- National Renewable Energy Laboratory (NREL), Golden, CO (United States)
- Country of Origin:
- United States
Citation Formats
Frank, Stephen, Smith, Joseph, Eslinger, Hannah, and Donson, James.
nrelWattileExt (SkySpark Wattile Extension) [SWR-24-73].
Computer Software.
https://github.com/NREL/nrelWattileExt.
USDOE.
13 Jun. 2024.
Web.
doi:10.11578/dc.20240916.1.
Frank, Stephen, Smith, Joseph, Eslinger, Hannah, & Donson, James.
(2024, June 13).
nrelWattileExt (SkySpark Wattile Extension) [SWR-24-73].
[Computer software].
https://github.com/NREL/nrelWattileExt.
https://doi.org/10.11578/dc.20240916.1.
Frank, Stephen, Smith, Joseph, Eslinger, Hannah, and Donson, James.
"nrelWattileExt (SkySpark Wattile Extension) [SWR-24-73]." Computer software.
June 13, 2024.
https://github.com/NREL/nrelWattileExt.
https://doi.org/10.11578/dc.20240916.1.
@misc{
doecode_128854,
title = {nrelWattileExt (SkySpark Wattile Extension) [SWR-24-73]},
author = {Frank, Stephen and Smith, Joseph and Eslinger, Hannah and Donson, James},
abstractNote = {The NREL Wattile extension, nrelWattileExt, provides an interface between SkySpark, an energy management and analytics software, and Wattile, an NREL-developed Python package for probabilistic prediction of building energy consumption. Wattile models predict discrete quantiles of the probability distribution of a target quantity (typically energy consumption) using the historical time series data from one or more predictors (typically weather data). Within SkySpark, predictions from Wattile models can be used for measurement & verification of building performance, detection of energy anomalies, and fault detection.
Related to: https://github.com/NREL/Wattile},
doi = {10.11578/dc.20240916.1},
url = {https://doi.org/10.11578/dc.20240916.1},
howpublished = {[Computer Software] \url{https://doi.org/10.11578/dc.20240916.1}},
year = {2024},
month = {jun}
}