Accurate short-term load forecasting (STLF) plays an increasingly important role in reliable and economical power system operations. This dataset contains The University of Texas at Dallas (UTD) campus load data with 13 buildings, together with 20 weather and calendar features. The dataset spans from 01/01/2014 to 12/31/2015 with an hourly resolution. The dataset is beneficial to various research such as STLF.

Dataset Files

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[1] Jie Zhang, Cong Feng, "Short-term load forecasting data with hierarchical advanced metering infrastructure and weather features", IEEE Dataport, 2019. [Online]. Available: http://dx.doi.org/10.21227/jdw5-z996. Accessed: Dec. 04, 2024.
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doi = {10.21227/jdw5-z996},
url = {http://dx.doi.org/10.21227/jdw5-z996},
author = {Jie Zhang; Cong Feng },
publisher = {IEEE Dataport},
title = {Short-term load forecasting data with hierarchical advanced metering infrastructure and weather features},
year = {2019} }
TY - DATA
T1 - Short-term load forecasting data with hierarchical advanced metering infrastructure and weather features
AU - Jie Zhang; Cong Feng
PY - 2019
PB - IEEE Dataport
UR - 10.21227/jdw5-z996
ER -
Jie Zhang, Cong Feng. (2019). Short-term load forecasting data with hierarchical advanced metering infrastructure and weather features. IEEE Dataport. http://dx.doi.org/10.21227/jdw5-z996
Jie Zhang, Cong Feng, 2019. Short-term load forecasting data with hierarchical advanced metering infrastructure and weather features. Available at: http://dx.doi.org/10.21227/jdw5-z996.
Jie Zhang, Cong Feng. (2019). "Short-term load forecasting data with hierarchical advanced metering infrastructure and weather features." Web.
1. Jie Zhang, Cong Feng. Short-term load forecasting data with hierarchical advanced metering infrastructure and weather features [Internet]. IEEE Dataport; 2019. Available from : http://dx.doi.org/10.21227/jdw5-z996
Jie Zhang, Cong Feng. "Short-term load forecasting data with hierarchical advanced metering infrastructure and weather features." doi: 10.21227/jdw5-z996