This dataset contains daily maximum load data with the average demand, customer count and PV capacity at two substations Arkana and Muchea, Western Australia used in the accepted IEEE Transactions on Power Systemspaper titled “The Use of Extreme Value Theory for Forecasting Long-Term Substation Maximum Electricity Demand” by Li and Jones (2019).  The dataset spans from 01/01/2008 to 30/06/2022, part history (01/01/2008 to 16/09/2018) and part forecast (17/09/2018 to 30/06/2022).  The dataset is beneficial to various research such as long-term load forecast.

DOI Link: 
10.21227/f1yn-1523
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[1] Yun Li, "The Use of Extreme Value Theory for Forecasting Long-Term Substation Maximum Electricity Demand ", IEEE Dataport, 2019. [Online]. Available: http://dx.doi.org/10.21227/f1yn-1523. Accessed: Jan. 28, 2025.
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doi = {10.21227/f1yn-1523},
url = {http://dx.doi.org/10.21227/f1yn-1523},
author = {Yun Li },
publisher = {IEEE Dataport},
title = {The Use of Extreme Value Theory for Forecasting Long-Term Substation Maximum Electricity Demand },
year = {2019} }
TY - DATA
T1 - The Use of Extreme Value Theory for Forecasting Long-Term Substation Maximum Electricity Demand
AU - Yun Li
PY - 2019
PB - IEEE Dataport
UR - 10.21227/f1yn-1523
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Yun Li. (2019). The Use of Extreme Value Theory for Forecasting Long-Term Substation Maximum Electricity Demand . IEEE Dataport. http://dx.doi.org/10.21227/f1yn-1523
Yun Li, 2019. The Use of Extreme Value Theory for Forecasting Long-Term Substation Maximum Electricity Demand . Available at: http://dx.doi.org/10.21227/f1yn-1523.
Yun Li. (2019). "The Use of Extreme Value Theory for Forecasting Long-Term Substation Maximum Electricity Demand ." Web.
1. Yun Li. The Use of Extreme Value Theory for Forecasting Long-Term Substation Maximum Electricity Demand [Internet]. IEEE Dataport; 2019. Available from : http://dx.doi.org/10.21227/f1yn-1523
Yun Li. "The Use of Extreme Value Theory for Forecasting Long-Term Substation Maximum Electricity Demand ." doi: 10.21227/f1yn-1523