aemo: Wind power data from 22 wind farms in south eastern Australia
In jakmes/onlineVAR: Online Fitting of Time-Adaptive Lasso Vector Auto Regression
Description
Usage
Format
Source
References
Description
Wind power data from 22 wind farms in south eastern Australia provided by
the Australian Electricity Market Operator (AEMO) and pre-processed by Jethro
Browell and Stefanos Delikaraoglou. The data set contains data from 2013
in 5 minute resolution and is a subset of the data set provided
at http://dx.doi.org/10.15129/9e1d9b96-baa7-4f05-93bd-99c5ae50b141.
Usage
1
data("aemo")
Format
A data frame with 22 columns for each wind farm and 105120 rows.
Source
http://dx.doi.org/10.15129/9e1d9b96-baa7-4f05-93bd-99c5ae50b141
References
Dowell J, Pinson P (2016), Very-Short-Term Probabilistic Wind Power Forecasts
by Sparse Vector Autoregression. IEEE Transactions on Smart Grid, 7(2),
763-770, DOI: 10.1109/TSG.2015.2424078
jakmes/onlineVAR documentation built on May 4, 2019, 4:23 p.m.
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Description Usage Format Source References
Description
Wind power data from 22 wind farms in south eastern Australia provided by the Australian Electricity Market Operator (AEMO) and pre-processed by Jethro Browell and Stefanos Delikaraoglou. The data set contains data from 2013 in 5 minute resolution and is a subset of the data set provided at http://dx.doi.org/10.15129/9e1d9b96-baa7-4f05-93bd-99c5ae50b141.
Usage
1 | data("aemo")
|
Format
A data frame with 22 columns for each wind farm and 105120 rows.
Source
http://dx.doi.org/10.15129/9e1d9b96-baa7-4f05-93bd-99c5ae50b141
References
Dowell J, Pinson P (2016), Very-Short-Term Probabilistic Wind Power Forecasts by Sparse Vector Autoregression. IEEE Transactions on Smart Grid, 7(2), 763-770, DOI: 10.1109/TSG.2015.2424078
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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