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Raven and Teal integration #177

Merged
merged 37 commits into from
Mar 30, 2023
Merged

Raven and Teal integration #177

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9a2a162
nuclear case notebook for multiperiod, TEAL cashflows added to determ…
GabrielSoto-INL Aug 19, 2022
78971db
some more commenting and year-fixes
GabrielSoto-INL Aug 19, 2022
b2d9390
results via TEAL NPV generation match DISPATCHESresults
GabrielSoto-INL Aug 22, 2022
abd1a37
TEAL NPV results match original notebook. Original notebook H2 mole f…
GabrielSoto-INL Aug 23, 2022
3de7f7b
printing NPV value from optimization
GabrielSoto-INL Aug 29, 2022
64540cc
Integration of RAVEN synthetic history generation
annawrobe Sep 2, 2022
8001697
fix to stochastic loop, TEAL results match previous nb
GabrielSoto-INL Sep 16, 2022
f5a512d
moving helper methods to separate script
GabrielSoto-INL Sep 16, 2022
6d46704
Merge branch 'main' into tealnb
GabrielSoto-INL Sep 16, 2022
5bd4bff
added ROM sampling, some bugs remain
annawrobe Sep 20, 2022
36a91f8
cleanup
GabrielSoto-INL Sep 20, 2022
0d1882e
Merge branch 'tealnb' into synhist
GabrielSoto-INL Sep 20, 2022
299d5c6
new notebook with both TEAL metrics and synthetic history generation
GabrielSoto-INL Sep 28, 2022
fc367e3
ARMA model files, synth training data, and README
GabrielSoto-INL Sep 28, 2022
e9dc290
Merge branch 'main' into synhist
GabrielSoto-INL Sep 28, 2022
9532ad2
updated instructions on training ARMA model, removing committed model
GabrielSoto-INL Nov 14, 2022
6be3ac0
updating external ROM loader and TEAL imports to match pip installed …
GabrielSoto-INL Nov 29, 2022
189097d
Merged with main - resolved conflicts
radhakrishnatg Feb 3, 2023
e725103
Merge branch 'main' of https://github.com/gmlc-dispatches/dispatches …
radhakrishnatg Feb 3, 2023
6134983
Updated the notebook to use new MultiPeriodModel class
radhakrishnatg Feb 6, 2023
435f48a
Moved scripts to util folder
radhakrishnatg Feb 7, 2023
55b5d8a
Adding init file
radhakrishnatg Feb 7, 2023
ac7856a
updates to ARMA generation guidelines, hopefully clearer usage of years
GabrielSoto-INL Feb 28, 2023
36ce1f4
replacing old LMP signal png
GabrielSoto-INL Feb 28, 2023
de44c70
fixing indexing of generated synth hist years, updating comp lifetime…
GabrielSoto-INL Feb 28, 2023
105c427
Added function to generate synthetic histories
radhakrishnatg Mar 10, 2023
b8acdf0
Re-run notebook
radhakrishnatg Mar 10, 2023
4d005d8
Merge branch 'main' of https://github.com/gmlc-dispatches/dispatches …
radhakrishnatg Mar 16, 2023
f6fe206
Run Raven within Jupyter notebook
radhakrishnatg Mar 16, 2023
d8b4911
Merge branch 'main' into teal-integration
ksbeattie Mar 20, 2023
a1e3a6f
Merge branch 'main' into teal-integration
lbianchi-lbl Mar 29, 2023
6962aa8
Exclude notebooks requiring TEAL from notebooks-checks runs
lbianchi-lbl Mar 29, 2023
56877b0
Update action tag to resolve warnings
lbianchi-lbl Mar 29, 2023
01b614b
Add step to test notebook execution in RAVEN/TEAL environment
lbianchi-lbl Mar 29, 2023
618715a
Get list of pinned package versions after installation
lbianchi-lbl Mar 29, 2023
026d0d9
Add raises-exception to cells affected by solver failure on GHA
lbianchi-lbl Mar 29, 2023
cbeef5b
Add skip directives for the affected cells instead to be more explicit
lbianchi-lbl Mar 30, 2023
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1 change: 1 addition & 0 deletions .gitignore
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Expand Up @@ -52,3 +52,4 @@ auto-save-list
*_results/
*_results_*/
sim_*/
dispatches/case_studies/nuclear_case/ARMA_Model/output/
Binary file added dispatches/case_studies/nuclear_case/ARMA_LMP_signals.png
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6 changes: 6 additions & 0 deletions dispatches/case_studies/nuclear_case/ARMA_Model/ARMA_pointer_2018_2021_to2045.csv
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@@ -0,0 +1,6 @@
scaling,Year,filename
1,2018,Price_2018.csv
1,2019,Price_2019.csv
1,2020,Price_2020.csv
1,2021,Price_2021.csv
1,2045,Price_2021.csv
131 changes: 131 additions & 0 deletions dispatches/case_studies/nuclear_case/ARMA_Model/ARMA_train.xml
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<?xml version="1.0" ?>
<Simulation verbosity="debug">
<RunInfo>
<WorkingDir>output</WorkingDir>
<Sequence>load, train, meta, serialize, sample</Sequence>
</RunInfo>

<Files>
<Input name="input">../ARMA_pointer_2018_2021_to2045.csv</Input>
<Input name="pk">arma.pk</Input>
</Files>

<Steps>
<IOStep name="load">
<Input class="Files" type="">input</Input>
<Output class="DataObjects" type="HistorySet">input</Output>
<Output class="OutStreams" type="Print">test1</Output>
</IOStep>
<RomTrainer name="train">
<Input class="DataObjects" type="HistorySet">input</Input>
<Output class="Models" type="ROM">arma</Output>
</RomTrainer>
<IOStep name="meta">
<Input class="Models" type="ROM">arma</Input>
<Output class="DataObjects" type="DataSet">meta</Output>
<Output class="OutStreams" type="Print">romMeta</Output>
</IOStep>
<IOStep name="serialize">
<Input class="Models" type="ROM">arma</Input>
<Output class="Files" type="">pk</Output>
</IOStep>
<MultiRun name="sample">
<Input class="DataObjects" type="PointSet">placeholder</Input>
<Model class="Models" type="ROM">arma</Model>
<Sampler class="Samplers" type="MonteCarlo">mc</Sampler>
<Output class="OutStreams" type="Print">test2</Output>
<Output class="DataObjects" type="DataSet">synthetic</Output>
<Output class="OutStreams" type="Print">synthetic</Output>
</MultiRun>
<IOStep name="plotting">
<Input class="DataObjects" type="HistorySet">input</Input>
<Input class="DataObjects" type="HistorySet">synthetic</Input>
<Output class="OutStreams" type="Plot">plotters</Output>
</IOStep>
</Steps>

<DataObjects>
<PointSet name="placeholder">
<Input>scaling</Input>
<Output>OutputPlaceHolder</Output>
</PointSet>
<HistorySet name="input">
<Input>scaling,Year</Input>
<Output>price,hour</Output>
<options>
<pivotParameter>hour</pivotParameter>
</options>
</HistorySet>
<DataSet name="synthetic">
<Input>scaling</Input>
<Output>price</Output>
<Index var="hour">price</Index>
<Index var="Year">price</Index>
</DataSet>
<DataSet name="meta"/>
</DataObjects>

<Models>
<ROM name="arma" subType="ARMA">
<pivotParameter>hour</pivotParameter>
<Features>scaling</Features>
<Target>price,hour</Target>
<P>0</P>
<Q>1</Q>
<Fourier>8760,4380,2190,1095,168,24,12</Fourier>
<Segment grouping="interpolate">
<macroParameter>Year</macroParameter>
<subspace pivotLength="24" shift="zero">hour</subspace>
<evalMode>full</evalMode>
<Classifier class="Models" type="PostProcessor">classifier</Classifier>
</Segment>
<reseedCopies>True</reseedCopies>
<preserveInputCDF>True</preserveInputCDF>
<seed>42</seed>
</ROM>
<PostProcessor name="classifier" subType="DataMining">
<KDD labelFeature="labels" lib="SciKitLearn">
<Features>price</Features>
<SKLtype>cluster|KMeans</SKLtype>
<n_clusters>20</n_clusters>
</KDD>
</PostProcessor>
</Models>

<OutStreams>
<Print name="romMeta">
<type>csv</type>
<source>meta</source>
</Print>
<Print name="test1">
<type>csv</type>
<source>input</source>
</Print>
<Print name="test2">
<type>csv</type>
<source>placeholder</source>
</Print>
<Print name="synthetic">
<type>csv</type>
<source>synthetic</source>
</Print>
<Plot name="plotters" subType="SyntheticCloud">
<training>input</training>
<samples>synthetic</samples>
<macroParam>Year</macroParam>
<microParam>hour</microParam>
<variables>price</variables>
</Plot>
</OutStreams>

<Samplers>
<MonteCarlo name="mc">
<samplerInit>
<limit>1</limit>
<initialSeed>42</initialSeed>
</samplerInit>
<constant name="scaling">1</constant>
</MonteCarlo>
</Samplers>

</Simulation>
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