Added notebook to sample from predictions and load model
This commit is contained in:
Victor Mylle
@@ -11,7 +11,9 @@ Eerst literatuur bekijken ofdat probleem al voorkomt
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- Training data -> 2 tresholds (1 voor charging, 1 voor discharging) (Volledig chargen / dischargen)
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- 2 Mwh -> 8 kwartieren
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- 1000 generaties voor 1 dag -> 1000 prijzen reconstrueren -> tresholds bepalen (logische tresholds) -> 2 tresholds voor 1 dag en toepassen op volledige test set
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2 MWh -> 0.25 MW per kwartier -> charge cycle: 4 MWh -> 16 kwartieren iets doen -> dan charge cycle (max 400 per jaar voor later)
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- 1000 generaties voor 1 dag uit test set -> 1000 prijzen reconstrueren -> tresholds bepalen (logische tresholds) -> 2 tresholds voor 1 dag en toepassen op de echte prijzen van de dag
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- [x] Learning rate non autoregressive
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@@ -28,6 +30,38 @@ Eerst literatuur bekijken ofdat probleem al voorkomt
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- [ ] Diffusion vs Variable Selection Network
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- [x] Bid ladder van gisteren
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- [ ] Plot van reconstucted prices with real bid ladder + bid ladder from yersterday against real reconstructed prices
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Presentatie:
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- Korte motivatie -> op dit moment: veel batterijen op simpele manier zoals onze baseline
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- Policy per dag afhankelijk van generation model (policy word day ahead vastgelegd)
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~~- NRV -> resultaten van verschillende resultaten (verder werken met autoregresive om te kunnen samplen)
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-> ook overconfidence tonen van de quantiles (met die histogram)~~
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~~- Quantile regreession + figuur van CDF
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Resultaten van de autoregression modellen~~
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- Plot van CRPS (kijk teams)
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~~- Prijs reconstructie + momenteel bid ladders geplubliceerd door Elia momenteel. (paar plotjes)~~
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~~- Baseline Policy voor batterij~~
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- (Resultaten van nieuwe methode met samplen)
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~~- Volgende stappen:~~
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~~3 mogelijkheden:~~
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~~- bid ladders (niet echt doen)~~
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~~- Generaties beter van NRV -> quantile regression + overconfidence fixen (+ betere modellen)
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Diffusion model is er een van en niet probleem van autoregressive~~
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~~- Betere RL modellen (policies)~~
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(mag 20 minuten zijn)
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# Different Model Architectures (For Quantile Regression)
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## Baseline
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The baseline just calculates the values for the given quantiles using the training data.
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@@ -10,72 +10,57 @@ Determining 2 thresholds for battery charging and discharging. Charging when the
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Training data: 01-01-2020 - 31-12-2022
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Test data: 01-01-2023 - 12-12-2023
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| Charging threshold (€/MWh) | Discharge threshold (€/MWh) | Profit (€) | Charge Cycles |
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------------------:|---------------------:|---------------:|----------------:|
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| 150 | 100 | 366406 | 2658 |
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| 150 | 50 | 366406 | 2658 |
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| 150 | 0 | 366406 | 2658 |
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| 150 | 150 | 365999 | 2639 |
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| 100 | 150 | 364905 | 2306 |
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| 100 | 100 | 364483 | 2886 |
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| 100 | 0 | 364376 | 2896 |
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| 100 | 50 | 364376 | 2896 |
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| 200 | 150 | 352953 | 2416 |
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| 200 | 100 | 352953 | 2416 |
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| 200 | 50 | 352953 | 2416 |
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| 200 | 0 | 352953 | 2416 |
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| 200 | 200 | 352811 | 2413 |
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| 150 | 200 | 350975 | 2243 |
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| 100 | 200 | 345855 | 1929 |
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| 50 | 50 | 341569 | 3864 |
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| 50 | 100 | 341421 | 2357 |
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| 50 | 0 | 341202 | 3865 |
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| 200 | 250 | 337567 | 1996 |
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| 50 | 150 | 330189 | 1815 |
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| 150 | 250 | 329684 | 1835 |
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| 200 | 300 | 329343 | 1610 |
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| 250 | 250 | 323456 | 2089 |
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| 250 | 0 | 322692 | 2103 |
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| 250 | 150 | 322692 | 2103 |
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| 250 | 50 | 322692 | 2103 |
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| 250 | 100 | 322692 | 2103 |
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| 250 | 200 | 322692 | 2103 |
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| 250 | 300 | 321378 | 1685 |
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| 100 | 250 | 319651 | 1554 |
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| 150 | 300 | 319089 | 1462 |
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| 300 | 250 | 314776 | 1752 |
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| 300 | 50 | 314776 | 1752 |
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| 300 | 100 | 314776 | 1752 |
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| 300 | 150 | 314776 | 1752 |
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| 300 | 200 | 314776 | 1752 |
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| 300 | 0 | 314776 | 1752 |
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| 50 | 200 | 313685 | 1476 |
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| 300 | 300 | 313469 | 1749 |
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| 100 | 300 | 309773 | 1236 |
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| 200 | 350 | 306832 | 1341 |
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| 250 | 350 | 302349 | 1411 |
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| 150 | 350 | 295917 | 1202 |
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| 300 | 350 | 290570 | 1466 |
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| 50 | 250 | 290097 | 1195 |
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| 350 | 300 | 284856 | 1507 |
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| 350 | 250 | 284856 | 1507 |
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| 350 | 150 | 284856 | 1507 |
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| 350 | 100 | 284856 | 1507 |
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| 350 | 50 | 284856 | 1507 |
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| 350 | 0 | 284856 | 1507 |
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| 350 | 200 | 284856 | 1507 |
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| 100 | 350 | 284323 | 996 |
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| 50 | 300 | 280922 | 954 |
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| 350 | 350 | 279834 | 1496 |
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| 0 | 150 | 277863 | 1243 |
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| 0 | 100 | 276435 | 1477 |
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| 0 | 200 | 270056 | 1080 |
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| 0 | 50 | 269265 | 1914 |
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| 50 | 350 | 259569 | 787 |
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| 0 | 250 | 258282 | 908 |
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| 0 | 300 | 250679 | 741 |
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| 0 | 0 | 248357 | 2065 |
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| 0 | 350 | 233775 | 624 |
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| | Charge treshold | Discharge treshold | Charging Cost | Discharging Profit | Total Profit | Charge cycles | Mean charging price | Mean discharging price |
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|---:|------------------:|---------------------:|----------------:|---------------------:|---------------:|----------------:|----------------------:|-------------------------:|
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| 0 | 150 | 100 | 184072 | 1.03303e+06 | 848962 | 1884.62 | 32.4889 | 332.002 |
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| 0 | 150 | 0 | 184072 | 1.03303e+06 | 848962 | 1884.62 | 32.4889 | 332.002 |
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| 0 | 150 | -100 | 184072 | 1.03303e+06 | 848962 | 1884.62 | 32.4889 | 332.002 |
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| 0 | 150 | -50 | 184072 | 1.03303e+06 | 848962 | 1884.62 | 32.4889 | 332.002 |
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| 0 | 150 | 50 | 184072 | 1.03303e+06 | 848962 | 1884.62 | 32.4889 | 332.002 |
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| 0 | 150 | 150 | 182152 | 1.02598e+06 | 843824 | 1860.12 | 32.4889 | 333.447 |
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| 0 | 200 | 150 | 248326 | 1.0773e+06 | 828976 | 1695.5 | 42.9038 | 367.058 |
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| 0 | 200 | 100 | 248326 | 1.0773e+06 | 828976 | 1695.5 | 42.9038 | 367.058 |
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| 0 | 200 | 50 | 248326 | 1.0773e+06 | 828976 | 1695.5 | 42.9038 | 367.058 |
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| 0 | 200 | 0 | 248326 | 1.0773e+06 | 828976 | 1695.5 | 42.9038 | 367.058 |
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| 0 | 200 | -50 | 248326 | 1.0773e+06 | 828976 | 1695.5 | 42.9038 | 367.058 |
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| 0 | 200 | -100 | 248326 | 1.0773e+06 | 828976 | 1695.5 | 42.9038 | 367.058 |
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| 0 | 200 | 200 | 247560 | 1.07529e+06 | 827727 | 1690 | 42.9038 | 367.44 |
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| 0 | 150 | 200 | 151145 | 937599 | 786454 | 1514.88 | 32.4889 | 367.44 |
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| 0 | 100 | -100 | 85591.8 | 865530 | 779938 | 1978.12 | 19.9739 | 283.851 |
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| 0 | 100 | 50 | 85591.8 | 865530 | 779938 | 1978.12 | 19.9739 | 283.851 |
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| 0 | 100 | 0 | 85591.8 | 865530 | 779938 | 1978.12 | 19.9739 | 283.851 |
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| 0 | 100 | -50 | 85591.8 | 865530 | 779938 | 1978.12 | 19.9739 | 283.851 |
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| 0 | 100 | 100 | 84872.7 | 864043 | 779171 | 1966.62 | 19.9739 | 284.61 |
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| 0 | 100 | 150 | 63807.1 | 802437 | 738630 | 1502.5 | 19.9739 | 333.447 |
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| 0 | 50 | 50 | -35789.2 | 689455 | 725244 | 2831 | -9.65396 | 204.943 |
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| 0 | 50 | -100 | -35776.3 | 688933 | 724710 | 2833.88 | -9.65396 | 204.79 |
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| 0 | 50 | 0 | -35776.3 | 688933 | 724710 | 2833.88 | -9.65396 | 204.79 |
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| 0 | 50 | -50 | -35776.3 | 688933 | 724710 | 2833.88 | -9.65396 | 204.79 |
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| 0 | 100 | 200 | 49469.3 | 721380 | 671911 | 1196.12 | 19.9739 | 367.44 |
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| 0 | 50 | 100 | -46110.5 | 592694 | 638805 | 1417.5 | -9.65396 | 284.61 |
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| 0 | 50 | 150 | -45858.6 | 531472 | 577330 | 1007.5 | -9.65396 | 333.447 |
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| 0 | 50 | 200 | -43738 | 473478 | 517216 | 779.25 | -9.65396 | 367.44 |
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| 0 | 0 | 100 | -97804.3 | 341072 | 438876 | 761.5 | -73.2011 | 284.61 |
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| 0 | 0 | 50 | -121468 | 314671 | 436139 | 993.625 | -73.2011 | 204.943 |
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| 0 | 0 | 150 | -85919 | 341046 | 426964 | 635.75 | -73.2011 | 333.447 |
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| 0 | 0 | 200 | -75822.2 | 328188 | 404010 | 541.25 | -73.2011 | 367.44 |
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| 0 | 0 | 0 | -135954 | 259915 | 395869 | 1110.12 | -73.2011 | 146.436 |
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| 0 | 0 | -100 | -136936 | 251758 | 388694 | 1117.5 | -73.2011 | 145.226 |
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| 0 | 0 | -50 | -136936 | 251758 | 388694 | 1117.5 | -73.2011 | 145.226 |
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| 0 | -50 | 150 | -97889.1 | 219525 | 317414 | 409.312 | -127.845 | 333.447 |
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| 0 | -50 | 100 | -108274 | 208273 | 316548 | 458.312 | -127.845 | 284.61 |
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| 0 | -50 | 200 | -87698.7 | 223235 | 310933 | 363.625 | -127.845 | 367.44 |
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| 0 | -50 | 50 | -124664 | 184027 | 308691 | 525.688 | -127.845 | 204.943 |
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| 0 | -50 | 0 | -131679 | 158118 | 289797 | 551.188 | -127.845 | 146.436 |
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| 0 | -50 | -50 | -138246 | 126218 | 264464 | 576.5 | -127.845 | 136.356 |
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| 0 | -50 | -100 | -138429 | 125059 | 263488 | 577.625 | -127.845 | 136.262 |
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| 0 | -100 | 200 | -76499.7 | 137174 | 213674 | 219.625 | -179.829 | 367.44 |
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| 0 | -100 | 150 | -82202.7 | 128215 | 210418 | 237.125 | -179.829 | 333.447 |
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| 0 | -100 | 100 | -86319.5 | 117325 | 203645 | 250.25 | -179.829 | 284.61 |
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| 0 | -100 | 50 | -94055.9 | 99443.5 | 193499 | 269.875 | -179.829 | 204.943 |
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| 0 | -100 | 0 | -95713.7 | 87279.5 | 182993 | 274.625 | -179.829 | 146.436 |
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| 0 | -100 | -50 | -97722.9 | 71560.6 | 169283 | 280.375 | -179.829 | 136.356 |
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| 0 | -100 | -100 | -101133 | 45851.2 | 146985 | 289.375 | -179.829 | 130.542 |
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## Optimal policy
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Charge threshold: 150 €/MWh \
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