204 lines
20 KiB
Markdown
204 lines
20 KiB
Markdown
# Policies for battery charging
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## Battery
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Capacity: 2MWh \
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Charging Power: 1MW \
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Discharging Power: 1MW
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## Baseline policy
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Determining 2 thresholds for battery charging and discharging. Charging when the imbalance price is below the lower threshold and discharging when the imbalance price is above the upper threshold.
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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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| | Charge threshold | Discharge threshold | Charging Cost | Discharging Profit | Total Profit | Charge cycles | Mean charging price | Mean discharging price |
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|---:|-------------------:|----------------------:|----------------:|---------------------:|---------------:|----------------:|----------------------:|-------------------------:|
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| 0 | 150 | 175 | 165982 | 989322 | 823340 | 1701.62 | 32.4889 | 348.51 |
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| 0 | 175 | 200 | 190060 | 1.00145e+06 | 811389 | 1594 | 37.0705 | 367.44 |
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| 0 | 125 | 150 | 132766 | 939145 | 806378 | 1729.88 | 27.7746 | 333.447 |
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| 0 | 200 | 225 | 219726 | 1.01789e+06 | 798159 | 1493.12 | 42.9038 | 390.49 |
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| 0 | 150 | 200 | 151145 | 937599 | 786454 | 1514.88 | 32.4889 | 367.44 |
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| 0 | 125 | 175 | 122067 | 904885 | 782818 | 1584.62 | 27.7746 | 348.51 |
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| 0 | 175 | 225 | 173050 | 950270 | 777219 | 1415 | 37.0705 | 390.49 |
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| 0 | 100 | 125 | 69876.4 | 829454 | 759577 | 1662.88 | 19.9739 | 315.1 |
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| 0 | 150 | 225 | 136563 | 886279 | 749716 | 1339.12 | 32.4889 | 390.49 |
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| 0 | 125 | 200 | 109873 | 853728 | 743855 | 1402.5 | 27.7746 | 367.44 |
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| 0 | 100 | 150 | 63807.1 | 802437 | 738630 | 1502.5 | 19.9739 | 333.447 |
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| 0 | 100 | 175 | 56405.8 | 770173 | 713768 | 1366.75 | 19.9739 | 348.51 |
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| 0 | 75 | 100 | 14153.7 | 724660 | 710506 | 1684.5 | 11.3023 | 284.61 |
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| 0 | 125 | 225 | 97524.1 | 804468 | 706944 | 1231.88 | 27.7746 | 390.49 |
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| 0 | 25 | 50 | -56542.1 | 637628 | 694171 | 2696.12 | -16.9846 | 204.943 |
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| 0 | 75 | 125 | 8003.32 | 688780 | 680776 | 1407.38 | 11.3023 | 315.1 |
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| 0 | 100 | 200 | 49469.3 | 721380 | 671911 | 1196.12 | 19.9739 | 367.44 |
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| 0 | 50 | 75 | -47575.2 | 614964 | 662539 | 1752 | -9.65396 | 254.211 |
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| 0 | 75 | 150 | 5147.22 | 661439 | 656292 | 1254.62 | 11.3023 | 333.447 |
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| 0 | 50 | 100 | -46110.5 | 592694 | 638805 | 1417.5 | -9.65396 | 284.61 |
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| 0 | 100 | 225 | 42046.6 | 677560 | 635514 | 1042.88 | 19.9739 | 390.49 |
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| 0 | 75 | 175 | 850.49 | 631552 | 630702 | 1129 | 11.3023 | 348.51 |
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| 0 | 25 | 75 | -63342.8 | 561356 | 624699 | 1637 | -16.9846 | 254.211 |
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| 0 | 50 | 125 | -46686.3 | 556263 | 602950 | 1150.5 | -9.65396 | 315.1 |
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| 0 | 25 | 100 | -61448.6 | 537683 | 599132 | 1306.5 | -16.9846 | 284.61 |
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| 0 | 75 | 200 | -1767.94 | 590094 | 591862 | 981.5 | 11.3023 | 367.44 |
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| 0 | 50 | 150 | -45858.6 | 531472 | 577330 | 1007.5 | -9.65396 | 333.447 |
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| 0 | 25 | 125 | -61228.7 | 500861 | 562089 | 1045.62 | -16.9846 | 315.1 |
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| 0 | 75 | 225 | -3475.71 | 555727 | 559203 | 855.875 | 11.3023 | 390.49 |
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| 0 | 50 | 175 | -46084.1 | 506348 | 552432 | 900.875 | -9.65396 | 348.51 |
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| 0 | 25 | 150 | -60177.2 | 476823 | 537000 | 906.75 | -16.9846 | 333.447 |
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| 0 | 50 | 200 | -43738 | 473478 | 517216 | 779.25 | -9.65396 | 367.44 |
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| 0 | 25 | 175 | -59466.7 | 453988 | 513455 | 808.25 | -16.9846 | 348.51 |
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| 0 | 50 | 225 | -40529.8 | 452651 | 493181 | 693.875 | -9.65396 | 390.49 |
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| 0 | 25 | 200 | -55766.8 | 426055 | 481822 | 699.875 | -16.9846 | 367.44 |
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| 0 | 25 | 225 | -51953 | 407484 | 459437 | 623.875 | -16.9846 | 390.49 |
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| 0 | 0 | 75 | -107853 | 332344 | 440197 | 851.375 | -73.2011 | 254.211 |
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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 | 125 | -91087.2 | 342646 | 433734 | 686.125 | -73.2011 | 315.1 |
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| 0 | 0 | 25 | -126590 | 305984 | 432574 | 1041.75 | -73.2011 | 193.87 |
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| 0 | 0 | 150 | -85919 | 341046 | 426964 | 635.75 | -73.2011 | 333.447 |
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| 0 | 0 | 175 | -82378.2 | 338310 | 420688 | 600.625 | -73.2011 | 348.51 |
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| 0 | 0 | 200 | -75822.2 | 328188 | 404010 | 541.25 | -73.2011 | 367.44 |
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| 0 | 0 | 225 | -69488.7 | 320776 | 390265 | 494.75 | -73.2011 | 390.49 |
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| 0 | -25 | 125 | -102495 | 269615 | 372110 | 534.062 | -105.73 | 315.1 |
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| 0 | -25 | 100 | -108934 | 262527 | 371462 | 574.938 | -105.73 | 284.61 |
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| 0 | -25 | 75 | -118553 | 252453 | 371006 | 626.062 | -105.73 | 254.211 |
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| 0 | -25 | 150 | -97080 | 271209 | 368289 | 503.438 | -105.73 | 333.447 |
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| 0 | -25 | 50 | -129918 | 236112 | 366030 | 683.562 | -105.73 | 204.943 |
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| 0 | -25 | 175 | -92889.5 | 272520 | 365409 | 480.438 | -105.73 | 348.51 |
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| 0 | -25 | 25 | -132518 | 227910 | 360428 | 695.562 | -105.73 | 193.87 |
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| 0 | -25 | 200 | -85482.7 | 268638 | 354120 | 438.5 | -105.73 | 367.44 |
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| 0 | -25 | 225 | -79253.2 | 264052 | 343305 | 403.75 | -105.73 | 390.49 |
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| 0 | -25 | 0 | -139125 | 199831 | 338956 | 724.312 | -105.73 | 146.436 |
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| 0 | -50 | 125 | -102665 | 216740 | 319405 | 431.562 | -127.845 | 315.1 |
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| 0 | -50 | 175 | -94272.2 | 223434 | 317706 | 393.188 | -127.845 | 348.51 |
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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 | 75 | -115707 | 198325 | 314032 | 488.438 | -127.845 | 254.211 |
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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 | 25 | -126605 | 177834 | 304440 | 533.062 | -127.845 | 193.87 |
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| 0 | -50 | 225 | -81706.8 | 221510 | 303217 | 337.75 | -127.845 | 390.49 |
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| 0 | -50 | 0 | -131679 | 158118 | 289797 | 551.188 | -127.845 | 146.436 |
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| 0 | -50 | -25 | -135234 | 140945 | 276180 | 565 | -127.845 | 139.469 |
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| 0 | -75 | 175 | -90764.9 | 184846 | 275611 | 325.812 | -146.153 | 348.51 |
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| 0 | -75 | 125 | -98076.6 | 176722 | 274799 | 355.062 | -146.153 | 315.1 |
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| 0 | -75 | 150 | -93979.3 | 179914 | 273893 | 338.188 | -146.153 | 333.447 |
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| 0 | -75 | 100 | -103131 | 169294 | 272425 | 375.062 | -146.153 | 284.61 |
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| 0 | -75 | 200 | -85036.8 | 186067 | 271104 | 302.375 | -146.153 | 367.44 |
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| 0 | -75 | 75 | -109431 | 159779 | 269210 | 395.938 | -146.153 | 254.211 |
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| 0 | -75 | 225 | -79978.8 | 185752 | 265731 | 282.75 | -146.153 | 390.49 |
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| 0 | -75 | 50 | -116483 | 147147 | 263630 | 421.062 | -146.153 | 204.943 |
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| 0 | -75 | 25 | -117886 | 141847 | 259734 | 424.812 | -146.153 | 193.87 |
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| 0 | -75 | 0 | -120983 | 126071 | 247054 | 435.188 | -146.153 | 146.436 |
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| 0 | -75 | -25 | -123261 | 111930 | 235190 | 443.625 | -146.153 | 139.469 |
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| 0 | -75 | -50 | -124708 | 101672 | 226380 | 449.25 | -146.153 | 136.356 |
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| 0 | -100 | 200 | -76499.7 | 137174 | 213674 | 219.625 | -179.829 | 367.44 |
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| 0 | -100 | 175 | -79830.5 | 132966 | 212797 | 230.125 | -179.829 | 348.51 |
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| 0 | -100 | 225 | -72449.9 | 138631 | 211081 | 207.625 | -179.829 | 390.49 |
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| 0 | -100 | 150 | -82202.7 | 128215 | 210418 | 237.125 | -179.829 | 333.447 |
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| 0 | -100 | 125 | -84192.7 | 123976 | 208169 | 243.625 | -179.829 | 315.1 |
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| 0 | -100 | 100 | -86319.5 | 117325 | 203645 | 250.25 | -179.829 | 284.61 |
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| 0 | -100 | 75 | -90219.7 | 109153 | 199373 | 259.25 | -179.829 | 254.211 |
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| 0 | -100 | 50 | -94055.9 | 99443.5 | 193499 | 269.875 | -179.829 | 204.943 |
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| 0 | -100 | 25 | -94464.1 | 96073.2 | 190537 | 270.875 | -179.829 | 193.87 |
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| 0 | -100 | 0 | -95713.7 | 87279.5 | 182993 | 274.625 | -179.829 | 146.436 |
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| 0 | -100 | -25 | -97020.3 | 78656.5 | 175677 | 278.25 | -179.829 | 139.469 |
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| 0 | -100 | -50 | -97722.9 | 71560.6 | 169283 | 280.375 | -179.829 | 136.356 |
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| 0 | -100 | -75 | -98604.6 | 63373.8 | 161978 | 282.625 | -179.829 | 134.012 |
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## Optimal policy
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Charge threshold: 150 €/MWh \
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Discharge threshold: 175 €/MWh
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Profit on test data: € 359548 \
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Charge cycles: 855.938
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# Smarter Policy using predicted NRV
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Test data: 01-01-2023 until 08-10–2023
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| Policy | Threshold Step Size (€) | Total Profit (€) | Charge Cycles |
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|--------|---------------------|--------------|---------------|
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| Baseline (charge: 150, discharge: 175) | 25 | 251202.59 | 725 |
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| Baseline (yesterday imbalance price) | 25 | 342980.0938 | 903 |
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| GRU Predicted NRV (mean reconstructed imbalance price) | 50 | 325362.81 | 856 |
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| GRU Predicted NRV (mean reconstructed imbalance price) | 25 | 334058.65 | 862 |
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| GRU Predicted NRV (mean thresholds) | 25 | 339846.9062 | 842 |
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| Diffusion Predicted NRV (mean thresholds) | 25 | 338168.0312 | 886 |
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# Penalty parameter for charge cycles
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| Policy | Penalty parameter | Total Profit (€) | Charge Cycles |
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|--------|---------------------|--------------|-----------------|
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| Baseline (yesterday imbalance price) | 10 | 335968.9062 | 895.4375 |
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| Baseline (yesterday imbalance price) | 20 | 328577.2812 | 886.5625 |
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| Baseline (yesterday imbalance price) | 50 | 306301.9688 | 850.9375 |
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| Baseline (yesterday imbalance price) | 150 | 251367.0469 | 749.7500 |
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| Diffusion Predicted NRV | 10 | 331288.7812 | 880.3750 |
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| Diffusion Predicted NRV | 20 | 324568.7812 | 871.5000 |
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| Diffusion Predicted NRV | 50 | 304761.1875 | 837.3125 |
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| Diffusion Predicted NRV | 150 | 238441.5625 | 670.1875 |
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# TODO
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- [ ] Baseline
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- [x] Profit penalty parameter als over charge cycles voor een dag -> parameter bepalen op training data (convex probleem) (< 400 charge cycles per jaar) (over een dag kijken hoeveel charge cycles -> profit - penalty * charge cycles erover, (misschien belonen als eronder charge cycles))
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- [ ] Meer verschil bekijken tussen GRU en diffusion
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- [ ] (In Progress) Andere lagen voor diffusion model (GRU, kijken naar TSDiff)
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- [x] Policies met andere modellen (Linear, Non Linear)
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- [ ] Visualize the policies over the whole testr set -> thresholds plotten voor elke dag (elke policy) -> mss distribution om overzichtelijk te houden (mean and std)
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- [ ] Probleem met diffusion model (activation function? waarom direct grote waardes?)
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- [ ] Autoregressive confidence problem -> Quantiles zelf uit elkaar halen (helpt dit?)
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- [ ] time steps reducing for diffusion model (UNet activation functions?)
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- [ ] (State space model? S4)
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TODO:
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- [ ] diffusion model oefening generative models vragen
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- [ ] Non autoregressive models policy testen (Non Linear eerst) -> als dit al slect, niet verder kijken, wel vermelden
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- [ ] Policy in test set -> over charge cycles (stop trading electricity)
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- [ ] penalty bepalen op training data
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- [ ] cycles en profit herschalen naar per jaar
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baseline -> NRV van gisteren gebruiken om thresholds te bepalen voor vandaag
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andere policies -> NRV van vandaag voorspellen met model en thresholds bepalen voor vandaag
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Eerste baseline -> thresholds bepalen op training data maar ook stoppen als 400 cycles (herschalen) per jaar bereikt zijn -> thresholds zouden anders moeten zijn (Ook met penalty parameter)
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-> deze toepassen op test set (ook stoppen als 400/jaar bereikt zijn)
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Visualizatie van thresholds over test set voor baselines en complexere modellen -> zonder penalties tonen
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1 a 2 Case studies (extreme gevallen, thresholds 150, -5, normale mss)
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- Generatie van NRV (echte NRV)
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- Thresholds die eruit komen
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- Profit en charge cycles
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Policy volledig fixen en later training script met policy direct erachter (tijdens schrijven door laten runnen)
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1) Policy
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2) Finetuning van modellen (+ vergelijken met elkaar opbv profit en error)
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3) Ablation Study (input features weghalen en kijken wat er gebeurt)
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( 4) Diffusion tussendoor )
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Inleiding +
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Literatuurstudie +
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Tabellen die we gaan bespreken -> updaten met nieuwe data dan
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Nog eens 3e meeting opbrengen voor 2e deel maart. |