{ "cells": [ { "cell_type": "code", "execution_count": 1, "metadata": {}, "outputs": [], "source": [ "import datetime\n", "import numpy as np\n", "import matplotlib.pyplot as plt\n", "import matplotlib.dates as mdates\n", "import matplotlib.cbook as cbook\n", "import EAtools as ea\n", "import pandas as pd\n", "import os \n", "import sys \n", "import numpy\n", "import fileinput\n", "import matplotlib.pyplot as plt \n", "import matplotlib.ticker \n", "from matplotlib.ticker import FormatStrFormatter \n", "import pandas.io.sql\n", "import pyodbc \n", "from matplotlib.pyplot import figure, show\n", "from matplotlib.patches import Ellipse\n", "import numpy as np\n", "from pandas import *\n", "import EAtools as ea\n", "ea.set_options()\n", "ea.ea_report_style()\n", "from pylab import *\n", "import matplotlib.ticker as tkr\n", "from datetime import datetime, date, time, timedelta\n", "ea_p=ea.ea_p\n", "ea_s=ea.ea_s\n", "def cm2inch(value):\n", " return value/2.54\n", "import pyarrow as pa\n", "import pyarrow.parquet as pq" ] }, { "cell_type": "code", "execution_count": 2, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Populating the interactive namespace from numpy and matplotlib\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "/home/julia/.local/lib/python3.5/site-packages/IPython/core/magics/pylab.py:160: UserWarning: pylab import has clobbered these variables: ['power', 'datetime', 'linalg', 'fft', 'random', 'info']\n", "`%matplotlib` prevents importing * from pylab and numpy\n", " \"\\n`%matplotlib` prevents importing * from pylab and numpy\"\n" ] } ], "source": [ "from db import DB\n", "import os\n", "ea.set_options()\n", "ea.ea_report_style()\n", "%pylab inline\n", "%matplotlib inline\n", "path='/media/usb/notebooks/Julia/20192020_review'\n", "db = DB(profile=\"hallj\") " ] }, { "cell_type": "code", "execution_count": 3, "metadata": {}, "outputs": [], "source": [ "meridian_watervalues = pd.read_parquet(\"/media/usb/notebooks/Julia/20192020_review/meridian_watervalues.parquet\")\n", "mercury_watervalues = pd.read_parquet(\"/media/usb/notebooks/Julia/20192020_review/mercury_watervalues.parquet\")\n", "genesis_watervalues = pd.read_parquet(\"/media/usb/notebooks/Julia/20192020_review/genesis_watervalues.parquet\")\n", "DOASA_watervalues = pd.read_parquet(\"/media/usb/notebooks/Julia/20192020_review/DOASA_avg_watervalue.parquet\")\n", "#meridian_watervalues.tail()" ] }, { "cell_type": "code", "execution_count": 4, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
\n", "\n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "
MegawattTotMWpercent
TradingDateTradingPeriod
2014-01-011439.3131356.31332.390237
2450.8251351.82533.349361
3442.0551347.05532.816403
4490.5221367.52235.869405
5513.5091369.50937.495847
\n", "
" ], "text/plain": [ " Megawatt TotMW percent\n", "TradingDate TradingPeriod \n", "2014-01-01 1 439.313 1356.313 32.390237\n", " 2 450.825 1351.825 33.349361\n", " 3 442.055 1347.055 32.816403\n", " 4 490.522 1367.522 35.869405\n", " 5 513.509 1369.509 37.495847" ] }, "execution_count": 4, "metadata": {}, "output_type": "execute_result" } ], "source": [ "#match in percent of offers over 300\n", "waitaki_300 = pd.read_parquet(\"/media/usb/notebooks/Julia/20192020_review/waitaki_percent300_v2.parquet\")\n", "waikato_300 = pd.read_parquet(\"/media/usb/notebooks/Julia/20192020_review/waikato_percent300_v2.parquet\")\n", "tekapo_300 = pd.read_parquet(\"/media/usb/notebooks/Julia/20192020_review/tekapo_percent300_v2.parquet\")\n", "clutha_300 = pd.read_parquet(\"/media/usb/notebooks/Julia/20192020_review/clutha_percent300_v2.parquet\")\n", "waitaki_300.head()" ] }, { "cell_type": "code", "execution_count": 5, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
\n", "\n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "
WeightstarPrice_exc300
TradingDateTradingPeriod
2014-01-01112.505573
212.727114
312.670994
413.074584
513.394603
\n", "
" ], "text/plain": [ " WeightstarPrice_exc300\n", "TradingDate TradingPeriod \n", "2014-01-01 1 12.505573\n", " 2 12.727114\n", " 3 12.670994\n", " 4 13.074584\n", " 5 13.394603" ] }, "execution_count": 5, "metadata": {}, "output_type": "execute_result" } ], "source": [ "#match in QWOP with offers over 300 removed\n", "waitaki_QWOPexc = pd.read_parquet(\"/media/usb/notebooks/Julia/20192020_review/waitaki_QWOPexc_v2.parquet\")\n", "waikato_QWOPexc = pd.read_parquet(\"/media/usb/notebooks/Julia/20192020_review/waikato_QWOPexc_v2.parquet\")\n", "tekapo_QWOPexc = pd.read_parquet(\"/media/usb/notebooks/Julia/20192020_review/tekapo_QWOPexc_v2.parquet\")\n", "clutha_QWOPexc = pd.read_parquet(\"/media/usb/notebooks/Julia/20192020_review/clutha_QWOPexc_v2.parquet\")\n", "waitaki_QWOPexc = waitaki_QWOPexc.rename(columns={'WeightstarPrice':'WeightstarPrice_exc300'})\n", "waikato_QWOPexc = waikato_QWOPexc.rename(columns={'WeightstarPrice':'WeightstarPrice_exc300'})\n", "tekapo_QWOPexc = tekapo_QWOPexc.rename(columns={'WeightstarPrice':'WeightstarPrice_exc300'})\n", "clutha_QWOPexc = clutha_QWOPexc.rename(columns={'WeightstarPrice':'WeightstarPrice_exc300'})\n", "waitaki_QWOPexc.head()" ] }, { "cell_type": "code", "execution_count": 6, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
\n", "\n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "
WeightstarPrice
TradingDateTradingPeriod
2014-01-011324.259802
2333.638973
3328.472761
4358.111504
5373.956692
\n", "
" ], "text/plain": [ " WeightstarPrice\n", "TradingDate TradingPeriod \n", "2014-01-01 1 324.259802\n", " 2 333.638973\n", " 3 328.472761\n", " 4 358.111504\n", " 5 373.956692" ] }, "execution_count": 6, "metadata": {}, "output_type": "execute_result" } ], "source": [ "#match in QWOP\n", "waitaki_QWOP = pd.read_parquet(\"/media/usb/notebooks/Julia/20192020_review/waitaki_v2.parquet\")\n", "waikato_QWOP = pd.read_parquet(\"/media/usb/notebooks/Julia/20192020_review/waikato_v2.parquet\")\n", "tekapo_QWOP = pd.read_parquet(\"/media/usb/notebooks/Julia/20192020_review/tekapo_v2.parquet\")\n", "clutha_QWOP = pd.read_parquet(\"/media/usb/notebooks/Julia/20192020_review/clutha_v2.parquet\")\n", "waitaki_QWOP.head()" ] }, { "cell_type": "code", "execution_count": 9, "metadata": {}, "outputs": [], "source": [ "MERI = waitaki_300.join(waitaki_QWOPexc).join(waitaki_QWOP)\n", "MRPL = waikato_300.join(waikato_QWOPexc).join(waikato_QWOP)\n", "GENE = tekapo_300.join(tekapo_QWOPexc).join(tekapo_QWOP)\n", "CTCT = clutha_300.join(clutha_QWOPexc).join(clutha_QWOP)" ] }, { "cell_type": "code", "execution_count": 10, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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MegawattTotMWpercentWeightstarPrice_exc300WeightstarPrice
TradingDateTradingPeriod
2014-01-0110.0150.00.0000001.2869331.286933
265.0150.043.3333331.792941867.717333
365.0150.043.3333331.792941867.717333
465.0150.043.3333331.792941867.717333
565.0150.043.3333331.792941867.717333
\n", "
" ], "text/plain": [ " Megawatt TotMW percent WeightstarPrice_exc300 WeightstarPrice\n", "TradingDate TradingPeriod \n", "2014-01-01 1 0.0 150.0 0.000000 1.286933 1.286933\n", " 2 65.0 150.0 43.333333 1.792941 867.717333\n", " 3 65.0 150.0 43.333333 1.792941 867.717333\n", " 4 65.0 150.0 43.333333 1.792941 867.717333\n", " 5 65.0 150.0 43.333333 1.792941 867.717333" ] }, "execution_count": 10, "metadata": {}, "output_type": "execute_result" } ], "source": [ "GENE.head()" ] }, { "cell_type": "code", "execution_count": 11, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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MegawattTotMWpercentWeightstarPrice_exc300WeightstarPrice
TradingDateTradingPeriod
2014-01-0110.0670.010.027.41981527.419815
20.0670.010.027.41981527.419815
30.0670.010.027.41981527.419815
40.0645.010.024.76170924.761709
50.0645.010.024.76170924.761709
\n", "
" ], "text/plain": [ " Megawatt TotMW percent WeightstarPrice_exc300 WeightstarPrice\n", "TradingDate TradingPeriod \n", "2014-01-01 1 0.0 670.01 0.0 27.419815 27.419815\n", " 2 0.0 670.01 0.0 27.419815 27.419815\n", " 3 0.0 670.01 0.0 27.419815 27.419815\n", " 4 0.0 645.01 0.0 24.761709 24.761709\n", " 5 0.0 645.01 0.0 24.761709 24.761709" ] }, "execution_count": 11, "metadata": {}, "output_type": "execute_result" } ], "source": [ "CTCT.head()" ] }, { "cell_type": "code", "execution_count": 12, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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MegawattTotMWpercentWeightstarPrice_exc300WeightstarPrice
TradingDateTradingPeriod
2014-01-0110.00760.0000.000000109.338224109.338224
27.00926.0110.755931121.959949137.668489
39.00935.0000.962567124.025616144.008257
49.00935.0000.962567129.885799149.812032
58.61928.6100.927192130.129598149.321276
\n", "
" ], "text/plain": [ " Megawatt TotMW percent WeightstarPrice_exc300 WeightstarPrice\n", "TradingDate TradingPeriod \n", "2014-01-01 1 0.00 760.000 0.000000 109.338224 109.338224\n", " 2 7.00 926.011 0.755931 121.959949 137.668489\n", " 3 9.00 935.000 0.962567 124.025616 144.008257\n", " 4 9.00 935.000 0.962567 129.885799 149.812032\n", " 5 8.61 928.610 0.927192 130.129598 149.321276" ] }, "execution_count": 12, "metadata": {}, "output_type": "execute_result" } ], "source": [ "MRPL.head()" ] }, { "cell_type": "code", "execution_count": 13, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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MegawattTotMWpercentWeightstarPrice_exc300WeightstarPrice
TradingDateTradingPeriod
2014-01-011439.3131356.31332.39023712.505573324.259802
2450.8251351.82533.34936112.727114333.638973
3442.0551347.05532.81640312.670994328.472761
4490.5221367.52235.86940513.074584358.111504
5513.5091369.50937.49584713.394603373.956692
\n", "
" ], "text/plain": [ " Megawatt TotMW percent WeightstarPrice_exc300 WeightstarPrice\n", "TradingDate TradingPeriod \n", "2014-01-01 1 439.313 1356.313 32.390237 12.505573 324.259802\n", " 2 450.825 1351.825 33.349361 12.727114 333.638973\n", " 3 442.055 1347.055 32.816403 12.670994 328.472761\n", " 4 490.522 1367.522 35.869405 13.074584 358.111504\n", " 5 513.509 1369.509 37.495847 13.394603 373.956692" ] }, "execution_count": 13, "metadata": {}, "output_type": "execute_result" } ], "source": [ "MERI.head()" ] }, { "cell_type": "code", "execution_count": 14, "metadata": {}, "outputs": [], "source": [ "MERI = MERI.reset_index().set_index(['TradingDate'])\n", "MRPL = MRPL.reset_index().set_index(['TradingDate'])\n", "GENE = GENE.reset_index().set_index(['TradingDate'])\n", "CTCT = CTCT.reset_index().set_index(['TradingDate'])" ] }, { "cell_type": "code", "execution_count": 15, "metadata": {}, "outputs": [], "source": [ "genesis_watervalues = genesis_watervalues.rename(columns={'WeightstarPrice':'WaterValue'})" ] }, { "cell_type": "code", "execution_count": 18, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
\n", "\n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "
WaterValueTradingPeriodMegawattTotMWpercentWeightstarPrice_exc300WeightstarPricemarginal_H20_value
2014-01-01NaN1439.3131356.31332.39023712.505573324.259802NaN
2014-01-01NaN2450.8251351.82533.34936112.727114333.638973NaN
2014-01-01NaN3442.0551347.05532.81640312.670994328.472761NaN
2014-01-01NaN4490.5221367.52235.86940513.074584358.111504NaN
2014-01-01NaN5513.5091369.50937.49584713.394603373.956692NaN
\n", "
" ], "text/plain": [ " WaterValue TradingPeriod Megawatt TotMW percent WeightstarPrice_exc300 WeightstarPrice marginal_H20_value\n", "2014-01-01 NaN 1 439.313 1356.313 32.390237 12.505573 324.259802 NaN\n", "2014-01-01 NaN 2 450.825 1351.825 33.349361 12.727114 333.638973 NaN\n", "2014-01-01 NaN 3 442.055 1347.055 32.816403 12.670994 328.472761 NaN\n", "2014-01-01 NaN 4 490.522 1367.522 35.869405 13.074584 358.111504 NaN\n", "2014-01-01 NaN 5 513.509 1369.509 37.495847 13.394603 373.956692 NaN" ] }, "execution_count": 18, "metadata": {}, "output_type": "execute_result" } ], "source": [ "MERI = meridian_watervalues.join(MERI,how='right').join(DOASA_watervalues,how='left')\n", "MRPL = mercury_watervalues.join(MRPL,how='right').join(DOASA_watervalues,how='left')\n", "GENE = genesis_watervalues.join(GENE,how='right').join(DOASA_watervalues,how='left')\n", "CTCT = CTCT.join(DOASA_watervalues,how='left')\n", "MERI.head()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "# correlations" ] }, { "cell_type": "code", "execution_count": 22, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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WaterValueTradingPeriodMegawattTotMWpercentWeightstarPrice_exc300WeightstarPricemarginal_H20_value
WaterValue1.000000-0.0000020.0239420.1003610.0167220.2550300.0314200.559460
TradingPeriod-0.0000021.000000-0.2985320.080542-0.312075-0.235219-0.3067810.000247
Megawatt0.023942-0.2985321.0000000.2471580.9949110.5002180.9833840.203704
TotMW0.1003610.0805420.2471581.0000000.164040-0.0187350.1609170.301959
percent0.016722-0.3120750.9949110.1640401.0000000.5160630.9887900.181426
WeightstarPrice_exc3000.255030-0.2352190.500218-0.0187350.5160631.0000000.5478060.092048
WeightstarPrice0.031420-0.3067810.9833840.1609170.9887900.5478061.0000000.190236
marginal_H20_value0.5594600.0002470.2037040.3019590.1814260.0920480.1902361.000000
\n", "
" ], "text/plain": [ " WaterValue TradingPeriod Megawatt TotMW percent WeightstarPrice_exc300 WeightstarPrice marginal_H20_value\n", "WaterValue 1.000000 -0.000002 0.023942 0.100361 0.016722 0.255030 0.031420 0.559460\n", "TradingPeriod -0.000002 1.000000 -0.298532 0.080542 -0.312075 -0.235219 -0.306781 0.000247\n", "Megawatt 0.023942 -0.298532 1.000000 0.247158 0.994911 0.500218 0.983384 0.203704\n", "TotMW 0.100361 0.080542 0.247158 1.000000 0.164040 -0.018735 0.160917 0.301959\n", "percent 0.016722 -0.312075 0.994911 0.164040 1.000000 0.516063 0.988790 0.181426\n", "WeightstarPrice_exc300 0.255030 -0.235219 0.500218 -0.018735 0.516063 1.000000 0.547806 0.092048\n", "WeightstarPrice 0.031420 -0.306781 0.983384 0.160917 0.988790 0.547806 1.000000 0.190236\n", "marginal_H20_value 0.559460 0.000247 0.203704 0.301959 0.181426 0.092048 0.190236 1.000000" ] }, "execution_count": 22, "metadata": {}, "output_type": "execute_result" } ], "source": [ "MERI['2016/1/6':'2018/9/30'].corr(method='spearman')" ] }, { "cell_type": "code", "execution_count": 23, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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WaterValueTradingPeriodMegawattTotMWpercentWeightstarPrice_exc300WeightstarPricemarginal_H20_value
WaterValue1.000000-0.0001580.0366700.0046530.0375960.505319-0.0875800.791397
TradingPeriod-0.0001581.000000-0.2958900.023537-0.305904-0.048117-0.2807630.000137
Megawatt0.036670-0.2958901.0000000.2791050.9942880.2676110.871251-0.008581
TotMW0.0046530.0235370.2791051.0000000.1903130.1331260.2876300.021484
percent0.037596-0.3059040.9942880.1903131.0000000.2609470.862330-0.010165
WeightstarPrice_exc3000.505319-0.0481170.2676110.1331260.2609471.0000000.3273230.233938
WeightstarPrice-0.087580-0.2807630.8712510.2876300.8623300.3273231.000000-0.216562
marginal_H20_value0.7913970.000137-0.0085810.021484-0.0101650.233938-0.2165621.000000
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" ], "text/plain": [ " WaterValue TradingPeriod Megawatt TotMW percent WeightstarPrice_exc300 WeightstarPrice marginal_H20_value\n", "WaterValue 1.000000 -0.000158 0.036670 0.004653 0.037596 0.505319 -0.087580 0.791397\n", "TradingPeriod -0.000158 1.000000 -0.295890 0.023537 -0.305904 -0.048117 -0.280763 0.000137\n", "Megawatt 0.036670 -0.295890 1.000000 0.279105 0.994288 0.267611 0.871251 -0.008581\n", "TotMW 0.004653 0.023537 0.279105 1.000000 0.190313 0.133126 0.287630 0.021484\n", "percent 0.037596 -0.305904 0.994288 0.190313 1.000000 0.260947 0.862330 -0.010165\n", "WeightstarPrice_exc300 0.505319 -0.048117 0.267611 0.133126 0.260947 1.000000 0.327323 0.233938\n", "WeightstarPrice -0.087580 -0.280763 0.871251 0.287630 0.862330 0.327323 1.000000 -0.216562\n", "marginal_H20_value 0.791397 0.000137 -0.008581 0.021484 -0.010165 0.233938 -0.216562 1.000000" ] }, "execution_count": 23, "metadata": {}, "output_type": "execute_result" } ], "source": [ "MERI['2019/1/1':'2021/3/31'].corr(method='spearman')" ] }, { "cell_type": "code", "execution_count": 24, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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WaterValueTradingPeriodMegawattTotMWpercentWeightstarPrice_exc300WeightstarPricemarginal_H20_value
WaterValue1.0000000.0001130.090417-0.0651690.0802660.1877500.1494530.333138
TradingPeriod0.0001131.000000-0.007862-0.031329-0.007714-0.298789-0.2247170.000246
Megawatt0.090417-0.0078621.0000000.3325090.996793-0.2556110.7645810.437369
TotMW-0.065169-0.0313290.3325091.0000000.290802-0.1211100.2369940.085408
percent0.080266-0.0077140.9967930.2908021.000000-0.2606540.7651410.435911
WeightstarPrice_exc3000.187750-0.298789-0.255611-0.121110-0.2606541.0000000.300692-0.113565
WeightstarPrice0.149453-0.2247170.7645810.2369940.7651410.3006921.0000000.322663
marginal_H20_value0.3331380.0002460.4373690.0854080.435911-0.1135650.3226631.000000
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" ], "text/plain": [ " WaterValue TradingPeriod Megawatt TotMW percent WeightstarPrice_exc300 WeightstarPrice marginal_H20_value\n", "WaterValue 1.000000 0.000113 0.090417 -0.065169 0.080266 0.187750 0.149453 0.333138\n", "TradingPeriod 0.000113 1.000000 -0.007862 -0.031329 -0.007714 -0.298789 -0.224717 0.000246\n", "Megawatt 0.090417 -0.007862 1.000000 0.332509 0.996793 -0.255611 0.764581 0.437369\n", "TotMW -0.065169 -0.031329 0.332509 1.000000 0.290802 -0.121110 0.236994 0.085408\n", "percent 0.080266 -0.007714 0.996793 0.290802 1.000000 -0.260654 0.765141 0.435911\n", "WeightstarPrice_exc300 0.187750 -0.298789 -0.255611 -0.121110 -0.260654 1.000000 0.300692 -0.113565\n", "WeightstarPrice 0.149453 -0.224717 0.764581 0.236994 0.765141 0.300692 1.000000 0.322663\n", "marginal_H20_value 0.333138 0.000246 0.437369 0.085408 0.435911 -0.113565 0.322663 1.000000" ] }, "execution_count": 24, "metadata": {}, "output_type": "execute_result" } ], "source": [ "MRPL['2016/1/1':'2018/9/30'].corr(method='spearman')" ] }, { "cell_type": "code", "execution_count": 23, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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WaterValueTradingPeriodMegawattTotMWpercentWeightstarPrice_exc300WeightstarPricemarginal_H20_value
WaterValue1.0000000.0003150.1202130.0282850.127819-0.0169320.3980270.448709
TradingPeriod0.0003151.000000-0.433580-0.089824-0.438439-0.337443-0.2579690.000137
Megawatt0.120213-0.4335801.0000000.3361250.9897570.4905040.7121240.080830
TotMW0.028285-0.0898240.3361251.0000000.2126200.1320900.068743-0.179225
percent0.127819-0.4384390.9897570.2126201.0000000.4919200.7310580.114469
WeightstarPrice_exc300-0.016932-0.3374430.4905040.1320900.4919201.0000000.2744180.093539
WeightstarPrice0.398027-0.2579690.7121240.0687430.7310580.2744181.0000000.138533
marginal_H20_value0.4487090.0001370.080830-0.1792250.1144690.0935390.1385331.000000
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" ], "text/plain": [ " WaterValue TradingPeriod Megawatt TotMW percent WeightstarPrice_exc300 WeightstarPrice marginal_H20_value\n", "WaterValue 1.000000 0.000315 0.120213 0.028285 0.127819 -0.016932 0.398027 0.448709\n", "TradingPeriod 0.000315 1.000000 -0.433580 -0.089824 -0.438439 -0.337443 -0.257969 0.000137\n", "Megawatt 0.120213 -0.433580 1.000000 0.336125 0.989757 0.490504 0.712124 0.080830\n", "TotMW 0.028285 -0.089824 0.336125 1.000000 0.212620 0.132090 0.068743 -0.179225\n", "percent 0.127819 -0.438439 0.989757 0.212620 1.000000 0.491920 0.731058 0.114469\n", "WeightstarPrice_exc300 -0.016932 -0.337443 0.490504 0.132090 0.491920 1.000000 0.274418 0.093539\n", "WeightstarPrice 0.398027 -0.257969 0.712124 0.068743 0.731058 0.274418 1.000000 0.138533\n", "marginal_H20_value 0.448709 0.000137 0.080830 -0.179225 0.114469 0.093539 0.138533 1.000000" ] }, "execution_count": 23, "metadata": {}, "output_type": "execute_result" } ], "source": [ "MRPL['2019/1/1':'2021/3/31'].corr(method='spearman')" ] }, { "cell_type": "code", "execution_count": 24, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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MWtimesdollarsVOLUMEWaterValueTradingPeriodMegawattTotMWpercentWeightstarPrice_exc300WeightstarPricemarginal_H20_value
MWtimesdollars1.0000000.9020270.663610-0.0005470.5483680.2554790.5463110.1121510.4085870.431862
VOLUME0.9020271.0000000.4685870.0000150.3985260.2534190.3956900.0562960.2638420.507593
WaterValue0.6636100.4685871.000000-0.0008410.4639410.4863600.4618660.5512060.733836-0.134406
TradingPeriod-0.0005470.000015-0.0008411.000000-0.040291-0.070774-0.0393120.011905-0.0537070.000549
Megawatt0.5483680.3985260.463941-0.0402911.0000000.2768700.999122-0.0463980.5641060.079466
TotMW0.2554790.2534190.486360-0.0707740.2768701.0000000.2619140.5597020.529675-0.167655
percent0.5463110.3956900.461866-0.0393120.9991220.2619141.000000-0.0496590.5636920.077506
WeightstarPrice_exc3000.1121510.0562960.5512060.011905-0.0463980.559702-0.0496591.0000000.735383-0.287638
WeightstarPrice0.4085870.2638420.733836-0.0537070.5641060.5296750.5636920.7353831.000000-0.263720
marginal_H20_value0.4318620.507593-0.1344060.0005490.079466-0.1676550.077506-0.287638-0.2637201.000000
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" ], "text/plain": [ " MWtimesdollars VOLUME WaterValue TradingPeriod Megawatt TotMW percent WeightstarPrice_exc300 WeightstarPrice marginal_H20_value\n", "MWtimesdollars 1.000000 0.902027 0.663610 -0.000547 0.548368 0.255479 0.546311 0.112151 0.408587 0.431862\n", "VOLUME 0.902027 1.000000 0.468587 0.000015 0.398526 0.253419 0.395690 0.056296 0.263842 0.507593\n", "WaterValue 0.663610 0.468587 1.000000 -0.000841 0.463941 0.486360 0.461866 0.551206 0.733836 -0.134406\n", "TradingPeriod -0.000547 0.000015 -0.000841 1.000000 -0.040291 -0.070774 -0.039312 0.011905 -0.053707 0.000549\n", "Megawatt 0.548368 0.398526 0.463941 -0.040291 1.000000 0.276870 0.999122 -0.046398 0.564106 0.079466\n", "TotMW 0.255479 0.253419 0.486360 -0.070774 0.276870 1.000000 0.261914 0.559702 0.529675 -0.167655\n", "percent 0.546311 0.395690 0.461866 -0.039312 0.999122 0.261914 1.000000 -0.049659 0.563692 0.077506\n", "WeightstarPrice_exc300 0.112151 0.056296 0.551206 0.011905 -0.046398 0.559702 -0.049659 1.000000 0.735383 -0.287638\n", "WeightstarPrice 0.408587 0.263842 0.733836 -0.053707 0.564106 0.529675 0.563692 0.735383 1.000000 -0.263720\n", "marginal_H20_value 0.431862 0.507593 -0.134406 0.000549 0.079466 -0.167655 0.077506 -0.287638 -0.263720 1.000000" ] }, "execution_count": 24, "metadata": {}, "output_type": "execute_result" } ], "source": [ "#use for Genesis's water value\n", "GENE['2016/10/1':'2018/9/30'].corr(method='spearman')" ] }, { "cell_type": "code", "execution_count": 25, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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MWtimesdollarsVOLUMEWaterValueTradingPeriodMegawattTotMWpercentWeightstarPrice_exc300WeightstarPricemarginal_H20_value
MWtimesdollars1.0000000.9020270.663610-0.0005470.5483680.2554790.5463110.1121510.4085870.431862
VOLUME0.9020271.0000000.4685870.0000150.3985260.2534190.3956900.0562960.2638420.507593
WaterValue0.6636100.4685871.000000-0.0008410.4639410.4863600.4618660.5512060.733836-0.134406
TradingPeriod-0.0005470.000015-0.0008411.000000-0.032622-0.062406-0.031945-0.016319-0.0645770.000507
Megawatt0.5483680.3985260.463941-0.0326221.0000000.2809080.999449-0.0622270.4827580.203720
TotMW0.2554790.2534190.486360-0.0624060.2809081.0000000.2695360.3941020.401070-0.132151
percent0.5463110.3956900.461866-0.0319450.9994490.2695361.000000-0.0649100.4825630.202244
WeightstarPrice_exc3000.1121510.0562960.551206-0.016319-0.0622270.394102-0.0649101.0000000.791108-0.305757
WeightstarPrice0.4085870.2638420.733836-0.0645770.4827580.4010700.4825630.7911081.000000-0.224134
marginal_H20_value0.4318620.507593-0.1344060.0005070.203720-0.1321510.202244-0.305757-0.2241341.000000
\n", "
" ], "text/plain": [ " MWtimesdollars VOLUME WaterValue TradingPeriod Megawatt TotMW percent WeightstarPrice_exc300 WeightstarPrice marginal_H20_value\n", "MWtimesdollars 1.000000 0.902027 0.663610 -0.000547 0.548368 0.255479 0.546311 0.112151 0.408587 0.431862\n", "VOLUME 0.902027 1.000000 0.468587 0.000015 0.398526 0.253419 0.395690 0.056296 0.263842 0.507593\n", "WaterValue 0.663610 0.468587 1.000000 -0.000841 0.463941 0.486360 0.461866 0.551206 0.733836 -0.134406\n", "TradingPeriod -0.000547 0.000015 -0.000841 1.000000 -0.032622 -0.062406 -0.031945 -0.016319 -0.064577 0.000507\n", "Megawatt 0.548368 0.398526 0.463941 -0.032622 1.000000 0.280908 0.999449 -0.062227 0.482758 0.203720\n", "TotMW 0.255479 0.253419 0.486360 -0.062406 0.280908 1.000000 0.269536 0.394102 0.401070 -0.132151\n", "percent 0.546311 0.395690 0.461866 -0.031945 0.999449 0.269536 1.000000 -0.064910 0.482563 0.202244\n", "WeightstarPrice_exc300 0.112151 0.056296 0.551206 -0.016319 -0.062227 0.394102 -0.064910 1.000000 0.791108 -0.305757\n", "WeightstarPrice 0.408587 0.263842 0.733836 -0.064577 0.482758 0.401070 0.482563 0.791108 1.000000 -0.224134\n", "marginal_H20_value 0.431862 0.507593 -0.134406 0.000507 0.203720 -0.132151 0.202244 -0.305757 -0.224134 1.000000" ] }, "execution_count": 25, "metadata": {}, "output_type": "execute_result" } ], "source": [ "#use for DOASA water value\n", "GENE['2016/1/1':'2018/9/30'].corr(method='spearman')" ] }, { "cell_type": "code", "execution_count": 26, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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MWtimesdollarsVOLUMEWaterValueTradingPeriodMegawattTotMWpercentWeightstarPrice_exc300WeightstarPricemarginal_H20_value
MWtimesdollars1.0000000.4801590.909272-0.0004910.4538460.4064150.4224210.5730770.4683150.608455
VOLUME0.4801591.0000000.2032270.0000270.072785-0.0277990.0685160.3311880.0855320.148434
WaterValue0.9092720.2032271.000000-0.0005430.5278080.4774260.4948560.6365500.5461050.561445
TradingPeriod-0.0004910.000027-0.0005431.000000-0.096122-0.032181-0.0962180.156125-0.0847640.000427
Megawatt0.4538460.0727850.527808-0.0961221.0000000.3157670.9836800.2556030.9742000.078042
TotMW0.406415-0.0277990.477426-0.0321810.3157671.0000000.1985150.5000860.2266340.200025
percent0.4224210.0685160.494856-0.0962180.9836800.1985151.0000000.2030810.9893030.060035
WeightstarPrice_exc3000.5730770.3311880.6365500.1561250.2556030.5000860.2030811.0000000.2962780.341004
WeightstarPrice0.4683150.0855320.546105-0.0847640.9742000.2266340.9893030.2962781.0000000.090901
marginal_H20_value0.6084550.1484340.5614450.0004270.0780420.2000250.0600350.3410040.0909011.000000
\n", "
" ], "text/plain": [ " MWtimesdollars VOLUME WaterValue TradingPeriod Megawatt TotMW percent WeightstarPrice_exc300 WeightstarPrice marginal_H20_value\n", "MWtimesdollars 1.000000 0.480159 0.909272 -0.000491 0.453846 0.406415 0.422421 0.573077 0.468315 0.608455\n", "VOLUME 0.480159 1.000000 0.203227 0.000027 0.072785 -0.027799 0.068516 0.331188 0.085532 0.148434\n", "WaterValue 0.909272 0.203227 1.000000 -0.000543 0.527808 0.477426 0.494856 0.636550 0.546105 0.561445\n", "TradingPeriod -0.000491 0.000027 -0.000543 1.000000 -0.096122 -0.032181 -0.096218 0.156125 -0.084764 0.000427\n", "Megawatt 0.453846 0.072785 0.527808 -0.096122 1.000000 0.315767 0.983680 0.255603 0.974200 0.078042\n", "TotMW 0.406415 -0.027799 0.477426 -0.032181 0.315767 1.000000 0.198515 0.500086 0.226634 0.200025\n", "percent 0.422421 0.068516 0.494856 -0.096218 0.983680 0.198515 1.000000 0.203081 0.989303 0.060035\n", "WeightstarPrice_exc300 0.573077 0.331188 0.636550 0.156125 0.255603 0.500086 0.203081 1.000000 0.296278 0.341004\n", "WeightstarPrice 0.468315 0.085532 0.546105 -0.084764 0.974200 0.226634 0.989303 0.296278 1.000000 0.090901\n", "marginal_H20_value 0.608455 0.148434 0.561445 0.000427 0.078042 0.200025 0.060035 0.341004 0.090901 1.000000" ] }, "execution_count": 26, "metadata": {}, "output_type": "execute_result" } ], "source": [ "GENE['2019/1/1':'2021/3/31'].corr(method='spearman')" ] }, { "cell_type": "code", "execution_count": 27, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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TradingPeriodMegawattTotMWpercentWeightstarPrice_exc300WeightstarPricemarginal_H20_value
TradingPeriod1.000000-0.072013-0.102023-0.072510-0.168389-0.1732700.000246
Megawatt-0.0720131.0000000.2351030.999663-0.3421880.8372460.680094
TotMW-0.1020230.2351031.0000000.2224680.0924000.2834930.087482
percent-0.0725100.9996630.2224681.000000-0.3455470.8373810.680415
WeightstarPrice_exc300-0.168389-0.3421880.092400-0.3455471.0000000.091826-0.130310
WeightstarPrice-0.1732700.8372460.2834930.8373810.0918261.0000000.581712
marginal_H20_value0.0002460.6800940.0874820.680415-0.1303100.5817121.000000
\n", "
" ], "text/plain": [ " TradingPeriod Megawatt TotMW percent WeightstarPrice_exc300 WeightstarPrice marginal_H20_value\n", "TradingPeriod 1.000000 -0.072013 -0.102023 -0.072510 -0.168389 -0.173270 0.000246\n", "Megawatt -0.072013 1.000000 0.235103 0.999663 -0.342188 0.837246 0.680094\n", "TotMW -0.102023 0.235103 1.000000 0.222468 0.092400 0.283493 0.087482\n", "percent -0.072510 0.999663 0.222468 1.000000 -0.345547 0.837381 0.680415\n", "WeightstarPrice_exc300 -0.168389 -0.342188 0.092400 -0.345547 1.000000 0.091826 -0.130310\n", "WeightstarPrice -0.173270 0.837246 0.283493 0.837381 0.091826 1.000000 0.581712\n", "marginal_H20_value 0.000246 0.680094 0.087482 0.680415 -0.130310 0.581712 1.000000" ] }, "execution_count": 27, "metadata": {}, "output_type": "execute_result" } ], "source": [ "CTCT['2016/1/1':'2018/9/30'].corr(method='spearman')" ] }, { "cell_type": "code", "execution_count": 28, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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TradingPeriodMegawattTotMWpercentWeightstarPrice_exc300WeightstarPricemarginal_H20_value
TradingPeriod1.000000-0.284155-0.070354-0.281284-0.093538-0.2479790.000137
Megawatt-0.2841551.0000000.2185450.996345-0.2566950.8885670.315246
TotMW-0.0703540.2185451.0000000.1527020.0331380.211423-0.155604
percent-0.2812840.9963450.1527021.000000-0.2663100.8836220.329415
WeightstarPrice_exc300-0.093538-0.2566950.033138-0.2663101.000000-0.218696-0.069476
WeightstarPrice-0.2479790.8885670.2114230.883622-0.2186961.0000000.270193
marginal_H20_value0.0001370.315246-0.1556040.329415-0.0694760.2701931.000000
\n", "
" ], "text/plain": [ " TradingPeriod Megawatt TotMW percent WeightstarPrice_exc300 WeightstarPrice marginal_H20_value\n", "TradingPeriod 1.000000 -0.284155 -0.070354 -0.281284 -0.093538 -0.247979 0.000137\n", "Megawatt -0.284155 1.000000 0.218545 0.996345 -0.256695 0.888567 0.315246\n", "TotMW -0.070354 0.218545 1.000000 0.152702 0.033138 0.211423 -0.155604\n", "percent -0.281284 0.996345 0.152702 1.000000 -0.266310 0.883622 0.329415\n", "WeightstarPrice_exc300 -0.093538 -0.256695 0.033138 -0.266310 1.000000 -0.218696 -0.069476\n", "WeightstarPrice -0.247979 0.888567 0.211423 0.883622 -0.218696 1.000000 0.270193\n", "marginal_H20_value 0.000137 0.315246 -0.155604 0.329415 -0.069476 0.270193 1.000000" ] }, "execution_count": 28, "metadata": {}, "output_type": "execute_result" } ], "source": [ "CTCT['2019/1/1':'2021/3/31'].corr(method='spearman')" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "# plot QWOPs and watervalues" ] }, { "cell_type": "code", "execution_count": 39, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "count 121561.000000\n", "mean 25.584433\n", "std 56.565043\n", "min -0.001926\n", "25% 0.010000\n", "50% 7.440645\n", "75% 18.456450\n", "max 298.080000\n", "Name: WeightstarPrice_exc300, dtype: float64" ] }, "execution_count": 39, "metadata": {}, "output_type": "execute_result" } ], "source": [ "GENE.WeightstarPrice_exc300.describe()" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "#all its offers are priced over $300/MWh in some trading periods, so the WeightstarPrice_exc300 is NA" ] }, { "cell_type": "code", "execution_count": 27, "metadata": {}, "outputs": [ { "data": { "image/png": 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\n", "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "fig = plt.figure(23,figsize=[cm2inch(25),cm2inch(25)])\n", "\n", "#----------------------------------------------------------------------------------------------------------------------\n", "\n", "ax=fig.add_subplot(111)\n", "\n", "plt.rcParams['xtick.major.size'] = 3\n", "plt.rcParams['xtick.major.width'] = 1\n", "plt.rcParams['xtick.minor.size'] = 3\n", "plt.rcParams['xtick.minor.width'] = 1\n", "\n", "plt.rcParams['ytick.major.size'] = 0\n", "plt.rcParams['ytick.major.width'] = 0\n", "plt.rcParams['ytick.minor.size'] = 0\n", "plt.rcParams['ytick.minor.width'] = 0\n", "plt.rcParams['xtick.major.pad']=7.8\n", "plt.rcParams['ytick.major.pad']=7.8\n", "mpl.rcParams['figure.subplot.bottom']=0.25\n", "\n", "lns1=ax.plot(MERI.index, MERI['WeightstarPrice'].rolling(48*365,center=True).mean(), label='QWOP',color=(ea_p['rd1']) )\n", "lns2=ax.plot(MERI.index, MERI['WaterValue'].rolling(48*365,center=True).mean(), label='Meridians water value',color=(ea_p['bl1']) )\n", "lns3=ax.plot(MERI.index, MERI['marginal_H20_value'].rolling(48*365,center=True).mean(), label='DOASA water value',color=(ea_p['bl2']) )\n", "\n", "ax.xaxis.tick_bottom()\n", "ax.set_frame_on(False)\n", "ax.axhline(y=0.1, lw=2, color='k') \n", "ax.grid(b=True, which='major', color='k', linestyle='-', axis='y',alpha=0.6, clip_on=True , marker=None )\n", "ax.grid(b=False, axis='x', which='both')\n", "ax.set_axisbelow(True)\n", "yearsFmt = mdates.DateFormatter('%Y')\n", "ax.xaxis.set_major_formatter(yearsFmt)\n", "def func(x, pos): # formatter function takes tick label and tick position\n", " s = '{:0,d}'.format(int(x))\n", " return s\n", "setp(ax.get_xticklabels(), rotation =0, fontsize=10)\n", "setp(ax.get_yticklabels(), fontsize=10 )\n", "ax.set_ylabel(r\"$/MWh\", fontsize=10, family='arial', rotation=90 )\n", "ax.set_xlabel('Date', fontsize=10,family='arial').set_visible(False)\n", "#lns = lns1+lns2\n", "lns = lns1+lns2+lns3\n", "labs = [l.get_label() for l in lns]\n", "ax.legend(lns, labs, loc=3, bbox_to_anchor=(-0.025, -0.33+0.15),fancybox=False, shadow=False, \n", " frameon=False ,ncol=3, fontsize=12)\n", "\n", "plt.savefig(path +'/pics/Meridian_QWOP_v_watervalues.png', dpi=500, format='png', bbox_inches='tight')" ] }, { "cell_type": "code", "execution_count": 21, "metadata": {}, "outputs": [ { "data": { "image/png": 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\n", "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "fig = plt.figure(23,figsize=[cm2inch(25),cm2inch(25)])\n", "\n", "ax=fig.add_subplot(111)\n", "\n", "plt.rcParams['xtick.major.size'] = 3\n", "plt.rcParams['xtick.major.width'] = 1\n", "plt.rcParams['xtick.minor.size'] = 3\n", "plt.rcParams['xtick.minor.width'] = 1\n", "\n", "plt.rcParams['ytick.major.size'] = 0\n", "plt.rcParams['ytick.major.width'] = 0\n", "plt.rcParams['ytick.minor.size'] = 0\n", "plt.rcParams['ytick.minor.width'] = 0\n", "plt.rcParams['xtick.major.pad']=7.8\n", "plt.rcParams['ytick.major.pad']=7.8\n", "mpl.rcParams['figure.subplot.bottom']=0.25\n", "\n", "lns1=ax.plot(MRPL.index, MRPL['WeightstarPrice'].rolling(48*365,center=True).mean(), label='QWOP',color=(ea_p['rd1']) )\n", "lns2=ax.plot(MRPL.index, MRPL['WaterValue'].rolling(48*365,center=True).mean(), label='Mercurys water value',color=(ea_p['bl1']) )\n", "lns3=ax.plot(MRPL.index, MRPL['marginal_H20_value'].rolling(48*365,center=True).mean(), label='DOASA water value',color=(ea_p['bl2']) )\n", "\n", "ax.xaxis.tick_bottom()\n", "ax.set_frame_on(False)\n", "ax.axhline(y=0.1, lw=2, color='k') \n", "ax.grid(b=True, which='major', color='k', linestyle='-', axis='y',alpha=0.6, clip_on=True , marker=None )\n", "ax.grid(b=False, axis='x', which='both')\n", "ax.set_axisbelow(True)\n", "yearsFmt = mdates.DateFormatter('%Y')\n", "ax.xaxis.set_major_formatter(yearsFmt)\n", "def func(x, pos): # formatter function takes tick label and tick position\n", " s = '{:0,d}'.format(int(x))\n", " return s\n", "\n", "setp(ax.get_xticklabels(), rotation =0, fontsize=10)\n", "setp(ax.get_yticklabels(), fontsize=10 )\n", "ax.set_ylabel(r\"$/MWh\", fontsize=10, family='arial', rotation=90 ).set_visible(False)\n", "ax.set_xlabel('Date', fontsize=10,family='arial').set_visible(False)\n", "lns = lns1+lns2+lns3\n", "labs = [l.get_label() for l in lns]\n", "ax.legend(lns, labs, loc=3, bbox_to_anchor=(-0.025, -0.33+0.15),fancybox=False, shadow=False, \n", " frameon=False ,ncol=3, fontsize=12)\n", "\n", "plt.savefig(path +'/pics/Mercury_QWOP_v_watervalues.png', dpi=500, format='png', bbox_inches='tight')" ] }, { "cell_type": "code", "execution_count": 23, "metadata": {}, "outputs": [ { "data": { "image/png": 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\n", "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "fig = plt.figure(23,figsize=[cm2inch(25),cm2inch(25)])\n", "ax=fig.add_subplot(111)\n", "\n", "plt.rcParams['xtick.major.size'] = 3\n", "plt.rcParams['xtick.major.width'] = 1\n", "plt.rcParams['xtick.minor.size'] = 3\n", "plt.rcParams['xtick.minor.width'] = 1\n", "\n", "plt.rcParams['ytick.major.size'] = 0\n", "plt.rcParams['ytick.major.width'] = 0\n", "plt.rcParams['ytick.minor.size'] = 0\n", "plt.rcParams['ytick.minor.width'] = 0\n", "plt.rcParams['xtick.major.pad']=7.8\n", "plt.rcParams['ytick.major.pad']=7.8\n", "mpl.rcParams['figure.subplot.bottom']=0.25\n", "\n", "lns1=ax.plot(GENE.index, GENE['WeightstarPrice'].rolling(48*365,center=True).mean(), label='QWOP',color=(ea_p['rd1']) )\n", "lns2=ax.plot(GENE.index, GENE['WaterValue'].rolling(48*365,center=True).mean(), label='Generators water value',color=(ea_p['bl1']) )\n", "lns3=ax.plot(GENE.index, GENE['marginal_H20_value'].rolling(48*365,center=True).mean(), label='DOASA water value',color=(ea_p['bl2']) )\n", "\n", "ax.xaxis.tick_bottom()\n", "ax.set_frame_on(False)\n", "ax.axhline(y=0.1, lw=2, color='k') \n", "ax.grid(b=True, which='major', color='k', linestyle='-', axis='y',alpha=0.6, clip_on=True , marker=None )\n", "ax.grid(b=False, axis='x', which='both')\n", "ax.set_axisbelow(True)\n", "yearsFmt = mdates.DateFormatter('%Y')\n", "ax.xaxis.set_major_formatter(yearsFmt)\n", "def func(x, pos): # formatter function takes tick label and tick position\n", " s = '{:0,d}'.format(int(x))\n", " return s\n", "\n", "setp(ax.get_xticklabels(), rotation =0, fontsize=10)\n", "setp(ax.get_yticklabels(), fontsize=10)\n", "ax.set_ylabel(r\"$/MWh\", fontsize=10, family='arial', rotation=90 ).set_visible(False)\n", "ax.set_xlabel('Date', fontsize=10,family='arial').set_visible(False)\n", "#lns = lns1+lns2\n", "lns = lns1+lns2+lns3\n", "labs = [l.get_label() for l in lns]\n", "ax.legend(lns, labs, loc=3, bbox_to_anchor=(-0.025, -0.33+0.15),fancybox=False, shadow=False, \n", " frameon=False ,ncol=3, fontsize=12)\n", "\n", "\n", "plt.savefig(path +'/pics/Genesis_QWOP_v_watervalues.png', dpi=500, format='png', bbox_inches='tight')" ] }, { "cell_type": "code", "execution_count": 27, "metadata": {}, "outputs": [ { "data": { "image/png": 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\n", "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "#do hydro ones as panels in the same chart\n", "\n", "fig = plt.figure(23,figsize=[cm2inch(25),cm2inch(25)])\n", "\n", "#----------------------------------------------------------------------------------------------------------------------\n", "\n", "ax=fig.add_subplot(221)\n", "\n", "plt.rcParams['xtick.major.size'] = 3\n", "plt.rcParams['xtick.major.width'] = 1\n", "plt.rcParams['xtick.minor.size'] = 3\n", "plt.rcParams['xtick.minor.width'] = 1\n", "\n", "plt.rcParams['ytick.major.size'] = 0\n", "plt.rcParams['ytick.major.width'] = 0\n", "plt.rcParams['ytick.minor.size'] = 0\n", "plt.rcParams['ytick.minor.width'] = 0\n", "plt.rcParams['xtick.major.pad']=7.8\n", "plt.rcParams['ytick.major.pad']=7.8\n", "mpl.rcParams['figure.subplot.bottom']=0.25\n", "\n", "lns1=ax.plot(MERI.index, MERI['WeightstarPrice'].rolling(48*365,center=True).mean(), label='QWOP',color=(ea_p['rd1']) )\n", "lns2=ax.plot(MERI.index, MERI['WaterValue'].rolling(48*365,center=True).mean(), label='Meridians water value',color=(ea_p['bl1']) )\n", "lns3=ax.plot(MERI.index, MERI['marginal_H20_value'].rolling(48*365,center=True).mean(), label='DOASA water value',color=(ea_p['bl2']) )\n", "\n", "ax.xaxis.tick_bottom()\n", "ax.set_frame_on(False)\n", "ax.axhline(y=0.1, lw=2, color='k') \n", "ax.grid(b=True, which='major', color='k', linestyle='-', axis='y',alpha=0.6, clip_on=True , marker=None )\n", "ax.grid(b=False, axis='x', which='both')\n", "ax.set_axisbelow(True)\n", "yearsFmt = mdates.DateFormatter('%Y')\n", "ax.xaxis.set_major_formatter(yearsFmt)\n", "def func(x, pos): # formatter function takes tick label and tick position\n", " s = '{:0,d}'.format(int(x))\n", " return s\n", "setp(ax.get_xticklabels(), rotation =0, fontsize=10)\n", "setp(ax.get_yticklabels(), fontsize=10 )\n", "ax.set_ylabel(r\"$/MWh\", fontsize=10, family='arial', rotation=90 )\n", "ax.set_xlabel('Date', fontsize=10,family='arial').set_visible(False)\n", "#lns = lns1+lns2\n", "lns = lns1+lns2+lns3\n", "labs = [l.get_label() for l in lns]\n", "ax.legend(lns, labs, loc=3, bbox_to_anchor=(-0.025, -0.33+0.15),fancybox=False, shadow=False, \n", " frameon=False ,ncol=3, fontsize=12).set_visible(False)\n", "plt.title('Waitaki',x=0.5, y=1)\n", "\n", "#----------------------------------------------------------------------------------------------------------------------\n", "\n", "ax=fig.add_subplot(222)\n", "\n", "plt.rcParams['xtick.major.size'] = 3\n", "plt.rcParams['xtick.major.width'] = 1\n", "plt.rcParams['xtick.minor.size'] = 3\n", "plt.rcParams['xtick.minor.width'] = 1\n", "\n", "plt.rcParams['ytick.major.size'] = 0\n", "plt.rcParams['ytick.major.width'] = 0\n", "plt.rcParams['ytick.minor.size'] = 0\n", "plt.rcParams['ytick.minor.width'] = 0\n", "plt.rcParams['xtick.major.pad']=7.8\n", "plt.rcParams['ytick.major.pad']=7.8\n", "mpl.rcParams['figure.subplot.bottom']=0.25\n", "\n", "lns1=ax.plot(MRPL.index, MRPL['WeightstarPrice'].rolling(48*365,center=True).mean(), label='QWOP',color=(ea_p['rd1']) )\n", "lns2=ax.plot(MRPL.index, MRPL['WaterValue'].rolling(48*365,center=True).mean(), label='Mercurys water value',color=(ea_p['bl1']) )\n", "lns3=ax.plot(MRPL.index, MRPL['marginal_H20_value'].rolling(48*365,center=True).mean(), label='DOASA water value',color=(ea_p['bl2']) )\n", "\n", "ax.xaxis.tick_bottom()\n", "ax.set_frame_on(False)\n", "ax.axhline(y=0.1, lw=2, color='k') \n", "ax.grid(b=True, which='major', color='k', linestyle='-', axis='y',alpha=0.6, clip_on=True , marker=None )\n", "ax.grid(b=False, axis='x', which='both')\n", "ax.set_axisbelow(True)\n", "yearsFmt = mdates.DateFormatter('%Y')\n", "ax.xaxis.set_major_formatter(yearsFmt)\n", "def func(x, pos): # formatter function takes tick label and tick position\n", " s = '{:0,d}'.format(int(x))\n", " return s\n", "\n", "setp(ax.get_xticklabels(), rotation =0, fontsize=10)\n", "setp(ax.get_yticklabels(), fontsize=10 )\n", "ax.set_ylabel(r\"$/MWh\", fontsize=10, family='arial', rotation=90 ).set_visible(False)\n", "ax.set_xlabel('Date', fontsize=10,family='arial').set_visible(False)\n", "lns = lns1+lns2+lns3\n", "labs = [l.get_label() for l in lns]\n", "ax.legend(lns, labs, loc=3, bbox_to_anchor=(-0.025, -0.33+0.15),fancybox=False, shadow=False, \n", " frameon=False ,ncol=3, fontsize=12).set_visible(False)\n", "plt.title('Waikato',x=0.5, y=1)\n", "\n", "#----------------------------------------------------------------------------------------------------------------------\n", "\n", "ax=fig.add_subplot(223)\n", "\n", "plt.rcParams['xtick.major.size'] = 3\n", "plt.rcParams['xtick.major.width'] = 1\n", "plt.rcParams['xtick.minor.size'] = 3\n", "plt.rcParams['xtick.minor.width'] = 1\n", "\n", "plt.rcParams['ytick.major.size'] = 0\n", "plt.rcParams['ytick.major.width'] = 0\n", "plt.rcParams['ytick.minor.size'] = 0\n", "plt.rcParams['ytick.minor.width'] = 0\n", "plt.rcParams['xtick.major.pad']=7.8\n", "plt.rcParams['ytick.major.pad']=7.8\n", "mpl.rcParams['figure.subplot.bottom']=0.25\n", "\n", "lns1=ax.plot(CTCT.index, CTCT['WeightstarPrice'].rolling(48*365,center=True).mean(), label='QWOP',color=(ea_p['rd1']) )\n", "#lns2=ax.plot(MRPL.index, MRPL['WaterValue'].rolling(48*365,center=True).mean(), label='Mercurys water value',color=(ea_p['bl1']) )\n", "lns3=ax.plot(CTCT.index, CTCT['marginal_H20_value'].rolling(48*365,center=True).mean(), label='DOASA water value',color=(ea_p['bl2']) )\n", "\n", "\n", "ax.xaxis.tick_bottom()\n", "ax.set_frame_on(False)\n", "ax.axhline(y=0.1, lw=2, color='k') \n", "ax.grid(b=True, which='major', color='k', linestyle='-', axis='y',alpha=0.6, clip_on=True , marker=None )\n", "ax.grid(b=False, axis='x', which='both')\n", "ax.set_axisbelow(True)\n", "yearsFmt = mdates.DateFormatter('%Y')\n", "ax.xaxis.set_major_formatter(yearsFmt)\n", "def func(x, pos): # formatter function takes tick label and tick position\n", " s = '{:0,d}'.format(int(x))\n", " return s\n", "\n", "setp(ax.get_xticklabels(), rotation =0, fontsize=10)\n", "setp(ax.get_yticklabels(), fontsize=10)\n", "ax.set_ylabel(r\"$/MWh\", fontsize=10, family='arial', rotation=90 )\n", "ax.set_xlabel('Date', fontsize=10,family='arial').set_visible(False)\n", "lns = lns1+lns3\n", "labs = [l.get_label() for l in lns]\n", "ax.legend(lns, labs, loc=3, bbox_to_anchor=(-0.025, -0.33+0.05),fancybox=False, shadow=False, \n", " frameon=False ,ncol=3, fontsize=10).set_visible(False)\n", "plt.title('Clutha',x=0.5, y=1)\n", "\n", "#----------------------------------------------------------------------------------------------------------------------\n", "\n", "ax=fig.add_subplot(224)\n", "\n", "plt.rcParams['xtick.major.size'] = 3\n", "plt.rcParams['xtick.major.width'] = 1\n", "plt.rcParams['xtick.minor.size'] = 3\n", "plt.rcParams['xtick.minor.width'] = 1\n", "\n", "plt.rcParams['ytick.major.size'] = 0\n", "plt.rcParams['ytick.major.width'] = 0\n", "plt.rcParams['ytick.minor.size'] = 0\n", "plt.rcParams['ytick.minor.width'] = 0\n", "plt.rcParams['xtick.major.pad']=7.8\n", "plt.rcParams['ytick.major.pad']=7.8\n", "mpl.rcParams['figure.subplot.bottom']=0.25\n", "\n", "lns1=ax.plot(GENE.index, GENE['WeightstarPrice'].rolling(48*365,center=True).mean(), label='QWOP',color=(ea_p['rd1']) )\n", "lns2=ax.plot(GENE.index, GENE['WaterValue'].rolling(48*365,center=True).mean(), label='Generators water value',color=(ea_p['bl1']) )\n", "lns3=ax.plot(GENE.index, GENE['marginal_H20_value'].rolling(48*365,center=True).mean(), label='DOASA water value',color=(ea_p['bl2']) )\n", "\n", "ax.xaxis.tick_bottom()\n", "ax.set_frame_on(False)\n", "ax.axhline(y=0.1, lw=2, color='k') \n", "ax.grid(b=True, which='major', color='k', linestyle='-', axis='y',alpha=0.6, clip_on=True , marker=None )\n", "ax.grid(b=False, axis='x', which='both')\n", "ax.set_axisbelow(True)\n", "yearsFmt = mdates.DateFormatter('%Y')\n", "ax.xaxis.set_major_formatter(yearsFmt)\n", "def func(x, pos): # formatter function takes tick label and tick position\n", " s = '{:0,d}'.format(int(x))\n", " return s\n", "\n", "setp(ax.get_xticklabels(), rotation =0, fontsize=10)\n", "setp(ax.get_yticklabels(), fontsize=10)\n", "ax.set_ylabel(r\"$/MWh\", fontsize=10, family='arial', rotation=90 ).set_visible(False)\n", "ax.set_xlabel('Date', fontsize=10,family='arial').set_visible(False)\n", "#lns = lns1+lns2\n", "lns = lns1+lns2+lns3\n", "labs = [l.get_label() for l in lns]\n", "ax.legend(lns, labs, loc=3, bbox_to_anchor=(-1.2, -0.30),fancybox=False, shadow=False, \n", " frameon=False ,ncol=3, fontsize=10)\n", "plt.title('Tekapo',x=0.5, y=1)\n", "\n", "an1=ax.annotate(\"Sources: Electricity Authority, Generators\",\n", " xy=(0.27, 0.1), xycoords='figure fraction',color='k',\n", " xytext=(.145-0.06\n", " , 0.07), textcoords='figure fraction',\n", " fontsize=12)\n", "\n", "plt.savefig(path +'/pics/QWOPs_v_watervalues.png', dpi=500, format='png', bbox_inches='tight')" ] }, { "cell_type": "code", "execution_count": 29, "metadata": {}, "outputs": [ { "data": { "image/png": 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\n", "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "#do hydro ones as panels in the same chart\n", "\n", "fig = plt.figure(23,figsize=[cm2inch(25),cm2inch(25)])\n", "\n", "#----------------------------------------------------------------------------------------------------------------------\n", "\n", "ax=fig.add_subplot(221)\n", "\n", "plt.rcParams['xtick.major.size'] = 3\n", "plt.rcParams['xtick.major.width'] = 1\n", "plt.rcParams['xtick.minor.size'] = 3\n", "plt.rcParams['xtick.minor.width'] = 1\n", "\n", "plt.rcParams['ytick.major.size'] = 0\n", "plt.rcParams['ytick.major.width'] = 0\n", "plt.rcParams['ytick.minor.size'] = 0\n", "plt.rcParams['ytick.minor.width'] = 0\n", "plt.rcParams['xtick.major.pad']=7.8\n", "plt.rcParams['ytick.major.pad']=7.8\n", "mpl.rcParams['figure.subplot.bottom']=0.25\n", "\n", "lns1=ax.plot(MERI.index, MERI['WeightstarPrice_exc300'].rolling(48*365,center=True).mean(), label='QWOP exc offers over $300/MWh',color=(ea_p['rd1']) )\n", "lns2=ax.plot(MERI.index, MERI['WaterValue'].rolling(48*365,center=True).mean(), label='Meridians water value',color=(ea_p['bl1']) )\n", "lns3=ax.plot(MERI.index, MERI['marginal_H20_value'].rolling(48*365,center=True).mean(), label='DOASA water value',color=(ea_p['bl2']) )\n", "\n", "ax.xaxis.tick_bottom()\n", "ax.set_frame_on(False)\n", "ax.axhline(y=0.1, lw=2, color='k') \n", "ax.grid(b=True, which='major', color='k', linestyle='-', axis='y',alpha=0.6, clip_on=True , marker=None )\n", "ax.grid(b=False, axis='x', which='both')\n", "ax.set_axisbelow(True)\n", "yearsFmt = mdates.DateFormatter('%Y')\n", "ax.xaxis.set_major_formatter(yearsFmt)\n", "def func(x, pos): # formatter function takes tick label and tick position\n", " s = '{:0,d}'.format(int(x))\n", " return s\n", "setp(ax.get_xticklabels(), rotation =0, fontsize=10)\n", "setp(ax.get_yticklabels(), fontsize=10 )\n", "ax.set_ylabel(r\"$/MWh\", fontsize=10, family='arial', rotation=90 )\n", "ax.set_xlabel('Date', fontsize=10,family='arial').set_visible(False)\n", "#lns = lns1+lns2\n", "lns = lns1+lns2+lns3\n", "labs = [l.get_label() for l in lns]\n", "ax.legend(lns, labs, loc=3, bbox_to_anchor=(-0.025, -0.33+0.15),fancybox=False, shadow=False, \n", " frameon=False ,ncol=3, fontsize=12).set_visible(False)\n", "plt.title('Waitaki',x=0.5, y=1)\n", "\n", "#----------------------------------------------------------------------------------------------------------------------\n", "\n", "ax=fig.add_subplot(222)\n", "\n", "plt.rcParams['xtick.major.size'] = 3\n", "plt.rcParams['xtick.major.width'] = 1\n", "plt.rcParams['xtick.minor.size'] = 3\n", "plt.rcParams['xtick.minor.width'] = 1\n", "\n", "plt.rcParams['ytick.major.size'] = 0\n", "plt.rcParams['ytick.major.width'] = 0\n", "plt.rcParams['ytick.minor.size'] = 0\n", "plt.rcParams['ytick.minor.width'] = 0\n", "plt.rcParams['xtick.major.pad']=7.8\n", "plt.rcParams['ytick.major.pad']=7.8\n", "mpl.rcParams['figure.subplot.bottom']=0.25\n", "\n", "lns1=ax.plot(MRPL.index, MRPL['WeightstarPrice_exc300'].rolling(48*365,center=True).mean(), label='QWOP exc offers over $300/MWh',color=(ea_p['rd1']) )\n", "lns2=ax.plot(MRPL.index, MRPL['WaterValue'].rolling(48*365,center=True).mean(), label='Mercurys water value',color=(ea_p['bl1']) )\n", "lns3=ax.plot(MRPL.index, MRPL['marginal_H20_value'].rolling(48*365,center=True).mean(), label='DOASA water value',color=(ea_p['bl2']) )\n", "\n", "ax.xaxis.tick_bottom()\n", "ax.set_frame_on(False)\n", "ax.axhline(y=0.1, lw=2, color='k') \n", "ax.grid(b=True, which='major', color='k', linestyle='-', axis='y',alpha=0.6, clip_on=True , marker=None )\n", "ax.grid(b=False, axis='x', which='both')\n", "ax.set_axisbelow(True)\n", "yearsFmt = mdates.DateFormatter('%Y')\n", "ax.xaxis.set_major_formatter(yearsFmt)\n", "def func(x, pos): # formatter function takes tick label and tick position\n", " s = '{:0,d}'.format(int(x))\n", " return s\n", "\n", "setp(ax.get_xticklabels(), rotation =0, fontsize=10)\n", "setp(ax.get_yticklabels(), fontsize=10 )\n", "ax.set_ylabel(r\"$/MWh\", fontsize=10, family='arial', rotation=90 ).set_visible(False)\n", "ax.set_xlabel('Date', fontsize=10,family='arial').set_visible(False)\n", "lns = lns1+lns2+lns3\n", "labs = [l.get_label() for l in lns]\n", "ax.legend(lns, labs, loc=3, bbox_to_anchor=(-0.025, -0.33+0.15),fancybox=False, shadow=False, \n", " frameon=False ,ncol=3, fontsize=12).set_visible(False)\n", "plt.title('Waikato',x=0.5, y=1)\n", "\n", "#----------------------------------------------------------------------------------------------------------------------\n", "\n", "ax=fig.add_subplot(223)\n", "\n", "plt.rcParams['xtick.major.size'] = 3\n", "plt.rcParams['xtick.major.width'] = 1\n", "plt.rcParams['xtick.minor.size'] = 3\n", "plt.rcParams['xtick.minor.width'] = 1\n", "\n", "plt.rcParams['ytick.major.size'] = 0\n", "plt.rcParams['ytick.major.width'] = 0\n", "plt.rcParams['ytick.minor.size'] = 0\n", "plt.rcParams['ytick.minor.width'] = 0\n", "plt.rcParams['xtick.major.pad']=7.8\n", "plt.rcParams['ytick.major.pad']=7.8\n", "mpl.rcParams['figure.subplot.bottom']=0.25\n", "\n", "lns1=ax.plot(CTCT.index, CTCT['WeightstarPrice_exc300'].rolling(48*365,center=True).mean(), label='QWOP exc offers over $300/MWh',color=(ea_p['rd1']) )\n", "#lns2=ax.plot(MRPL.index, MRPL['WaterValue'].rolling(48*365,center=True).mean(), label='Mercurys water value',color=(ea_p['bl1']) )\n", "lns3=ax.plot(CTCT.index, CTCT['marginal_H20_value'].rolling(48*365,center=True).mean(), label='DOASA water value',color=(ea_p['bl2']) )\n", "\n", "\n", "ax.xaxis.tick_bottom()\n", "ax.set_frame_on(False)\n", "ax.axhline(y=0.1, lw=2, color='k') \n", "ax.grid(b=True, which='major', color='k', linestyle='-', axis='y',alpha=0.6, clip_on=True , marker=None )\n", "ax.grid(b=False, axis='x', which='both')\n", "ax.set_axisbelow(True)\n", "yearsFmt = mdates.DateFormatter('%Y')\n", "ax.xaxis.set_major_formatter(yearsFmt)\n", "def func(x, pos): # formatter function takes tick label and tick position\n", " s = '{:0,d}'.format(int(x))\n", " return s\n", "\n", "setp(ax.get_xticklabels(), rotation =0, fontsize=10)\n", "setp(ax.get_yticklabels(), fontsize=10)\n", "ax.set_ylabel(r\"$/MWh\", fontsize=10, family='arial', rotation=90 )\n", "ax.set_xlabel('Date', fontsize=10,family='arial').set_visible(False)\n", "lns = lns1+lns3\n", "labs = [l.get_label() for l in lns]\n", "ax.legend(lns, labs, loc=3, bbox_to_anchor=(-0.025, -0.33+0.05),fancybox=False, shadow=False, \n", " frameon=False ,ncol=3, fontsize=10).set_visible(False)\n", "plt.title('Clutha',x=0.5, y=1)\n", "\n", "#----------------------------------------------------------------------------------------------------------------------\n", "\n", "ax=fig.add_subplot(224)\n", "\n", "plt.rcParams['xtick.major.size'] = 3\n", "plt.rcParams['xtick.major.width'] = 1\n", "plt.rcParams['xtick.minor.size'] = 3\n", "plt.rcParams['xtick.minor.width'] = 1\n", "\n", "plt.rcParams['ytick.major.size'] = 0\n", "plt.rcParams['ytick.major.width'] = 0\n", "plt.rcParams['ytick.minor.size'] = 0\n", "plt.rcParams['ytick.minor.width'] = 0\n", "plt.rcParams['xtick.major.pad']=7.8\n", "plt.rcParams['ytick.major.pad']=7.8\n", "mpl.rcParams['figure.subplot.bottom']=0.25\n", "\n", "lns1=ax.plot(GENE.index, GENE['WeightstarPrice_exc300'].rolling(48*365,center=True,min_periods=48*200).mean(), label='QWOP exc offers over $300/MWh',color=(ea_p['rd1']) )\n", "lns2=ax.plot(GENE.index, GENE['WaterValue'].rolling(48*365,center=True).mean(), label='Generators water value',color=(ea_p['bl1']) )\n", "lns3=ax.plot(GENE.index, GENE['marginal_H20_value'].rolling(48*365,center=True).mean(), label='DOASA water value',color=(ea_p['bl2']) )\n", "\n", "ax.xaxis.tick_bottom()\n", "ax.set_frame_on(False)\n", "ax.axhline(y=0.1, lw=2, color='k') \n", "ax.grid(b=True, which='major', color='k', linestyle='-', axis='y',alpha=0.6, clip_on=True , marker=None )\n", "ax.grid(b=False, axis='x', which='both')\n", "ax.set_axisbelow(True)\n", "yearsFmt = mdates.DateFormatter('%Y')\n", "ax.xaxis.set_major_formatter(yearsFmt)\n", "def func(x, pos): # formatter function takes tick label and tick position\n", " s = '{:0,d}'.format(int(x))\n", " return s\n", "\n", "setp(ax.get_xticklabels(), rotation =0, fontsize=10)\n", "setp(ax.get_yticklabels(), fontsize=10)\n", "ax.set_ylabel(r\"$/MWh\", fontsize=10, family='arial', rotation=90 ).set_visible(False)\n", "ax.set_xlabel('Date', fontsize=10,family='arial').set_visible(False)\n", "#lns = lns1+lns2\n", "lns = lns1+lns2+lns3\n", "labs = [l.get_label() for l in lns]\n", "ax.legend(lns, labs, loc=3, bbox_to_anchor=(-1.2, -0.35),fancybox=False, shadow=False, \n", " frameon=False ,ncol=3, fontsize=10)\n", "plt.title('Tekapo',x=0.5, y=1)\n", "\n", "\n", "\n", "plt.savefig(path +'/pics/QWOPs_exc300_v_watervalues.png', dpi=500, format='png', bbox_inches='tight')" ] }, { "cell_type": "code", "execution_count": 30, "metadata": {}, "outputs": [ { "data": { "image/png": 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\n", "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "#do hydro ones as panels in the same chart\n", "\n", "fig = plt.figure(23,figsize=[cm2inch(25),cm2inch(25)])\n", "\n", "#----------------------------------------------------------------------------------------------------------------------\n", "\n", "ax=fig.add_subplot(221)\n", "\n", "plt.rcParams['xtick.major.size'] = 3\n", "plt.rcParams['xtick.major.width'] = 1\n", "plt.rcParams['xtick.minor.size'] = 3\n", "plt.rcParams['xtick.minor.width'] = 1\n", "\n", "plt.rcParams['ytick.major.size'] = 0\n", "plt.rcParams['ytick.major.width'] = 0\n", "plt.rcParams['ytick.minor.size'] = 0\n", "plt.rcParams['ytick.minor.width'] = 0\n", "plt.rcParams['xtick.major.pad']=7.8\n", "plt.rcParams['ytick.major.pad']=7.8\n", "mpl.rcParams['figure.subplot.bottom']=0.25\n", "\n", "lns4=ax.plot(MERI.index, MERI['WeightstarPrice'].rolling(48*365,center=True).mean(), label='QWOP',color=(ea_p['rd1']) )\n", "lns1=ax.plot(MERI.index, MERI['WeightstarPrice_exc300'].rolling(48*365,center=True).mean(), label='QWOP exc offers over $300/MWh',color=(ea_p['rd2']) )\n", "lns2=ax.plot(MERI.index, MERI['WaterValue'].rolling(48*365,center=True).mean(), label='Meridians water value',color=(ea_p['bl1']) )\n", "lns3=ax.plot(MERI.index, MERI['marginal_H20_value'].rolling(48*365,center=True).mean(), label='DOASA water value',color=(ea_p['bl2']) )\n", "\n", "ax.xaxis.tick_bottom()\n", "ax.set_frame_on(False)\n", "ax.axhline(y=0.1, lw=2, color='k') \n", "ax.grid(b=True, which='major', color='k', linestyle='-', axis='y',alpha=0.6, clip_on=True , marker=None )\n", "ax.grid(b=False, axis='x', which='both')\n", "ax.set_axisbelow(True)\n", "yearsFmt = mdates.DateFormatter('%Y')\n", "ax.xaxis.set_major_formatter(yearsFmt)\n", "def func(x, pos): # formatter function takes tick label and tick position\n", " s = '{:0,d}'.format(int(x))\n", " return s\n", "setp(ax.get_xticklabels(), rotation =0, fontsize=10)\n", "setp(ax.get_yticklabels(), fontsize=10 )\n", "ax.set_ylabel(r\"$/MWh\", fontsize=10, family='arial', rotation=90 )\n", "ax.set_xlabel('Date', fontsize=10,family='arial').set_visible(False)\n", "#lns = lns1+lns2\n", "lns = lns1+lns2+lns3+lns4\n", "labs = [l.get_label() for l in lns]\n", "ax.legend(lns, labs, loc=3, bbox_to_anchor=(-0.025, -0.33+0.15),fancybox=False, shadow=False, \n", " frameon=False ,ncol=3, fontsize=12).set_visible(False)\n", "plt.title('Waitaki',x=0.5, y=1)\n", "\n", "#----------------------------------------------------------------------------------------------------------------------\n", "\n", "ax=fig.add_subplot(222)\n", "\n", "plt.rcParams['xtick.major.size'] = 3\n", "plt.rcParams['xtick.major.width'] = 1\n", "plt.rcParams['xtick.minor.size'] = 3\n", "plt.rcParams['xtick.minor.width'] = 1\n", "\n", "plt.rcParams['ytick.major.size'] = 0\n", "plt.rcParams['ytick.major.width'] = 0\n", "plt.rcParams['ytick.minor.size'] = 0\n", "plt.rcParams['ytick.minor.width'] = 0\n", "plt.rcParams['xtick.major.pad']=7.8\n", "plt.rcParams['ytick.major.pad']=7.8\n", "mpl.rcParams['figure.subplot.bottom']=0.25\n", "\n", "lns4=ax.plot(MRPL.index, MRPL['WeightstarPrice'].rolling(48*365,center=True).mean(), label='QWOP',color=(ea_p['rd1']) )\n", "lns1=ax.plot(MRPL.index, MRPL['WeightstarPrice_exc300'].rolling(48*365,center=True).mean(), label='QWOP exc offers over $300/MWh',color=(ea_p['rd2']) )\n", "lns2=ax.plot(MRPL.index, MRPL['WaterValue'].rolling(48*365,center=True).mean(), label='Mercurys water value',color=(ea_p['bl1']) )\n", "lns3=ax.plot(MRPL.index, MRPL['marginal_H20_value'].rolling(48*365,center=True).mean(), label='DOASA water value',color=(ea_p['bl2']) )\n", "\n", "ax.xaxis.tick_bottom()\n", "ax.set_frame_on(False)\n", "ax.axhline(y=0.1, lw=2, color='k') \n", "ax.grid(b=True, which='major', color='k', linestyle='-', axis='y',alpha=0.6, clip_on=True , marker=None )\n", "ax.grid(b=False, axis='x', which='both')\n", "ax.set_axisbelow(True)\n", "yearsFmt = mdates.DateFormatter('%Y')\n", "ax.xaxis.set_major_formatter(yearsFmt)\n", "def func(x, pos): # formatter function takes tick label and tick position\n", " s = '{:0,d}'.format(int(x))\n", " return s\n", "\n", "setp(ax.get_xticklabels(), rotation =0, fontsize=10)\n", "setp(ax.get_yticklabels(), fontsize=10 )\n", "ax.set_ylabel(r\"$/MWh\", fontsize=10, family='arial', rotation=90 ).set_visible(False)\n", "ax.set_xlabel('Date', fontsize=10,family='arial').set_visible(False)\n", "lns = lns1+lns2+lns3+lns4\n", "labs = [l.get_label() for l in lns]\n", "ax.legend(lns, labs, loc=3, bbox_to_anchor=(-0.025, -0.33+0.15),fancybox=False, shadow=False, \n", " frameon=False ,ncol=3, fontsize=12).set_visible(False)\n", "plt.title('Waikato',x=0.5, y=1)\n", "\n", "#----------------------------------------------------------------------------------------------------------------------\n", "\n", "ax=fig.add_subplot(223)\n", "\n", "plt.rcParams['xtick.major.size'] = 3\n", "plt.rcParams['xtick.major.width'] = 1\n", "plt.rcParams['xtick.minor.size'] = 3\n", "plt.rcParams['xtick.minor.width'] = 1\n", "\n", "plt.rcParams['ytick.major.size'] = 0\n", "plt.rcParams['ytick.major.width'] = 0\n", "plt.rcParams['ytick.minor.size'] = 0\n", "plt.rcParams['ytick.minor.width'] = 0\n", "plt.rcParams['xtick.major.pad']=7.8\n", "plt.rcParams['ytick.major.pad']=7.8\n", "mpl.rcParams['figure.subplot.bottom']=0.25\n", "\n", "lns4=ax.plot(CTCT.index, CTCT['WeightstarPrice'].rolling(48*365,center=True).mean(), label='QWOP',color=(ea_p['rd1']))\n", "lns1=ax.plot(CTCT.index, CTCT['WeightstarPrice_exc300'].rolling(48*365,center=True).mean(), label='QWOP exc offers over $300/MWh',color=(ea_p['rd2']))\n", "#lns2=ax.plot(MRPL.index, MRPL['WaterValue'].rolling(48*365,center=True).mean(), label='Mercurys water value',color=(ea_p['bl1']) )\n", "lns3=ax.plot(CTCT.index, CTCT['marginal_H20_value'].rolling(48*365,center=True).mean(), label='DOASA water value',color=(ea_p['bl2']) )\n", "\n", "\n", "ax.xaxis.tick_bottom()\n", "ax.set_frame_on(False)\n", "ax.axhline(y=0.1, lw=2, color='k') \n", "ax.grid(b=True, which='major', color='k', linestyle='-', axis='y',alpha=0.6, clip_on=True , marker=None )\n", "ax.grid(b=False, axis='x', which='both')\n", "ax.set_axisbelow(True)\n", "yearsFmt = mdates.DateFormatter('%Y')\n", "ax.xaxis.set_major_formatter(yearsFmt)\n", "def func(x, pos): # formatter function takes tick label and tick position\n", " s = '{:0,d}'.format(int(x))\n", " return s\n", "\n", "setp(ax.get_xticklabels(), rotation =0, fontsize=10)\n", "setp(ax.get_yticklabels(), fontsize=10)\n", "ax.set_ylabel(r\"$/MWh\", fontsize=10, family='arial', rotation=90 )\n", "ax.set_xlabel('Date', fontsize=10,family='arial').set_visible(False)\n", "lns = lns1+lns3+lns4\n", "labs = [l.get_label() for l in lns]\n", "ax.legend(lns, labs, loc=3, bbox_to_anchor=(-0.025, -0.33+0.05),fancybox=False, shadow=False, \n", " frameon=False ,ncol=3, fontsize=10).set_visible(False)\n", "plt.title('Clutha',x=0.5, y=1)\n", "\n", "#----------------------------------------------------------------------------------------------------------------------\n", "\n", "ax=fig.add_subplot(224)\n", "\n", "plt.rcParams['xtick.major.size'] = 3\n", "plt.rcParams['xtick.major.width'] = 1\n", "plt.rcParams['xtick.minor.size'] = 3\n", "plt.rcParams['xtick.minor.width'] = 1\n", "\n", "plt.rcParams['ytick.major.size'] = 0\n", "plt.rcParams['ytick.major.width'] = 0\n", "plt.rcParams['ytick.minor.size'] = 0\n", "plt.rcParams['ytick.minor.width'] = 0\n", "plt.rcParams['xtick.major.pad']=7.8\n", "plt.rcParams['ytick.major.pad']=7.8\n", "mpl.rcParams['figure.subplot.bottom']=0.25\n", "\n", "\n", "lns4=ax.plot(GENE.index, GENE['WeightstarPrice'].rolling(48*365,center=True,min_periods=48*200).mean(), label='QWOP',color=(ea_p['rd1']))\n", "lns1=ax.plot(GENE.index, GENE['WeightstarPrice_exc300'].rolling(48*365,center=True,min_periods=48*200).mean(), label='QWOP exc offers over $300/MWh',color=(ea_p['rd2']) )\n", "lns2=ax.plot(GENE.index, GENE['WaterValue'].rolling(48*365,center=True).mean(), label='Generators water value',color=(ea_p['bl1']) )\n", "lns3=ax.plot(GENE.index, GENE['marginal_H20_value'].rolling(48*365,center=True).mean(), label='DOASA water value',color=(ea_p['bl2']) )\n", "\n", "ax.xaxis.tick_bottom()\n", "ax.set_frame_on(False)\n", "ax.axhline(y=0.1, lw=2, color='k') \n", "ax.grid(b=True, which='major', color='k', linestyle='-', axis='y',alpha=0.6, clip_on=True , marker=None )\n", "ax.grid(b=False, axis='x', which='both')\n", "ax.set_axisbelow(True)\n", "yearsFmt = mdates.DateFormatter('%Y')\n", "ax.xaxis.set_major_formatter(yearsFmt)\n", "def func(x, pos): # formatter function takes tick label and tick position\n", " s = '{:0,d}'.format(int(x))\n", " return s\n", "\n", "setp(ax.get_xticklabels(), rotation =0, fontsize=10)\n", "setp(ax.get_yticklabels(), fontsize=10)\n", "ax.set_ylabel(r\"$/MWh\", fontsize=10, family='arial', rotation=90 ).set_visible(False)\n", "ax.set_xlabel('Date', fontsize=10,family='arial').set_visible(False)\n", "#lns = lns1+lns2\n", "lns = lns1+lns2+lns3+lns4\n", "labs = [l.get_label() for l in lns]\n", "ax.legend(lns, labs, loc=3, bbox_to_anchor=(-1.2, -0.35),fancybox=False, shadow=False, \n", " frameon=False ,ncol=3, fontsize=10)\n", "plt.title('Tekapo',x=0.5, y=1)\n", "\n", "\n", "\n", "plt.savefig(path +'/pics/QWOPs_both_v_watervalues.png', dpi=500, format='png', bbox_inches='tight')" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [] } ], "metadata": { "kernelspec": { "display_name": "Python 3", "language": "python", "name": "python3" }, "language_info": { "codemirror_mode": { "name": "ipython", "version": 3 }, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", "version": "3.5.2" } }, "nbformat": 4, "nbformat_minor": 2 }