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   "source": [
    "## Sample for optimizing a portfolio that supplies a load minimum share of green energy\n",
    "In this sample, we define a more realistic example from the power sector: We define a complex sales contract, with an hourly load profile and the obligation to provide at least 80% of the power from green sources. In the portfolio we link it to a wind and a PV PPA along with a battery that allows us to flatten out green production to be abme to meet the target share of green energy."
   ],
   "cell_type": "markdown",
   "metadata": {}
  },
  {
   "source": [
    "## Some prerequisites\n",
    "### Basic definitions"
   ],
   "cell_type": "markdown",
   "metadata": {}
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import pandas as pd\n",
    "import datetime as dt\n",
    "import os, sys\n",
    "from IPython.display import display, HTML\n",
    "# in case eao is not installed, set path\n",
    "myDir = os.path.join(os.getcwd(), '../..')\n",
    "sys.path.append(myDir)\n",
    "addDir = os.path.join(os.getcwd(), '../../../..')\n",
    "sys.path.append(addDir)\n",
    "import eaopack as eao"
   ]
  },
  {
   "source": [
    "### Timegrid\n",
    "The timegrid defines start and end of the optimization, including discretization and conversion unit from flow (i.e. capacity, here MW) and volume (here MWh)"
   ],
   "cell_type": "markdown",
   "metadata": {}
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "Start = dt.date(2021,1,1)\n",
    "End   = dt.date(2021,1,10)\n",
    "timegrid = eao.assets.Timegrid(Start, End, freq = 'h', main_time_unit = 'h')"
   ]
  },
  {
   "source": [
    "## Define the portfolio"
   ],
   "cell_type": "markdown",
   "metadata": {}
  },
  {
   "source": [
    "### The nodes as the starting point\n",
    "A node reflects a virtual trading point that all assets are connected to. In case of a setup with transport limitations, several nodes may be used. A node always comes with a commodity that is traded at it. Here it's power. Note that commodity and unit serve for documentation only\n",
    "\n",
    "In order to clearly separate \"green power\" from \"grey power\" we define two nodes"
   ],
   "cell_type": "markdown",
   "metadata": {}
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "green_sources = eao.assets.Node('green sources', commodity= 'power')\n",
    "grey_sources  = eao.assets.Node('grey sources', commodity= 'power')"
   ]
  },
  {
   "source": [
    "### The downstream contract\n",
    "Assume we have a contract, where we are obliged to \n",
    "(1) deliver a given load profile\n",
    "(2) ensure that a fraction (e.g. 80%) of the overall energy comes from green sources (our PPAs). The rest may be provided from the market\n",
    "We assume we have an obligation to deliver at a fixed price.\n",
    "\n",
    "This is a rather complex asset and we make use of the StructuredAsset. This could be done in a simpler way, but allows us to encapsulate everything in one asset."
   ],
   "cell_type": "markdown",
   "metadata": {}
  },
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   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "min_fraction_green = 0.8\n",
    "sales_fix_price    = 130"
   ]
  },
  {
   "source": [
    "#### Starting with the load\n",
    "The asset is located in it's own node to ensure delivery is channeled separate from green and grey sources\n",
    "Attention: As the consumer draws power, the load must have negative sign in the contract"
   ],
   "cell_type": "markdown",
   "metadata": {}
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "node_load = eao.assets.Node('node load', commodity= 'power')\n",
    "load_profile = {'start' : timegrid.timepoints.to_list(),\\\n",
    "                'values':  - 5*abs(np.sin(np.pi/22 * timegrid.timepoints.hour.values)     \\\n",
    "                              + np.sin(0.1 + np.pi/10 * timegrid.timepoints.hour.values)\\\n",
    "                              + np.sin(0.2 + np.pi/3 * timegrid.timepoints.hour.values) )}\n",
    "load         = eao.assets.Contract(name = 'load', min_cap= load_profile, max_cap=load_profile, extra_costs=-sales_fix_price ,nodes = node_load)\n",
    "volume_sold  = -load_profile['values'].sum()\n",
    "max_load     = -load_profile['values'].min()"
   ]
  },
  {
   "source": [
    "#### Green restriction\n",
    "To link green and grey sources to their delivery counterparts, we define transport assets. The green link implements a \"minimum take\", i.e. a minimum volume over the optimization time"
   ],
   "cell_type": "markdown",
   "metadata": {}
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "min_green = {'start':Start, 'end':End, 'values' : volume_sold * min_fraction_green }\n",
    "link_green = eao.assets.ExtendedTransport(name = 'green link', min_take = min_green,  min_cap = 0, max_cap = max_load, nodes = [green_sources, node_load])\n",
    "link_grey  = eao.assets.Transport(name = 'grey link',   min_cap = 0, max_cap = 20, nodes = [grey_sources, node_load])"
   ]
  },
  {
   "source": [
    "#### Create contract object\n",
    "To wrap things up, we pack all assets together in a portfolio that defines our downstream contract. This in turn is used to define the new structured asset that connects to the outside world via the sourcing nodes"
   ],
   "cell_type": "markdown",
   "metadata": {}
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "downstream_portfolio = eao.portfolio.Portfolio([load, link_green, link_grey])\n",
    "downstream_contract  = eao.portfolio.StructuredAsset(name = 'downstream', nodes = [green_sources, grey_sources], portfolio = downstream_portfolio)"
   ]
  },
  {
   "source": [
    "How does it look like? The network graph explains:"
   ],
   "cell_type": "markdown",
   "metadata": {}
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
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     },
     "metadata": {}
    }
   ],
   "source": [
    "#eao.network_graphs.create_graph(portf = downstream_portfolio, file_name='test.eps', title = 'Downstream contract structure')\n",
    "eao.network_graphs.create_graph(portf = downstream_portfolio,title = 'Downstream contract structure')"
   ]
  },
  {
   "source": [
    "### Green energy supply PPAs: PV and wind with a given generation profile\n",
    "We are using a \"contract\" as the asset type. This gives us the opportunity to define a detailed minimum and maximum capacity that reflects available generation according to how wind blows and sun shines. We assume those assets are PPAs. Note that the minimum capacity is the same as max. We assume we have the obligation to take off all production at the fix price. They are attached to the \"green node\""
   ],
   "cell_type": "markdown",
   "metadata": {}
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [],
   "source": [
    "PPA_fix_price = 75. # unit: €/MWh\n",
    "PV_gen = {'start': timegrid.timepoints.to_list(),\n",
    "          'values':5*np.maximum(0,-np.cos(2*np.pi/24 * timegrid.timepoints.hour.values))}\n",
    "PV         = eao.assets.Contract(name = 'PV', min_cap= PV_gen, max_cap= PV_gen, extra_costs = PPA_fix_price ,nodes = green_sources)\n",
    "wind_gen = {'start': timegrid.timepoints.to_list(),\\\n",
    "            'values': 5.*np.random.rand(timegrid.T)}\n",
    "wind        = eao.assets.Contract(name = 'wind', min_cap= wind_gen, max_cap= wind_gen, extra_costs = PPA_fix_price, nodes = green_sources)\n"
   ]
  },
  {
   "source": [
    "### Add storage to be able to maximize green supply\n",
    "Green sources are not always available. The storage enables us to flatten green production to match the load\n",
    "The storage is placed at the node \"green_sources\" so that we ensure there is no mixture of green and grey power. A storage comes with a defined capacity in and out (MW) and storage volume (MWh). Furthermore we define efficiency, costs, etc\n",
    "\n",
    "Note that in order to take out computational complexity we define a daily block size. This has the effect that the battery is optimized per day only, going back to start/end fill level each day."
   ],
   "cell_type": "markdown",
   "metadata": {}
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [],
   "source": [
    "storage = eao.assets.Storage(name = 'battery', nodes = green_sources, cap_in= 1*max_load, cap_out=1*max_load, size = 4*max_load, cost_in=0.5,cost_out=0.5, eff_in=0.9, block_size='d', start_level = 2*max_load, end_level = 2*max_load)"
   ]
  },
  {
   "source": [
    "### The market\n",
    "We may buy and sell energy from/to the spot market at given spot prices. The market is modeled in a simplistic way here, assuming high market depth. If required, more complexity may be added. Note it's attached to the \"grey node\". We also add an external market for surplus green power (sales only)"
   ],
   "cell_type": "markdown",
   "metadata": {}
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [],
   "source": [
    "prices = {'spot market': 50+12.*(np.sin(np.linspace(0.,100., timegrid.T)))}\n",
    "prices['green market'] = prices['spot market'] + 20.\n",
    "spot_market = eao.assets.SimpleContract(name = 'spot market', price = 'spot market',  min_cap = -100, max_cap = 100, nodes= grey_sources)\n",
    "green_sales = eao.assets.SimpleContract(name = 'green sales', price = 'green market', min_cap = -100, max_cap = 0,   nodes= green_sources)"
   ]
  },
  {
   "source": [
    "### Putting everything together\n",
    "Add all assets to the portfolio and optimize\n",
    "\n",
    "(1) As a portfolio with separate assets. This is the complete structure"
   ],
   "cell_type": "markdown",
   "metadata": {}
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "output_type": "display_data",
     "data": {
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     },
     "metadata": {}
    }
   ],
   "source": [
    "portfolio_separate = eao.portfolio.Portfolio([ load,link_grey,link_green,   spot_market,  wind, PV,green_sales, storage])\n",
    "op_separate = portfolio_separate.setup_optim_problem(prices = prices, timegrid=timegrid)\n",
    "res_separate = op_separate.optimize()\n",
    "eao.network_graphs.create_graph(portf = portfolio_separate,title = 'Complete portfolio with separate assets')\n",
    "#eao.network_graphs.create_graph(portf = portfolio_separate,title = '', file_name = 'full_portfolio.pdf')"
   ]
  },
  {
   "source": [
    "(2) With the structured downstream contract as a structured asset, hiding some internal mechanics"
   ],
   "cell_type": "markdown",
   "metadata": {}
  },
  {
   "source": [
    "## Optimize"
   ],
   "cell_type": "markdown",
   "metadata": {}
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "output_type": "display_data",
     "data": {
      "text/plain": "<Figure size 432x288 with 1 Axes>",
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jjls0dOjQdaWP8+GHH3adNWtW/9TU1OIRI0asF5GTROQqIBWYH0K4vExcE4CLol9/BiwDnkHfNAtCCFc20FOSUKI68yzgX/GOpamJnrt9ge+hPWqSo10F3vungWedc8vjFR9Y0m2pRgMzQwh3icgDMduzgRPRJPcGcDxaBTVNRF4Frv3JT37yHHDo5MmTBw4dOnTdjh07Wp100klfFBcXJz3//PP7xybdRYsWdTvnnHM+zM7Ozg8hZOfl5RUDJ4UQikTkcREZUHqsiGQBZwLfQSfn/jvwZ2B6CGGiiJQOFGgJjkT/Bh/FO5CmxHufhjbunow+f9+wuwosFRgHjPfePwn8Pl4lX0u6LVMfoHS1gY9jts8LIRSLSDYwGHgt2p6N9sEd/MADD/RNS0trn5eXlxRCID09fWeHDh12AhQUFKTGPshxxx3339dff31ASUlJ0oknnvjN5s2b04F/iUgHtGdD95jD+wIHsmdr/QzgOyIyBZgGPFbnO28axgDrrBGt+qKqhLvRPuNriBb2jFGI9qpJAsYDGd772+LxHFvSbZmWon1pXwKGAu9H20vrcdcDC4BRURJORUsMCy677LIpKSkpOUVFRWujwmeFL9qsrKy8cePGzf/iiy86vvPOOwNWr159CDA1hPCwiPxDRCQ7O7tdfn5+xy1btiwF3g8hfA8geszkEMKvo98/puUk3aOBT+IdRBMzDhgBrKriuBJgNdrHfA7wSgPH9S3We6FlmgqMEJFXgK5oKWCXqBHtXuB1EXkT+H3ptjvvvHPCpEmTBj3zzDP7V/Ug06ZNG/jAAw8c9eqrrx44cODAT4cNG/ZVp06dJu27774FAwYMGHPhhRe+fMoppzw7dOjQSydOnLgeeFFE3ooe85fA4SLyjoi8x+5Sd0uwL9Y/91sq6ukSlXIvAjZs27Yt5YMPPuhauu/tt9/uWc6lArAduDiqA25UVtJtgUIIBSIyJqpbfQBYEkJYBlwQc8xLaEmYstu8979DS2Ncfvnlu9boysnJmRV7/OjRo0tHonVHv/q9MmLEiM3Aw2gjHgB9+vT5wDkXnHMPoY15sY6uy702Nd77ZLRO+6l4x9KEHIWOiszNy8tL/+yzz7odeuihawAWLFjQ85hjjllRzjlbgH5oNdrCKnrs1CubT7eFikq5bYAvQwgXVXV8LO99N+BRdJHEjVUc3g14F7jGOVcUnd8H/Wq3V2k46CCLt4C7nHPTaxJPc+K9PwX4t3MutcqDWxgRGQlcgxYW09AqhSnt27ffJysrq9P48ePffeGFFwYtWrRonw4dOmzt06fP2g8++GBAp06dNp922mmffPPNN+mzZ8/uX1JSIsccc8wXQ4cOTfntb3/bNi8v7w104c9hwIlRldrTwGUhhHqfQN6qF1qoEMKoEMKImiZcAOfcauBSdMhvVzT5ltUh2vcOcENpwo3OXwoMR/vv7oyOvRGdUet17/127/0L3vsRNY2tGTgTrXM05WsdQjgV+BtwCXDGz3/+88mdOnXKW7hwYdaRRx65vEePHutycnJmjRo1anHHjh235OTkzOrRo8fW9957r9+ll14669JLL505a9asfkBScXFxe+D2EMLVwOvAcSLSDkhtiIQLVr1gask5t9R7fx5wOvADtHdDCVpqTUYbgh4D3o5NuDHnL/HeDweOcM5tAX4P/D7q9nMF+oZ623u/He2+drtzbk7D31ncHcnuniUm4r0fdf7550+aO3fuBu/92MGDB3+1aNGik0Tkofvuu+9gEenUvn37dV26dNle3vlbtmxptWnTprYPPvjgEQD5+flpIYTi5OTkTSGEr6PDpgA3AHsDzzbUvVjSNbXmnNsMTIn6PQ5CVzooBlZHc8JWdf4SYEmZbQXAPcA93vt0dJDED4HZ3vttwKtoAp5brzeTOPoBj8Q7iAS0PSUlpWtBQcE+wBNDhgxJ7dq1a8mOHTvWjxo16syXXnrp2RACycnJoaSk5FuNY+3atdvZsWPHLRMmTJidnJxMUVGRiEiXwsLCbaXHhBCWiEh3dMj6+Ia6EavTNU2C9z4Trc+7EO3TuwXt7nObc25BPGOrL9GHTB7QParCadGideJ+AJwGHLR06dJOM2fOpKSkhKKionD88cff8dBDD50GrOrfv/+wvn37bh4+fPjiv//978NTU1OLxo4dO3/q1Kn7FxcXJ5900kmfrVu3LmP27Nn9ADp37rxz7Nixr0ycOHFACGFXY62I/ASt1z27oe7Lkq5pcrz3bYFfoL0teqNDmacBtzrnmuwkMd77c4FHnXNp8Y4lHrz3w9C/6fFot7kMdMKkRWiXwe+hA3tWASc65/4bc+5YtF1gNZX0HY8kowN+rnbOvRW7Q0QuB9aFEBqs94hVL5gmxzm3Ffg18GvvfXu0T+94YJH3fgPwb7QE/GUcw6yN04CvqzyqGYi6xp0FjEXrsXuiyXAtMBd4EJjinNsUc04hcAwwJnZ75FngIPQ5XMPugT5lpaDtD48Ab8fuiBLu2dE1GoyVdE2z4b3vhCbg89CeEOvRVXVvdc4ti2NolfLefx+tMrkMmOuca7CvtvES/W12VRWwe2n5r9AuhU8B0+oyH0I0SOIKtCsZ6PSjpfM9p6N9eUuAvwKPxGuYtSVd0yxF9YE3oZOBd0dLUFPREnB5neXjxns/Ce2tkYw2RC4Hhjvn1sc1sDrw3h+A1r8fDwwEMtGqgs/RrlmPOuc+baDH7gZ8Fy1Fd4o2r0EX+HzJObehIR63uizpmmYvehPehL4Ju6JvwGfQBBz3Bivv/Vlo97q2aL/l94DjEmX+16pEVQWnox9wRwH7oB8g69GqgheAf8Qj2UWT7odEmjzIkq5pUbz3PdEEfDbamLIK/Wp7p3OuJhOz184UaQUcgY5+GgZ0KgrJKQu2HDBqVUE3WVvQdUNBSdqgnBseWFf5heLHe98ROB8tTQ5DqwqK0aqCmejz+WJT+dBobJZ0TYvlve8N/Apt0MlCG7GeRBPwN/X6YFMkDW3s+wH6VTsJnXRlJ8Dy/J7HpVCUkpW2/pO0pMJV6BwU/2J8+NbAksbmvd8PrSo4Ea0qaIPG/gVaVfC4c25e/CJsWizpGgN47/ujCfgMtB7wK+AJdC6ITXW6+BTZF7gT/dpduljnHpbk9RmZKkXbeqav+ABt9OmArpF2E+NDo610EH0dPxUdIDAiijkVrSr4GHgRrSpI2JJ4orOka0wZ3vtBaAI+DU1+y9Ahor+JuqtV3xQZhq6AEahkcqA1BV0GdUzduDwtaWd+zOYsNEH/mPHh8xo9bjVFXe5iqwqy0aqCFcAs4GngOasqqD+WdI2pRNQKfxNwCtrlaAk6w9rvnHPljvPfZYr0iY4tQlvua6N9dP54xoc1tbzGLtEHSmlVwSC08S4PrSp4A60qaK5DrBOCJV1jqikaMXUTcBKarL5E5wa+zzmXHw3j/QS43A2Y+Hq0ry+6VldddAY+AK5gfPXfsNEE3aOAc9Gqgt7sriqYh86X/I9GaUA0u1jSNaYWvPeHoQn4BLRh7HN0juBzgJIzu0z97bB2H3+X+pumsSvwC//fiW8DE4E3nXNvlImpLdpYdyZwMNAFHQywAu2G9jQw1Tm3x0ohpnFZ0jWmjqJ5f3+JNkAlQ+C8bk+EvVt/Pb9NSl59DcToUFiSsvyOxb/aGx0K+xQ6FPpCtOQ9GK3+yAP+C0xHqwo+qKfHN/XEkq4x9SCaBW0jkJrVai1nZU9le3EmmSl5X3dLW70gWUrq1BC1o7hVxsbCvb7zz9XjZEtR++SYXd+g8+9OQ5Ns3Ad7mMrZhDfG1FAF62l1REdfrdgvc2Fhx9RNh2ck528pJjk1BElCqFXSLQkiq3bsPWx7cUb3zOTtdEr9hi1F7UEb13pNnDhxTWOt7WXqh5V0jSlDRNLQr++t0GkjX0a/rj+ElixfQudyuA4tuNwSQnhZRM4AruvdmT6/OY9t5xzBl0OuY8T+Pdj84VL2mjiWRRccza7+rZPeoOt9L9E/PY3iq05h8XlHsu6MuxmWu4XWXdqx44VfMPe+aexdRFq7n52asubmJwv269ZzwJpP8g7Neu+997JWrVo1a9u2bbeiDWQXoet85aDLIE1GG/sWhRAuj+aJ/UF0zDUhhI8a/Ik05bI10oz5ttHAzBDCKezZtzYb7QnwMHAtOpnLSOAXIpJUuu2T3/DcPS/SFWBzHq1+O54vpl3PnAffpFfsgzzzPt2euooPP7qdWRcczdr/fZOu+3Zj67w7mTmwO1v/9gbdBJCSgm1tUrZvCCVF29oVLpr52GOPfX/x4sVvXHvttUcDH6JzHowIIRyH1uf+Ergz+n2riByJjro7LtpmXcLiyJKuMd/Wh93rlH0cs31eCKEYHbQwGJ1Y+1V0xePOpdsOvYmz1m+lVUmAjpns7JXFzgFd2bE1nz1W+L3le/z3pv9jwBl3c9DHy8j87xoyD+vLZoDh/dj03zVkSMzCMyFACDpBd3Fx8XvOuZIo1o+iuIiqGgYDd4nIdLR3RXfAAQ+IyCT0w8PEiSVdY75tKXBA9PPQmO2ldafrgQXACSGEkcCBwLrSbYvu4Z5Fd7MoSQDZvYpB2Yq8wd3Je+5q5uecyPI7nqNvvy5sn7OE9gDvLaZD/y7kdcigaNVG0gAWraTN+q27uqCVxrIEGBaVtIn+/xy4OoQwMoRwKPAc8HEI4WK0muTiWj8zps6sIc2Yb5sKPCUir6Ajyfbo1xpCKBGRe4HXRSQAC0MIPyndlp1Dh5OH0u3xyyvvo3vlowycu4yOeTtJvvNcFp4+jA1n3M2wA2/gqM5t2XH3eL78Jr91hz+/VjTk2NvolpYaktelHjTk7LP3Gbp48eJe3vubQwjrRORpYKaIlNbp3gFMEpH2aHL+ETBRRPoAaehCnyZOrCHNmHKISEoIoUhEHgAeDSHMqvbJUyQbXTJoPRUvG1MtO0tS01bv6H7wzpKUTq2TC3h85Q9Kdoa0JHRCnt6JNE+sqR6rXjCmfC+KyLtARo0SLsD4sBZdf2uvHcVpGat2dNs/v7h1m9oE0SqpsKBXxvJZnVutX/Xf7QNKEy7ocN7x0VBf04RYSdeYeuS9/zlwbJdWq4ee2eX53tuKMiU1qWhTr/TlM5Ok1v1pU0Og/aQVP/5sTUG3c9CE+x46GXoR2qXthqa8EnJLYiVdY+rXOODM3J3d+szbcqC0TdlW0it92bt1SLgAWSLcv6ag2yVoffN/nHPHAK3RZceHoishr/SqRS7h3lRYSdeYeuS9vwL4I0CKFOZN6Png7C5pa9uh67LVRjfgHeDa0lUkvPfJZee3jZYhuh1dhigDeB/wzrlptXxc00As6RpTD6LS5fPo5DPT0UlpPv9F398ckZGc/zvgELRhrbozfKUBewEzgBsZH7612kQlsZyOToZzKLqszlS0+mFlda9hGo4lXWPqyHt/PJrYitDJzt8H7gcecc69xxRJQadcvAxdJXcj0dpo5UhDV6soBH4HTGV87aomog+CG4EJ6ACJJcCfgD/ZShDxY0nXmFqKeg48ii538yxwTqXJbIrsjQ4xPgdNroL2lQ/oEjkBLZk+ATwf9YKor1gHoeu0nRI95lvAzc65mfX1GKZ6LOkaUwvRMj6voSvjnuec+3e1T9aS7z5AP3R2shK09LsYWMH40GCl0OiDYjw6P8OQ6HGnAL92zlW4hpupP5Z0jakh7/1v0MltZgKnVLlWWoKKFqW8BS2p7wUsBO4GHrVBFw3Hkq4x1RT1EHgTLaX+xDn3YJxDqjfe++HAbeisacXoRD43OOc+jWdczZElXWOqwXt/FXAPOpnM8c11MUfvfRLwE+BKtPojF52b93bnXH5l55rqsaRrTCWir+CvoQs9eufcLXEOqdF477uhk+eMQeuuPwJudc49H9fAmjhLusZUwHt/LvAI2r/2eOfcF3EOKW689yejc/Iega4+8Rxwo3NueVwDa4Is6RpThvc+FR3oMAqYBFxmDUsq6vt7HXAp0ANYjvZJvtf6/laPJV1jYnjvj0UTbglwqnNudpxDSlje+/5o39/T0fXk3kH7/r4d18ASnCVdY9jVf/Uh4EI06Y61klv1RVUxN6CT72wGngRucs59E9fAEpAlXdPiee+HAK8D7dCBDtZQVEve+7bARHTl4Sy0t8e9wP/GVtF4748EPnDOVTgXRfRBeCC6AGhnoCC63qtNOZlb0jUtmvf+TrSOchYwqqkOdEhE3vtD0JnPjkeHOL+GzgWxOvpXOnT6W3NLeO9PAH4K7B1tKkSHTaeiVT+vAX9wztXbUOnGYknXtEje+73RgQ69gZ865ybFN6LmKyqx5gBXAQPQ+SVao5P+PEaZhkrv/Q/RhLsFXaOurGS0FL0BuNQ591VDxl/fLOmaFsd7/1PgPuBLYGRzHeiQiLz32egcE6XLF5UA/3LOnRvtPw0dGZeLztpWmb3QuSPGOee2NkzE9c9WAzYtRlTf+Bo6z+xtzjkX55Baoq5owt2M9nhIB87x3g8ATkBLwxuIEu7TTz89ZPTo0Z8mJyeXd60N0fVOE5FTgYkhhGUNfQN1ZUnXtAje+7HA4+gbdYitJxY3S4CxaEl2Fbqixk50kvf90bmEd33zGDt2bFVzP2xBe5ysa4BYG4RVL5hmLRroMBU4Ffhf4Mc20CHxiMjdF1xwQcedO3ce+dprr/W48sor3/rHP/5x0Nq1aztceeWVM6ZNmzZg69atrbds2ZLRrl27vHHjxs3Pzc1Nf+qppw5p27ZtWLVq1ecFBQXjrKRrTBx5748BSue5/Y5z7p14xmMqNXP58uW/KCgoyMjIyNiRl5eXnJeXl5aenr5rmaLOnTtvHTdu3PxJkyYN37ZtW8qMGTP6n3TSSZ/2798/+a677uoSz+BrwpKuaXai1vLJwMXAC8DZNtAh4b27cuXK36akpKQPGTJk5bx587pmZGQUbN26Nb30gC5dumwFyMzMLMjLy0vdvHlzRq9evbYkJyd3bN269ZeFhdVdfi6+bAl206x47/dD6wrHAd9zzp1pCTfxhRDWbt68mZSUlOR+/fptmDNnTr8ePXpsiD1GRPY4p127dnlfffVVu5KSkuS8vLxejRpwHVjSNc2G9/42YAGwDMh2zj0T34hMTezYsePT7Ozs/Ozs7PwdO3a06tOnT6XLBx177LGL//Of/wydPHlyt+Li4q8bK866soY00+RF875OB/oCVzrnHohvRKY2omqhf6IrF2+q5mndgF86515rqLjqm5V0TZPmvb8M+AodZrqPJdymK+pVchva1pRRjVO6Au8BMxoyrvpmJV3TJEUDHf4DHAbc6Zz7VZxDMvXEe38E8Ds0+e4aKBGjDTo50fvAtc658oYKJyxLuqbJ8d6PAf6BfgU9wTm3ML4Rmfrmve+NrlJ8OjrXQhL6bSagk+U8ArzonNsZrxhry5KuaTKigQ7PoG/Eh4AJNtChefPet0NHq7VDZxr7GljQlP/ulnRNk+C9HwG8GP36XVudwDRVNjjCJLSoRftB4BJgGjC6somvjUl0lnRNwvLeDwLeADoC33fOPR3nkIypM+syZhKS994DnwIr0IEOlnBNs2AlXRN33vsDgA7Oube9913RFR36Az9zzv05vtEZU7+sIc3Elfc+CfgMXQvrFrRz/FLgOOfcynjGZkxDsJKuaRBR9662QDGwrZJJZ85Hh32mA3ehAx1ubJwojWl8lnRNvYl6GuwPnAuchK7eCpDnvf8/4LnY0qv3vjXwZyAz2rQD7fhuTLNlSdfUC+99JnAncAS62OA3aCkXdC2si4GLvfeT0LluBa27Le30noSu/Nq/UQM3ppFZ0jV1FpVY/wQcgK55VdZOdN2rZOAydDKTDdH/NwDPA0ucczsaJWBj4siSrqkPPwaGUnXVQDGafC8ErnDOHdjQgRmTaKyfrgFARC4WkYtrel5UrfB9YH15+xcuXNgpNzc3dpq+YqAA+EFt4jSmqbOka+rqOCANrZf9liVLlnRat25d2blRN5aUlBzqve/Z4NEZk2Csn24LJiKtgKfQpLkReAU4GDgI2IJ257oAWA58AcwGOgEeXfDx8n79+g3avn37fj179lx9+umnf/Hcc88NWrlyZaekpKSSsWPHfvzwww8f1apVq8KePXuuz87O3rJ48eLswsLClJNPPjn3lVde+WjlypW90Ya3S4CVwMtAKrAOOAfoCfwdLUkPAG4FctD64FEhhO0N/kQZU4+spNuyjQbmhBBOAbYCnYHMEMJ30GVTcoCZwAjgKHTS6P3QpDwXoG/fvrk5OTnzly5dmg2watWqvXJyct7NycmZlZWVlT948OAVJ5xwwsIxY8YsBEhLSyuaMGHCnKSkJNm5c2eXEMJI4Cdog1oRcEb0+IuA46M4OwLnAXcDF4UQTgZeAkY15JNjTEOwpNuy9SVKnsCHaO+Cj6LfP0C7b81HeyUcDtwLHAMkhRAKAbp3774USE5JSSkGOPLII7+cMmXKsKeffnpIQUFBctkH7Nat2yaA3NzctE2bNu0vItOBB9CuY5nAZBGZAXwPHTQBsDCEUIKu8vtJtG0VmoyNaVIs6bZsS4HSHgTD0K/5h0S/HwosDiEUR9s7oIs//hBdcReATZs2zUWTNQCDBw9ef8EFF8zNyMgomDdvXpfk5OSSkpKSXWtnR8toJ2VnZxckJSW9EkIYGZV2L0RLrl+EEI4Fnmb34IrYOrDYn/dck9uYJsC6jLVsU4F/icgraJ3uWqCXiLyNVjeMj46bC3QIIRSISBFa5QDA22+//f6wYcPyiT7AH3300cMKCwuTAY444ogP165dm//GG28MXrFiRYf27dvnR6ft1bNnz1cKCgo2RiXdADyBVhncJCKHApuB/zbo3RsTB9aQZuokmmPhYrSvbnWG8KaijXE/cs593HCRGZOYrKRrasR7nwzsg/YkuAoYjq7IOwQ4Gh2RVtEneSsgC7jPEq5pqayka6olSrbzgX3RYb3paJ1qjnPub977VsAvgTOiUzahgyAE7d7VBu2dcLdz7tnGjd6YxGFJ11Sb9/5JYAz6DSkAzzrnxpY5pidwFnA22vhWjPa/nQK84pzb0pgxG5NoLOmaavHet0d7LxwUbcoH9nXOfV3JOQLQlJfLNqa+WdI1VfLefx94DB0Vdh3wD+Be59w1cQ3MmCbIGtJMhaKeCVOBU4FJwGXOueC93wC8G8/YjGmqrKRryuW9PxqdXwHgdOecJVlj6oGVdM0eonrYB9EJaF4Exjjnyp1BzBhTc5Z0zS7e+33RJXT2Ar7vnHs6ziEZ0+zY3AsGAO/9r9GZvVYCXS3hGtMwrKTbwnnvO6Ol20HANc6538c3ImOaNyvptmDe+9KJw9OBPpZwjWl4VtJtgbz36cA0dG7c31t/W2MajyXdFsZ7fwrwL3RE2aHOublVnGKMqUeWdFuIqCvYFOBcdF2082x4rjGNz5JuC+C9PxD4D7oczunOuWlxDsmYFssa0po57/3d6Lpni4AsS7jGxJeVdJupaIrFN9EJxy91zk2Oc0jGGKyk2yx5769AF50sAHpYwjUmcVhJtxnx3rcFXkNX8r3VOTcxvhEZY8qypNtMeO/HoPPcbgSGOOc+i3NIxphyWNJt4qK1y55F1yb7O7rKrnUFMyZBWdJtwrz3R6HTLyYBxzrn3o5zSMaYKljSbYKigQ4PAJcCLwNn2Zy3xjQNlnSbGO99f7QrWGdgnHPuyTiHZIypAesy1oR4728EPgNygS6WcI1peqyk2wR47zuhpdv9gOudc7+Lc0jGmFqykm6C895fBKwC2gD9LOEa07RZSbc+TZEkdGDC4cAhQHcgGdgCfAK8D7zF+LC5qkt579OAl4DjgD86565qoKiNMY3IlmCvD1NEgNOBy4AsQIA8dBhuQD/cMqP/i9BuXn9hfNgAu3oj7O2c+zr6/US07+1O4GTn3IeNej/GmAZjSbeupkhnwKOl2y3A9irOSEYT83bAMT685b0/Bx1NdghwHTAeeBqd87a4oUI3xjQ+S7p1MUW6Aw+iSXRtDc/OANrvLEn9zZ2Lb/oj0BUoRkvH5zrnXqjXWI0xCcEa0mprimQCfwE6UvOEC1r98E1BSdrv9mm9LCvaJsDDlnCNab4s6dbeFcDewDe1vUBBSavk9QVZPUd2mp7SOim/AE3EP/Let6uvII0xicWSbm1MkYHAGGpXwgWgKCSnrMjvOaKIlMIOqRtzx3R9+jngRHTQw5b6CtUYk1isTrc2psivgO9Sh6QbAuSXpLfLSM7fgvZqaA+MYnzYWk9RGmMSkJV0a2qKtAJOow7VCgAiECVc0G5kKcAxdYzOGJPgLOlWQEQqem76oM9bfXflKikuYZiISD1f1xiTQFps0hWRNBF5XkReFpF/isjFItJbRN4UkX8BF4vIGSLylojMFJFTRGT4wTdyOyBfb6DVyFs5NPaaEx5k0AHXM+LgGznyy1zSFq0k/eCbOPKA6xlx9eP0Azjjbg6au4wMgGE3ciTAZX9n39H3ss/hN3MFkC0i/ysiM0RkWhTrcBGZLiLvisgPo22PRMe8WckHhDEmwbTkYcCjgZkhhLtE5IGY7dlog1YA3gCORz+cpoUQTti7owwsCRT8fQZdRx/K6tgLfrCEvT6+k3eTk6AkwHl/Yn93Np+fdSgbDr+Z4V/m8nVFwfTNZtvUq/lSzucoYG0IYUJMMr0FOBPYCvxHRKYAPUIIx4qIBKuYN6bJaMklpD7A/Ojnj2O2zwshFKMDHgajCz2+CnQTEenXhYWvLiDzlXl0vfhY1sRe8Oen8uUZ9zBs/P0M2ZJP8vL1ZB67H5sB9u/B5kUryRBhV4IMgV1VCcP7sRWtstgXmKn7Q0m0+0DgeXSmsa5RbI+IyOPAbVbSNabpaMlv1qXAAdHPQ2O2lya69cAC4IQQwkjgwBBC+N7hPHvvi2S3aU1hh4w963XHHMb6adcxt3NbCh57hy77dCJv+kLaA3zyNe0HdSe/bTpFX62ndV4BSSs2kFl6bkoyqcAK4HPgCNijXnkucHoUxzBgDfBECOECdDLzw+rpOTHGNLCWXL0wFXhKRF4BtgF7LHcTQigRkXuB10UkAAuBn1x5Cm9OepO0q05hcdkLnnAHh+0oJBngqlP48IT92Hj+XzjoV0+RdOL+5A7oyo4JI/n6R//LgYO6s2WvTHaUnpucRBrwAVqi/a6IvBXFdRrggOejJLwB+J/o99IZzBbU83NjjGkgLbqfroikhBCKojrdR0MIs6o8aYrI8JtZM+NmFrVuRX32qc0GLmV8mFeP1zTGJJiWXL0A8KKIvAtkVCvhAnI+L7TPZFrrVmQUlSSn5hZkD9xY2GHvOsbRFljJ7jpmY0wz1aJLujXlvT8TOL+VFOx3bvd/DhZKkotCalGv9OXTWyUV7qjyAuUTtHHsesaH1+svWmNMImrpJd2aOgwYuzOk7f/G+hOS05J20rP1VzPrkHBBqxWmo93TjDHNnCXdmvlX6Q8rC3oULsnrO7N18s426MTktdEZrVa4nfH2lcOYlsCSbjV5728DPkLrXfOBwrc2HHs2Ool5Z7RetrqS0SqF5Wjj2cZ6DtcYk6CsTrcK3vtu6KCEfsCVzrkHvPcXA+nOOR3JNkUOB24F9kKX4amoV0NqdEwAHgceZHyoS9WEMaaJsaRbCe99DvAnYAkw0jm3usKDp0gGOmT4IqA3OnNYabVD6YCLQrR/8NOMD8saImZjTGKzpFsO730m8ApwJPAb59yNNbrAFNkLGIA2kiWhgxyWACsYH4rqN1pjTFNiSbcM7/13gSfRkV4nOOc+jXNIxphmpCUPA96D9z4Z+D/gbLS+9SLnnH0iGWPqlSVdwHt/KFqd0Ao40TlnfWaNMQ2ixXcZ897/AZiDdgfLsoRrjGlILbak673vjY4E6wZc6Jx7PK4BGWNahBZZ0vXeXwt8CWwGulvCNcY0lhZV0vXedwReRyctv9k5d2ecQzLGtDAtJul6788DHgbWAgOdc9+ahNwYYxpas0+63vtU4N/AycADwE+tK5gxJl6addL13h+LLn9TDBzlnJsd55CMMS1cs0y63nsBJgMXo0l3rHOuuNKTjDGmETS7pOu93w9tLOsAjHHOTY1rQMYYE6NZdRnz3t+Croy7HMi2hGuMSTRNtqTrvU9xzhVFP3dB57wdAPzMOffnuAZnjDEVaJKzjEVzJfwHOBSdw/Z+YBlwnHNuZRxDM8aYSjW5pBs1kr2HJtw8IB24xzl3fVwDM8aYakiI6gXvfRvgOGAg0BpYB7wDLCynT+2pwAHo0uUZwAOWcI0xTUVcS7re+w5ADnAm+gEQ0KVtUqP/lwL3O+feio5PRudLyIyOLYiO3ds5l9vY8RtjTE3FLelGjV9/A3qgJdvylrFpB7QB/gA8gTaWHQF8DLwBLIr+vWejzIwxTUFckq73Ph14FE2466s4PAVda2wimoSfLO21YIwxTU2j9tMVkUuiH09EV8ytKuGCloA3AldSQcIVkXeq8dgjRaRv9aM1xpj619iDIy6Jeh9cBGyvwXn5QHt0dd49iEh172EkYEnXGBNXNa5eEJGjgPvQpPk4Wrf6ELp6bhdgXAhhqYhcjzaQFaBzIJwC3J2amrrooosuyujRo8dygHfeeafH0qVLOxcUFKQmJSWFvn37rl20aNHeHTp02DZu3Lj5y5Ytazdt2rT9QwitunfvPm/u3LlHi8jFaC+GNsBNwJ9DCEeLyB+Bmegw4MlAW7TO9yrgC7QR7rUQwjW1fcKMMaYualPSPQ24PoRwPJpsAboCY4GfAdeLSFfg+BDCCODXwA0hhEnAgptuuumKHj16bIu9YHp6+s4JEybMycjIKCgqKkq67LLLZm7dujV969atqd26dduWk5Mz8/LLL39/9erVA0QkPTptUwjh9BDCxwAi8gdgVgjhn8AvgTtDCMcBW4FD0Ll0r7GEa4yJp9r00/0L8CsR+R/gT+ik4AtCCEUi8jHQH62vnR8d/wHgYs4vKXvB7OzsrQBt2rTZ0aVLl60AmZmZBdu3b0/dtGlT2ssvvzykuLg4ddOmTa3RRjWAD2MusS+wAy3RAgwG7hKRgJaG59TiPo0xpt7VpqS7MYRwOXA94KNt+4tIMnAgsBgdkntgtO/QaBto39q1VJLsRWTXzyEEZs+e3XvEiBFf5uTkfJ6RkbEeHRQBeybvL9AuZXdHv38OXB1CGBlCOBR4DigEkmt+u8YYU39qU9L9sYiMQUuQv4m2rQWmAp2B80MIa0TkTRGZCexEG84AVkycOPH3l1xyycp99tknC9hU1YMNHDgw99VXX93/o48+KszPz19S0XEhhMkickNUl3wHMElE2qPJ+Ufoyr93iMjwEMIttbhvY4ypszr30xWR3sBtIYQLqnuO9/4ENGGvruYpbdG62TNtEIQxpimL13y6bwHvow1wVWmNzrFwqyVcY0xTF89hwG2Be4GD0WqGvDKHJAF7oXW4v3LOvdaoARpjTAOI94Q3acDZwA/Q+uAkNMkWo41ubwIPO+c+i1uQxhhTjxJiPl3vfRJa4u2Jzhq2DZjjnKvOMGFjjGkyEiLpGmNMS9GsFqY0xphEZ0nXGGMakSVdY4xpRJZ0jTGmEVnSNcaYRmRJ1xhjGpElXWOMaUSWdI0xphFZ0jXGmEZkSdcYYxqRJV1jjGlElnSNMaYRWdI1xphGZEnXGGMakSVdY4xpRJZ0jTGmEVnSNcaYRvT/kZBatNESsHIAAAAASUVORK5CYII=\n"
     },
     "metadata": {}
    }
   ],
   "source": [
    "portfolio_struct = eao.portfolio.Portfolio([downstream_contract, wind, PV, spot_market, green_sales, storage])\n",
    "op_struct = portfolio_struct.setup_optim_problem(prices = prices, timegrid=timegrid)\n",
    "res_struct = op_struct.optimize()\n",
    "eao.network_graphs.create_graph(portf = portfolio_struct,title = 'Complete portfolio with downstream contract')"
   ]
  },
  {
   "source": [
    "## Interpret the results"
   ],
   "cell_type": "markdown",
   "metadata": {}
  },
  {
   "source": [
    "output = eao.io.extract_output(portfolio_struct, op_struct, res_struct , prices)"
   ],
   "cell_type": "code",
   "metadata": {},
   "execution_count": 14,
   "outputs": []
  },
  {
   "source": [
    "The overall portfolio value is the following (plus an indication that the optimization was successful). In case we want to evaluate how much the promise of 80% renewable energy costs, we can easily recalculate the portcolio, changing this parameter"
   ],
   "cell_type": "markdown",
   "metadata": {}
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "output_type": "stream",
     "name": "stdout",
     "text": [
      "                 Values\nParameter              \nstatus       successful\nvalue      57820.038998\n"
     ]
    }
   ],
   "source": [
    "print(output['summary'])"
   ]
  },
  {
   "source": [
    "### Detailed results\n",
    "Plotting and saving results to file for further inspection "
   ],
   "cell_type": "markdown",
   "metadata": {}
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "output_type": "display_data",
     "data": {
      "text/plain": "                     downstream (green sources)  downstream (grey sources)  \\\n2021-01-01 06:00:00                        -9.3                       -0.0   \n2021-01-01 07:00:00                        -9.8                       -2.9   \n2021-01-01 08:00:00                        -2.7                       -8.1   \n2021-01-01 09:00:00                        -4.9                       -0.0   \n2021-01-01 10:00:00                        -0.0                       -0.3   \n2021-01-01 11:00:00                        -0.8                       -0.0   \n2021-01-01 12:00:00                        -2.6                       -0.0   \n2021-01-01 13:00:00                        -5.2                       -0.0   \n2021-01-01 14:00:00                        -3.4                       -0.0   \n2021-01-01 15:00:00                        -1.8                       -0.0   \n2021-01-01 16:00:00                        -5.5                       -0.0   \n2021-01-01 17:00:00                        -4.2                       -0.0   \n\n                     wind (green sources)  PV (green sources)  \\\n2021-01-01 06:00:00                   4.7                 0.0   \n2021-01-01 07:00:00                   2.5                 1.3   \n2021-01-01 08:00:00                   0.2                 2.5   \n2021-01-01 09:00:00                   1.5                 3.5   \n2021-01-01 10:00:00                   3.6                 4.3   \n2021-01-01 11:00:00                   4.6                 4.8   \n2021-01-01 12:00:00                   0.9                 5.0   \n2021-01-01 13:00:00                   4.4                 4.8   \n2021-01-01 14:00:00                   1.5                 4.3   \n2021-01-01 15:00:00                   3.4                 3.5   \n2021-01-01 16:00:00                   0.2                 2.5   \n2021-01-01 17:00:00                   1.7                 1.3   \n\n                     spot market (grey sources)  green sales (green sources)  \\\n2021-01-01 06:00:00                         0.0                         -0.0   \n2021-01-01 07:00:00                         2.9                         -0.0   \n2021-01-01 08:00:00                         8.1                         -0.0   \n2021-01-01 09:00:00                         0.0                         -0.0   \n2021-01-01 10:00:00                         0.3                         -0.0   \n2021-01-01 11:00:00                         0.0                         -0.0   \n2021-01-01 12:00:00                         0.0                         -0.0   \n2021-01-01 13:00:00                         0.0                         -0.0   \n2021-01-01 14:00:00                         0.0                         -0.0   \n2021-01-01 15:00:00                         0.0                         -0.0   \n2021-01-01 16:00:00                         0.0                         -0.0   \n2021-01-01 17:00:00                         0.0                         -0.0   \n\n                     battery (green sources)  \n2021-01-01 06:00:00                      4.6  \n2021-01-01 07:00:00                      6.0  \n2021-01-01 08:00:00                      0.0  \n2021-01-01 09:00:00                     -0.2  \n2021-01-01 10:00:00                     -7.9  \n2021-01-01 11:00:00                     -8.7  \n2021-01-01 12:00:00                     -3.3  \n2021-01-01 13:00:00                     -4.1  \n2021-01-01 14:00:00                     -2.4  \n2021-01-01 15:00:00                     -5.2  \n2021-01-01 16:00:00                      2.8  \n2021-01-01 17:00:00                      1.2  ",
      "text/html": "<div>\n<style scoped>\n    .dataframe tbody tr th:only-of-type {\n        vertical-align: middle;\n    }\n\n    .dataframe tbody tr th {\n        vertical-align: top;\n    }\n\n    .dataframe thead th {\n        text-align: right;\n    }\n</style>\n<table border=\"1\" class=\"dataframe\">\n  <thead>\n    <tr style=\"text-align: right;\">\n      <th></th>\n      <th>downstream (green sources)</th>\n      <th>downstream (grey sources)</th>\n      <th>wind (green sources)</th>\n      <th>PV (green sources)</th>\n      <th>spot market (grey sources)</th>\n      <th>green sales (green sources)</th>\n      <th>battery (green sources)</th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th>2021-01-01 06:00:00</th>\n      <td>-9.3</td>\n      <td>-0.0</td>\n      <td>4.7</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>-0.0</td>\n      <td>4.6</td>\n    </tr>\n    <tr>\n      <th>2021-01-01 07:00:00</th>\n      <td>-9.8</td>\n      <td>-2.9</td>\n      <td>2.5</td>\n      <td>1.3</td>\n      <td>2.9</td>\n      <td>-0.0</td>\n      <td>6.0</td>\n    </tr>\n    <tr>\n      <th>2021-01-01 08:00:00</th>\n      <td>-2.7</td>\n      <td>-8.1</td>\n      <td>0.2</td>\n      <td>2.5</td>\n      <td>8.1</td>\n      <td>-0.0</td>\n      <td>0.0</td>\n    </tr>\n    <tr>\n      <th>2021-01-01 09:00:00</th>\n      <td>-4.9</td>\n      <td>-0.0</td>\n      <td>1.5</td>\n      <td>3.5</td>\n      <td>0.0</td>\n      <td>-0.0</td>\n      <td>-0.2</td>\n    </tr>\n    <tr>\n      <th>2021-01-01 10:00:00</th>\n      <td>-0.0</td>\n      <td>-0.3</td>\n      <td>3.6</td>\n      <td>4.3</td>\n      <td>0.3</td>\n      <td>-0.0</td>\n      <td>-7.9</td>\n    </tr>\n    <tr>\n      <th>2021-01-01 11:00:00</th>\n      <td>-0.8</td>\n      <td>-0.0</td>\n      <td>4.6</td>\n      <td>4.8</td>\n      <td>0.0</td>\n      <td>-0.0</td>\n      <td>-8.7</td>\n    </tr>\n    <tr>\n      <th>2021-01-01 12:00:00</th>\n      <td>-2.6</td>\n      <td>-0.0</td>\n      <td>0.9</td>\n      <td>5.0</td>\n      <td>0.0</td>\n      <td>-0.0</td>\n      <td>-3.3</td>\n    </tr>\n    <tr>\n      <th>2021-01-01 13:00:00</th>\n      <td>-5.2</td>\n      <td>-0.0</td>\n      <td>4.4</td>\n      <td>4.8</td>\n      <td>0.0</td>\n      <td>-0.0</td>\n      <td>-4.1</td>\n    </tr>\n    <tr>\n      <th>2021-01-01 14:00:00</th>\n      <td>-3.4</td>\n      <td>-0.0</td>\n      <td>1.5</td>\n      <td>4.3</td>\n      <td>0.0</td>\n      <td>-0.0</td>\n      <td>-2.4</td>\n    </tr>\n    <tr>\n      <th>2021-01-01 15:00:00</th>\n      <td>-1.8</td>\n      <td>-0.0</td>\n      <td>3.4</td>\n      <td>3.5</td>\n      <td>0.0</td>\n      <td>-0.0</td>\n      <td>-5.2</td>\n    </tr>\n    <tr>\n      <th>2021-01-01 16:00:00</th>\n      <td>-5.5</td>\n      <td>-0.0</td>\n      <td>0.2</td>\n      <td>2.5</td>\n      <td>0.0</td>\n      <td>-0.0</td>\n      <td>2.8</td>\n    </tr>\n    <tr>\n      <th>2021-01-01 17:00:00</th>\n      <td>-4.2</td>\n      <td>-0.0</td>\n      <td>1.7</td>\n      <td>1.3</td>\n      <td>0.0</td>\n      <td>-0.0</td>\n      <td>1.2</td>\n    </tr>\n  </tbody>\n</table>\n</div>"
     },
     "metadata": {}
    }
   ],
   "source": [
    "eao.io.output_to_file(output,  os.path.join(os.getcwd(), 'results.xlsx'))\n",
    "display(output['dispatch'][6:18].round(1))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "output_type": "display_data",
     "data": {
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\n"
     },
     "metadata": {
      "needs_background": "light"
     }
    }
   ],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "%matplotlib inline\n",
    "# take out complexity of the chart\n",
    "output['dispatch']['downstream'] = output['dispatch']['downstream (green sources)'] +  output['dispatch']['downstream (grey sources)']\n",
    "output['dispatch'].drop(['downstream (green sources)', 'downstream (grey sources)'], axis=1, inplace = True)\n",
    "ax = output['dispatch'].plot(kind='line')\n",
    "plt.axis('off')\n",
    "plt.show()\n"
   ]
  }
 ]
}