From c7fd066152adf1753587ef88fd4e88dc111a9f57 Mon Sep 17 00:00:00 2001
From: Fabian Neumann <fabian.neumann@outlook.de>
Date: Tue, 9 Jan 2024 07:59:57 +0100
Subject: [PATCH] update workshop CEM in PyPSA

---
 .../10-workshop-pypsa-cem.ipynb               | 1248 +++++++++++++++--
 1 file changed, 1099 insertions(+), 149 deletions(-)

diff --git a/data-science-for-esm/10-workshop-pypsa-cem.ipynb b/data-science-for-esm/10-workshop-pypsa-cem.ipynb
index a8f96585..c63e5aa9 100644
--- a/data-science-for-esm/10-workshop-pypsa-cem.ipynb
+++ b/data-science-for-esm/10-workshop-pypsa-cem.ipynb
@@ -99,7 +99,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 1,
    "metadata": {
     "jp-MarkdownHeadingCollapsed": true,
     "tags": []
@@ -131,7 +131,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 2,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -142,7 +142,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 3,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -181,7 +181,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 4,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -191,9 +191,20 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
+   "execution_count": 5,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "0.09439292574325567"
+      ]
+     },
+     "execution_count": 5,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
    "source": [
     "annuity(0.07, 20)"
    ]
@@ -207,7 +218,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 6,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -223,7 +234,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 7,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -232,7 +243,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 8,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -255,7 +266,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 9,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -267,9 +278,78 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
+   "execution_count": 10,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "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>load</th>\n",
+       "      <th>onwind</th>\n",
+       "      <th>offwind</th>\n",
+       "      <th>solar</th>\n",
+       "      <th>prices</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>2015-01-01 00:00:00</th>\n",
+       "      <td>41.151</td>\n",
+       "      <td>0.1566</td>\n",
+       "      <td>0.7030</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2015-01-01 01:00:00</th>\n",
+       "      <td>40.135</td>\n",
+       "      <td>0.1659</td>\n",
+       "      <td>0.6875</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2015-01-01 02:00:00</th>\n",
+       "      <td>39.106</td>\n",
+       "      <td>0.1746</td>\n",
+       "      <td>0.6535</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "                       load  onwind  offwind  solar  prices\n",
+       "2015-01-01 00:00:00  41.151  0.1566   0.7030    0.0     NaN\n",
+       "2015-01-01 01:00:00  40.135  0.1659   0.6875    0.0     NaN\n",
+       "2015-01-01 02:00:00  39.106  0.1746   0.6535    0.0     NaN"
+      ]
+     },
+     "execution_count": 10,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
    "source": [
     "ts.head(3)"
    ]
@@ -283,7 +363,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 11,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -299,7 +379,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 12,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -348,7 +428,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 13,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -364,7 +444,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 14,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -380,7 +460,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 15,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -389,9 +469,31 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
+   "execution_count": 16,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "DatetimeIndex(['2015-01-01 00:00:00', '2015-01-01 04:00:00',\n",
+       "               '2015-01-01 08:00:00', '2015-01-01 12:00:00',\n",
+       "               '2015-01-01 16:00:00', '2015-01-01 20:00:00',\n",
+       "               '2015-01-02 00:00:00', '2015-01-02 04:00:00',\n",
+       "               '2015-01-02 08:00:00', '2015-01-02 12:00:00',\n",
+       "               ...\n",
+       "               '2015-12-30 08:00:00', '2015-12-30 12:00:00',\n",
+       "               '2015-12-30 16:00:00', '2015-12-30 20:00:00',\n",
+       "               '2015-12-31 00:00:00', '2015-12-31 04:00:00',\n",
+       "               '2015-12-31 08:00:00', '2015-12-31 12:00:00',\n",
+       "               '2015-12-31 16:00:00', '2015-12-31 20:00:00'],\n",
+       "              dtype='datetime64[ns]', name='snapshot', length=2190, freq='4H')"
+      ]
+     },
+     "execution_count": 16,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
    "source": [
     "n.snapshots"
    ]
@@ -405,16 +507,84 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
+   "execution_count": 17,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "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>objective</th>\n",
+       "      <th>stores</th>\n",
+       "      <th>generators</th>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>snapshot</th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>2015-01-01 00:00:00</th>\n",
+       "      <td>1.0</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>1.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2015-01-01 04:00:00</th>\n",
+       "      <td>1.0</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>1.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2015-01-01 08:00:00</th>\n",
+       "      <td>1.0</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>1.0</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "                     objective  stores  generators\n",
+       "snapshot                                          \n",
+       "2015-01-01 00:00:00        1.0     1.0         1.0\n",
+       "2015-01-01 04:00:00        1.0     1.0         1.0\n",
+       "2015-01-01 08:00:00        1.0     1.0         1.0"
+      ]
+     },
+     "execution_count": 17,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
    "source": [
     "n.snapshot_weightings.head(3)"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 18,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -423,9 +593,77 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
+   "execution_count": 19,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "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>objective</th>\n",
+       "      <th>stores</th>\n",
+       "      <th>generators</th>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>snapshot</th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>2015-01-01 00:00:00</th>\n",
+       "      <td>4.0</td>\n",
+       "      <td>4.0</td>\n",
+       "      <td>4.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2015-01-01 04:00:00</th>\n",
+       "      <td>4.0</td>\n",
+       "      <td>4.0</td>\n",
+       "      <td>4.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2015-01-01 08:00:00</th>\n",
+       "      <td>4.0</td>\n",
+       "      <td>4.0</td>\n",
+       "      <td>4.0</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "                     objective  stores  generators\n",
+       "snapshot                                          \n",
+       "2015-01-01 00:00:00        4.0     4.0         4.0\n",
+       "2015-01-01 04:00:00        4.0     4.0         4.0\n",
+       "2015-01-01 08:00:00        4.0     4.0         4.0"
+      ]
+     },
+     "execution_count": 19,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
    "source": [
     "n.snapshot_weightings.head(3)"
    ]
@@ -446,9 +684,22 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
+   "execution_count": 20,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "Index(['onwind', 'offwind', 'solar', 'OCGT', 'hydrogen storage underground',\n",
+       "       'battery storage'],\n",
+       "      dtype='object')"
+      ]
+     },
+     "execution_count": 20,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
    "source": [
     "carriers = [\n",
     "    \"onwind\",\n",
@@ -476,7 +727,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 21,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -497,9 +748,30 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
+   "execution_count": 22,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<Axes: xlabel='snapshot', ylabel='MW'>"
+      ]
+     },
+     "execution_count": 22,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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czo5NcXFxyM3NRWVlJdRqNWJiYtjdfIODg6FSqSzu2YKCAlRUVMDDwwMtWrRASkoKe896enqy19W8v7nuWUfGiICAAHbcbtq0Kaqqqth71ry/fXx8EBwcbHHP1tbWorCwEHq9Hk2aNHFqjNh42YDDucYXwLTCarzx12WMucsf9/gZ80bsjRFc96z1GGHqMx//QKQU6+GjK4GfSmYxRuTkCU/s14tL7B7XM0BhkTgF12rr7BcIvX69kP9YpQ5H0nLQKlBld4wwv2etxwjTPSmEjHEkaaKBGTRoEFQqFbZu3QoAOHjwIHr27Ilr164hIiKClZs8eTKysrKwfft2rF+/Hk899ZSFFwMABgwYgLi4OHz11VdYtGgR1qxZY7MNd8uWLfH0009j9uzZePbZZ5GZmYm//vrLQkalUuG7777DE088YaNvfX099u3bh+bNm0Muv+mcUqvVKKhhMOnHFJvvjGoXih/s7GS545mOAIwJVvZkUvIr8eJv/DHRHc90xE8HzuLrFH53pFwGPNE+DOtP5Vl8/sekDuxafFIeXHXKwpPSu7k/Xu8bayGTnJzMJpw98M1J6Bmgmb8GKx5t49C5xOJYVhnm/nXJ4rMezfywYEDzRtGHD/N+kxpS1U2qepmg+jmHK3rxjammMddVTLp9cSgbW84VQC4D1o1ORJDWg5X5+Ww+lh+xX2Tt4btCsPkc97JlEx0ivXHqWoVL+naN8sXFwioUVfHPEY+2DeUN/QDA/4a3QhurdAZH0Ov1OH36NHr16gWlkt9vIpnQT2ZmJnbt2oVnnnmG/Sw8PBwAbDwa+fn57BtzeHg46urq2DchPhmTFWdOQUGBhYz1eYqLi6HT6Ww8Ldb4+PjA19eX/U+tVvMmTcllwgaAkO14raxWcOkZCQYGkHHo8+j3ZzDvr0ucevxx/jpm/HYBuy4WWbj9rO2avZdLeM+bVVLDloDOLBEuONQQGBjGxkgBYD+RjXJLUVytw8XrVQ4lsFPEx8AwKKy8c7b22HLDyDAwwOj1SXjk+zNIv7Hahy8sbk5BpfBK0+si9KdKKbdrpJDg6Auts0jGUFm9ejVCQ0MxZMgQ9rPY2FiEh4ezK4EAYx7Lvn370KNHDwBA586d4eHhYSGTk5ODpKQkVqZ79+4oLS3F0aNHWZkjR46gtLTUQiYpKYl17QHAjh07oFar0blzZ4d/D98NSXJhy2vtJ8pO/zWVdx8HE5cKq+DlFyh4Li5tqnQGHMkq49wU69P9WUjOr8QH+zIx6/eLbIyTK1HXeoIIDgvHsoNZePonS0/TLjsrlxoKvvHiv+xyi91KpYB53pTUkKpugaHhePrHFEzdkoq9bt6XhASp9psJMfV79fc0jN6Q5HB9Jy649MoqqcE3R68izc6y3lyelYjWkORcMAyDAxkl2J9eYjHGRUZGskaKOeW1eszbcYm4fXslK0yQmAdCU40Y9vsdZagYDAasXr0aEyZMsHD/yGQyzJgxA4sWLcLmzZuRlJSEiRMnQqvVYsyYMQAAPz8/PP3005g5cyZ2796NkydP4sknn0Tbtm3ZVUBt2rTB4MGDMXnyZBw+fBiHDx/G5MmTMXToUMTHxwMABg4ciISEBIwbNw4nT57E7t27MWvWLEyePNmpFT98hoqHQvjCFvEk0pooq9WjUGDzwTl/XkJFjWs1YKwte+u/z+VVIu268U1BweGZmfBDMt7adZl9mH9MKuRcAv3BvkyU1rg3m9/eW/abO4RrELgT67Am4Ngy94aESzcpcCCjlE08f2+P9HbclWq/mRBLv4LKOnYfMtPKRVfg0uuVPy5i05l8TNmSyvGNGzK/28/pA4AvDmXj4e/OYOdF/rwMADh+tRwLd6Xjrd3p+PFsPvssVtfU4ItD3CXx8yt0qK03EHlUbiXuKENl165duHLlCiZNmmRz7NVXX8WMGTMwZcoUdOnSBVevXsWOHTssMqw/+eQTjBgxAqNGjULPnj2h1WqxdetWKBQKVmbdunVo27YtBg4ciIEDB6Jdu3b4/vvv2eMKhQK///47NBoNevbsiVGjRmHEiBH46KOPnPpNvIaKwIW9UlyDSgGPCiBsLZfU1KOsXDiGaa8dc8+OTm/Ay1ttd9n86Wwebzu55XXYn1HKPry/XuTXZznPnhcNhb15/lqZtCYRU9KmiQ/2ZmDMhnM4k+NajFoMrHWTCtVVln1jvdrOGbiMw8JKHb45ds3hMuNS7TcTYuknVJjMUbj0IglfWC9qMIdhGHx3PAdbzhWgpt6AD/ddwZErpZyyBobB69tvhoxXHr2GrTc8RXkF9vvso32Zoq2S4QrZ28gISpB5j6SAJAyVgQMHgmEYtOIoYiGTybBgwQLk5OSgpqYG+/btQ2JiooWMRqPB0qVLUVhYiKqqKmzduhVRUVEWMoGBgVi7di27hHjt2rXw9/e3kImOjsa2bdtQVVWFwsJCLF26FGq12qnfxGeocIVIzHnlj4tEtU1I7neie8zODf/z2Xw2tJOSX8n5sO+9XIKT18rt/q5fk6/joh23LADsSitmKzLqDQwW/Z2OV36/KFpse9fFIiz5JxN55cbfII3Hz3EuF1ZjV1oxCqt0mPU7//bstzNcy+qtKauzPD5jqzHxvKCyDquOXcPc7Zfw8T9X7IYLzPlsfxZGb0iyKJCYVVKD0RuSsOl0Hl77Iw3VOuEXjDuJjOJqVBH0SVlNPbs60VX4Nvmzx7HsMqw9aZmfOG/HZXzIYVhwhXaWHTSeU2hM3pdeYrf0vQkZUWDHPgSOeyKEtHWXHSMJQ+V2pJ5nLbzQzVxcXU908UnW/5uSke1ip52c8jr8nWaM79tb27/xVJ5gkvAf54Xj05duTBrbUq5j7+USnM6pwLfHyZav2aO8th4f7MvEXxeK8MaNWHFDPV/XK+ugEzkht3Xr1uy/K0Qa0MXCXDd3UFZTj+c3n8fULam8e1OdyanAlgzLfiqv1aPewGDar6nYeDoPx7LLsP1CIaZsSRU0hvMr6rDt/HUUVdVjjtnbtMn4MZFbzv3WzmVUubvfTKTkVyKZI/fMRE29ASuOXMWp2gCX3qZ3XizEsz+fx3O/nLcrl11agzEbkvDE+iSiJFKhftucVICTVx3zbvF5JndeLLIZt0zbk3DRvEVLwXOJFfkRskOCvVREXhchhG6Bzw+5Hs4jgRoqDQSfR4Xk4SfJ1yC54Quu21/iBghP2OtPGd807KldUq2DQuBOIslSNyWR/Wf21vrXhSI8/N0ZjNt4zundpivMQlimbc0bwqX5T3oxxm44h+d+EbcQkqlGBACbfq6s0zfqpmHmurmDFUev4nJRDdIKq7HqGPfeVJ/uv8L5eWZxNWeYYPsFW5d9fkUdfj1XgKySGjy/mXuytU56r+IwIj87kIVR65JsQgnu7jcASLtehRd/u4AZWy/wPktfHsrGj2fz8e3xXLsr94T4cB/3NbDmswNZqNMzqK034COC75D02y9J+Q493yo7g9cJB4yeS+kZgjLuyegAGDCC5yLpIiGRk9cqcLW0FgzD4FxuhUXhTzGhhkoDwZe5TfKuzbVxlU07BHeZrl747VuoGdNyXcbOLVulMwh6VISqLQI3q+1au4Er6/TIq6jDi79dQFWdHtmlNXjjr0v44bTtknMuuHRzxE5hGAbpRdU4cqUUGcX81+ad3RlgAGSX1uKYmbHlKuYbY1onr41ad9bpCpG19QaUu7hjdkNs2mmPjOKbuSZ8zwlfX2iU3MMd15v8W7vS8fmhbDz9U4rgKjwTlVZhjpJqHbalXEdpTT3mWSVoO9pvf10oxDdHr7oUXjKv38GV2PrT2Xz8mXrTaPs7TfzVeOYGBMMwFrVATl4rx6HMmwZdeW09Tlwtg97AoK7euIEeSb8dySrD27sziMNJ9hY4mN9jRQILGGoEiqeRQuQIEUGGZMQgGSc/P5SFvZeL8dK2i3jmpxTRwnjmUEOlgeCbAEguvKeH8GUhmZc8POzv40BCbb3wifQGRtBQIVqWpzOgsFKHJDuu6SslNZi7/RKOZpVh5bFrbM4JF2U19Xj1j4tYsMtykpi7/ZJDoZ8VR6/huV/OY96Oy3ju5/OcO0Rbx67FqHNjwsvrZkEla0NFp2eQWVyDfQ4uwa2s02P8pnN4Yl0SLhSQ5WlwodRosfRAFlYevUpcjvxCQRVe2noBmwgNTROpBZVINdOV73x8+48o5dzP1R/nC212KLe3gy3A7ZGzfjmxd8ubX1MhcspqseSfK9h0Jh9LXVg5Y37vXCqsxlu7Llvk6HxtVYjsSFaZqPcxALy/9+YKrJ85ComZdv1lGAYvb72I2X9ewty/LmH0hiQ881MKlBot0Xn2Z5QQrzLysONRyTEbX17fzr9y6GppLVQaT8FziRCNIYJhhG0ZIkOFQKqsRs+urKupN9jdKNdZqKHSQPC9hZEM5mqhOArIQhdab+G9J4RaYT0qdgTrDYzgKiSSJLI6PYNFezLsyugMjMXgkVfBv0Lni0PZOHWtApcKLd+8j2WX2UxM9jCvzMgA7L5J7GcMY7Ms8bMDWQ4N8noDg0/+vYJ3d6fbvJGYFxzkS1ouM7vfsktrBN/+fj9/HcXV9dAZGLzwa6rTobCD1xXYmnIdP5zJx/ZU/lUPlwqrcP2G52Lmtgs4l1eJb45d49Tzp7P5ePG3VPx5/rpFCHWW1RJTPkOAz5Vvb9B9fnOqQ14pLlHrLrS+VBcKqljDWqiIpDlpZvfvrjTna8JYG7n7M0rtLukFgHUn7W8fwsXBzBLeY3su3dT/66Pc+WdncspRVqtni0GeuFqO8lo9sktr8cLfxcTP7p5LxTAwDOb8aX9psoow8/RyEf/KsRlbL8A/MIioHSHc5FAhgiw8ZCnUECuWqaHSQPDlqBCt1iFon6Qd034uds8lcCfW1htQU2/AhlP8b796RtijQlI/QM8wOJtrf8mtdZLyrN/TkFNWi0uFVRYTTbVOj78v8Q/qrqSofHcily0KZ2AYvLzNdvVNea0e63kGea4Jcc+lYvyZWoh96SX4ymrlgikuzzAMUni8TfU3DMozORWY9GMKxm86h6TcCvxwJo8zbmytw7f/ced7AMCv5wowd/sltrqmObvNak78k17C+f0jV0rx/OZUjNlwDuM2nkOt2TW0ruBcrdPj6yNXkZJfhU/2Z2Gu2VusteHHZ/TzDZRCt+CqY+SJ21whmJ/OWuZGWJ/uhV9T8fRPySiu1jmUo+LvKc6WbHyeA3vP3EYOr5dQ+GnBznS7x/UGBldL+Sf9Wb+n2V218vzmVOKw79GsMhwXyDOxl6NiQmicLK2pR8YV9ySWAoTeEiH3jUhzkTUNUVuFGioNBN+lInlzJZEh8cyI4bQ1MMC25AIk20lk1RsYwWeC5G2VpOaCjkNowg/JeH5zKhbsvDn4m/+bC1fTT5/5KQU19QacyangrOALABtO2xoJh6+U4rG1Z/HhPssiZOahhr8uFOH5zect4vUAcL7AOHlzobvRv6Z26/RGA2rl0Wucb5TW4ZENPAN/SbUOnx/KxrHsMjy/+TyWH87G1uSbYS7NzVJFN958bUOeb+++OXFZL3Gvt7qPdVaG6MlrFbz3jqN5OUKrsX684TkTMliq6vQYtynZ5vPUgirLBFQO9er0DH6ys9cXF2LkfSflVmB/RgnnsZnbLtoNoW5NLmAThX9JysfD353BZ2b3YVJuBf7vl/NYe4Lf2DVHb2Dw/Gb7nhyhFSsrCY3KMoKFCd5qhaBMLUGOHYGIaMt5SUJI4nhUSOYry7+poXILYGAYnMmp4F25QzK2ktzwJO14iRD6ASCYGKo3MII3EpGhQhge4uNIVhnruTkpsGGXGBUivziYbTOxWrPQKj/mzR2XUVGnx86LRcgxK+sdqLU0HC4VVmP+TmNVX9OGnNaeFnNM4QEuQy6r1DY8xuXuXsGxWZp5CNPAAD8nFWDpwWx2iWuAl8ZC3lRTwhx7XW3tIeMa4/j2X0ovrsHULeex2yzpc8+lIpzmWW5KMtmkF1VzehHM+TO1kDdh8L09GTiXVwGd3oB3/87glKmo01tssiqMpd5XSmpQUq0jmoRNvMGxr5U5/6bzex+XHszGs7+koN7A4KvDV40vL+ev43JhNY5lleHlbRdxuaga353IRYlAVW3A+OwJlYknDUVm2kluB8gmTZJVlnvteGdN+PiLE/oRBSdCNk42YwPJwglHoYaKyPx6rgCzfr/IG3YgC+uIM6nXk9TzIAkhCSwt1jPCb0D1BuHlcmS/yb7M7D/SiAY5MZb0br9QKJj4fPH6zYHUOgn36JUybE7KR1Wdntf9/F92OerrjQOpPRf1v+klOH2tHFoP4bdDA8NwLrv88Wy+jUeEb0WEqRKrUmbZj3us7vsagbLhpmNXS2vw2h8X8fi6JBsZe8bgxevVWGyWoGmvXD7JNefbTNSiHYH76+WtF/FnaiFbOt6aqjo9e00BY+7K7+evo7beAIZh8Ou5Aqw7mcubH/bMTykYu/EcRm9IIt7DpkpgbzChrsmv0OHEVcsXlv/bfN5mY0+SOj8kLwkkT2dtvQFTBDwz9hJlTdQR5JL9fUk4QTTfTr6cCZLfRZZwa1+IIW7HPiT2YuemllvMfHYgS7DAp6OIE/yksHxppyAQQDYZEyUwEciUVwjXHSF5cFQ8yzpNkCXTGt+W7dkZJHYVl8fAnDO5FSgimGzE2nODb8krF9aD+uc3EnCzSmsR7a/h+grm/nUJszt4oG9IiKBR9NbudIR5C6/02nWxCLt5kjL/TS/Bg62DARj7aDnP/Wya9HUCy0W/5Nn7xLqd9/dmWqzoMUenF65ES4KQ9wsAvAjCAF4q+zIMYHeg/jejBA+FVyEkJATVOj1m/n4RtfUGHM4sxZGsm8aAXAaM7hDOGcI1/ZZlB7PxzqA4lNfWQ+uhEKx8zQdRsjvhCkAxZEgud9r1KjbkyQeJR4Xkzmoe6GmxlJqL3CLxShKIgSh1VAhkAjhyqBb9nYHVoxKEv0wI9ai4GZL5kcSYIRlYSB5AEhmh/YkAYetdT2DMENWGIZhs7MXbWX0aYQ+LtEJuN/W2lOt2++bfHONbqqeAt6Su3sDrdTE3zD76h7+w1qf7s9jlyn+ev44DVnkyJkzXSui6/2lnJRBgNDyvldXyGimAMfRjT2cTQkuKia45SUiVwGvlo+Z/BzQwwPECo/mRW17HJgmbGykA8OONXBZ7RlpJdT1OXi3HE+uS8MCqU/gztdApbyGJt17IKADIXjas85K49RGWEXqBAsg2gTUI/K4vD2ejeaDw0mOi8dZNJfRJwjpitcPVfSRVhh2BGipuxpnkJGdl/AMCRdGHxH0qWEeFYQTbIQr9EAyWfDkNFvqI5FERy9yx138qL6NrVWgZpclrxYUjS6U3nzNOkP/ZWS1hmtgUhHUteNsxCOdP6PQMUW2GFwSW2hK9yRNcUZK3dK2A12VdmtHrZ88DotMbjbjZf/L3j05vwOvb01gj4pN/r3BW2hVCaLI2nUuwHZGeYRIZkjIOJC9ZQr9qc1IB0b0THBIiKEM0XpAkyhLJuLFoixViJ9RSQ8XNiOVRITEwiku534bNIXkASeoMkLgZZQI6k7zVkSRqieWZIYHMqGTwOUeSqTn2uvh6qdHlLGQMGhiGd3ByxDAzyXraeWM1GBicy6vA8auu7eBcb2CQzZHsaw6J4UkiQ5QbQdBNJOEVkohgTb0Bnx/kX9KqM9jW5+GSsb6Vlx3Igk5vwJ5LxRabKNrDnQYGyb0olIsG2G4nwYWcxFAh8vAIn6u4uERQxm1+XEacVT/OltMQ21ChOSpuhmzpsXA7RK5agnLbRBVuCQwVsknU/snEeqsjcT+LlZhO8gb+X3Y5fk22v++SvQHVVLdCOHTGL2PuSlcpZHYNPtMhezkxeobBTI76MY5CZFQS3RfiTH5iJTsqCIQOZZbYXZ1mYCC4uzPX79YzwJDVp9m/v3w4XlAXknGAtBaSoIxI15Ms1CIsQ1IWgWTc1ukISugT6OO2Ym5iyXAIUY/KLQ6JA16sVT8KpbAdSjKwkAy6QiIGRvjmJTEe3DlYkkAyEJoqbNrDXs/IbpR+J3mT57sO5j9XLfC6b+obe4nCeoM4O8ESvc2KFO4Ty6NCIiNkuAPAsSxhb4cfz3YAJkgM99+ShQs/uloawARRjgqJoUJgPZB6M4UgG2+Fz6X08BAWchOieW6czIV0NqmbD2qouBky610cGS3BfiIk+rgyQZpgGAYqAcNJrJCNWC5qEkha8SLYu8keHio1ALLJjy8Rz3yyFzI8TddBace3TrqvjxBE3i+R3sDJEtDF+V0k4zTJcyWUMKozMMIvAEQ1jARFyFb0iPQMi+ZRIZARKxzv6+snij4kCI+34pzH2b6hHpVbHKIsaoJ2SB6cIoKYKcnAQnLPyQnW9Rv09l2jZIYKQUKfOw0VEoNRILESsD+AVVcbVwuRhBz4y8ebGSqCE9sNOTtiYq2aInkeSM4lVm4EyUxC5M0kMe4JHPhCRqWexFARaZWNWN4v0V4kRLpWYnlUyLYsEW7HTSmwhPv4OEdOeZ1FQUtXoYaKmyF6/kRK7hLL4BHDo0K2w7LgaUQLD5EYMySQTLRCoRbA/qBhUtWVEJz5zyVdJm7vepF44kgQKzeCxIAlyXUh+VkkkzGJ94tnM2erduwfNzAkhifJ8yCsi1ieB7FyjgwEz15VHclKJUERsgUOws0QSwkhZOSSeZsa9mXtje32V/M5AjVU3IxY1juJMaMh2HacZOInGnQJ9r/yUAoVyiLJIXDfGzgRIr0h2ftdptg3kWeLYNWP4MR2Qxd7cmKFfkgMRqJCgET5E+LkqJBMtCQb8pI9V8JhOqFzuXOlIVGOCknoR6QclUqiBQXi3BdaL2/hdoSbEaWibGlNvWCV4P+y7W/WCLi2pxzX1h3OQg0VEZj9Rxrm77gsWrKeWMYMkQzR26FwO0Jr9o3ncd2jQhZLF5YRy1AheQMnGXjsaWNSlSxHha8NB3JUDKbz8cuIFfohMZSJ8h5EC/e5L3+CyPAUGKGNK72EPSpibF8hmveLwAgRq3wA355M5pCtshTrBVNYhuTVxl0lUoj2DHJD8Uy6PFkEzhdUotYgw7YUcbLrxXoDqqy2v2EXQJqj4nodFQMAfb390vai7XEkVr4CAWI9o/aaMS17JCvyxP25+c8l9qjYC/2I9LuJrrlYy5OJkkEFRchCi6J5KoWNEJLrqZDL7Oot1phDlH8iVjItybUSqe4S2ZYlwjWF3BkeEgMi094N6lKPioik5BPsrSOShUrmmRFHRgxI9BXrrUWsAZWMhjd4HMtREQ79CO7LdEPWXm0XsQw98ZIvxalGTLbCSJwEHbJQnv3jDIGM3kCel2T3XERGnDi5QmQbF4oTBnZvjoow7pj4SRGrb1xFEobK1atX8eSTTyIoKAharRYdOnTA8ePH2eMMw2DBggWIjIyEp6cnevfujXPnzlm0UVtbi2nTpiE4OBheXl4YPnw4srMtqzoWFxdj3Lhx8PPzg5+fH8aNG4eSkhILmStXrmDYsGHw8vJCcHAwpk+fjjqBjdfM9RSCKFlPpJvDiyBm6q5S8gaGgUptf8M8soQ+kSY2sXIs3GAMqlTGfiNbfSWsA7lHhV/G3nWY/msqvjpsv6Iqey6RJi2xclTEWpFCMhaQeFRIjFOh62mvYrEJscYckp0aiIxB0cLowjJiFeH08w8gOJkoIm7jWplwnok7XnYb3VApLi5Gz5494eHhgT///BPJyclYsmQJ/P39WZkPPvgAH3/8MZYtW4Zjx44hPDwcAwYMQHn5zWSgGTNmYPPmzdi4cSP279+PiooKDB06FHr9zRjlmDFjcOrUKWzfvh3bt2/HqVOnMG7cOPa4Xq/HkCFDUFlZif3792Pjxo34+eefMXPmTKLfQrI6hsSNLdaqn8oq4dCPu3ZzNjBAvUDlRgNDEksX1kWMN2fSuKtYCZr2rkMdG/pxwaPiSI4KY78twH4e0PmCKvySVIDUAmEPo1ib4ZHVURE+l1hhHZK7x5XkaEdk9CTPlUhhMbGMEBKvFUkfi1Uen6SdsnLh5FQSL1BpjfDu7/Y28RSTy0XCc8gdkaOyePFiREVFYfXq1exnMTEx7L8ZhsGnn36KuXPnYuTIkQCANWvWICwsDOvXr8dzzz2H0tJSfPPNN/j+++/Rv39/AMDatWsRFRWFXbt2YdCgQUhJScH27dtx+PBhdO3aFQCwYsUKdO/eHampqYiPj8eOHTuQnJyMrKwsREZGAgCWLFmCiRMn4t1334Wvr6/d30IyqJA9XMIyJDdHnV6cRDKyZWyuG2BEBbnclKNiYMhWbrhjF2aTrq5MfuYTEWnox15fk/xuoT18zM/lqgzZzr7ukxGrei1R4TihsI5ooR9xDAx3FnwTaywlWg2mEzYwSPQ5lyds4EsJsbYjsUeje1R+++03dOnSBY899hhCQ0PRsWNHrFixgj2enp6O3NxcDBw4kP1MrVajV69eOHjwIADg+PHj0Ol0FjKRkZFITExkZQ4dOgQ/Pz/WSAGAbt26wc/Pz0ImMTGRNVIAYNCgQaitrbUIRfFhqBfe6yGvXDiMJFY5a5lM+PK6I75oQnippXAbYr0VC8mQ9otYlVXtnu5GvxFtEc+718/Nf4txHUj6h2THZrGWkpPkRohV+Vis+kRkq35cD/2Il6chLEO24aBY2x0Q/C6RPGRE11NBUNhRSnEdkbgjPCqXL1/Gl19+iZdffhmvv/46jh49iunTp0OtVmP8+PHIzc0FAISFhVl8LywsDJmZmQCA3NxcqFQqBAQE2MiYvp+bm4vQ0FCb84eGhlrIWJ8nICAAKpWKlbHHhg3rEdptmF2ZZIKE2+oa4b1hDmaWCsroCQbvymrhc5FUuK0n8t7Yv6Grqmsgk9l/mEn6Jjff/gaAAFAnMImmZ15BfU0Vmx/CRxWBPhlZ/Dvkmiixs9O14cZ1JKl8WV7GvX/M5YwMKIvliIyMRL2AQV1dU4vk5GRUVGp5ZSoqhV3CufnC+uYRXCuSc13JviYoQzIhZWVfFZSpJlhNdzVHeLwoI9jdvLpSeLzQ1dn3XNUQ5NiVlArvO1RUXCwsUyLcztXcPEGZ6lphnS9fTheUITFgCwl+V0WVcKiljsCjsv1CoaDMrUaVnedBp9Ph4kXj5qWhoaGQyWTIyzNe/7i4OFy7JvzcAhLwqBgMBnTq1AmLFi1Cx44d8dxzz2Hy5Mn48ssvLeSs4+UMQYKYtQyXvDMyfIx/cqygDAmqG3u7uArJmxTJuXz9/ARl5HLhtwmhHiTRxYNAJiAwSFBGqGeaNo1CQkICWrRoYVdOrhTeiCw8oomgjL2woknXoKBgwXb8ea5VVFQ0EhIS4O/vD5XKvs5KDw8kJCTAU8tvqKg1GkFdvP2EkwuDgoV/k0ojfM2DQ8MFZUje9kPCIwRlSO7BoBDblyJrAgP8BWV8fIQT4j0FroVcoRT0onn5+Aiex9fPX1BG6y2sbzBB38gVwu/QMbGxgjIkNUlIfhdJ8cw7lT8v8S/L9rgxliQkJCA4OBhBQUHs32q1GtHR0UTnaHRDJSIiAgkJCRaftWnTBleuXAEAhIcbByBrj0Z+fj7r/QgPD0ddXR2KrSxjaxmTJWdOQUGBhYz1eYqLi6HT6Ww8LVx4qsUxMEQrmuqmxFNShFoRbYt4olCB/eNihn6IVjDY1UVYxgTffGT+XaHy2+x1sJejQvCbakkSIknc7iL1sVj3F1mROmEZd0UBDAzB7uZEIRL3hVFIZKoJqs6KlfdGFu4jEKIAAL47noMpm8/jPEGEAZCAodKzZ0+kpqZafHbhwgU0a9YMABAbG4vw8HDs3LmTPV5XV4d9+/ahR48eAIDOnTvDw8PDQiYnJwdJSUmsTPfu3VFaWoqjR4+yMkeOHEFpaamFTFJSEnJycliZHTt2QK1Wo3PnzoK/RaytrcW63xUe9sMWAOkAL3wukglHQRDDFdTFTQmRpIMOWYEr1yZsU7+RDN58nj/z7wrdpSZ17Z2NKLeEqGiXOJMWUY6KWEalSLkR7spXEGv3ZLLkVXGeTxJ9fj0nziaAYlWUVXtSrwsJ1yvrsPZkLtIKqzH7zzSi7zR6jspLL72EHj16YNGiRRg1ahSOHj2Kr7/+Gl9//TUA48A7Y8YMLFq0CC1btkTLli2xaNEiaLVajBkzBgDg5+eHp59+GjNnzkRQUBACAwMxa9YstG3bll0F1KZNGwwePBiTJ0/G8uXLAQDPPvsshg4divj4eADAwIEDkZCQgHHjxuHDDz9EUVERZs2ahcmTJwuu+AHIVomQIFaCK0krJMvciJJBCc4lNEUyDEGFW5LsexGqlJKu5hGr7oZYO/vyvXl8+18OzuVWYnznCOG36xu/3d7pxCrgRzb5EcgQbWjpvklUrAJhJEOK8PUkea7EGXPEmvSJPCr14uzjI9aKJ/fte3xrkl5Ujf/tz4KP2vEX1kY3VO6++25s3rwZc+bMwVtvvYXY2Fh8+umnGDv2Zr7Hq6++iurqakyZMgXFxcXo2rUrduzYAR+zuOonn3wCpVKJUaNGobq6Gv369cO3335r8Ra/bt06TJ8+nV0dNHz4cCxbtow9rlAo8Pvvv2PKlCno2bMnPD09MWbMGHz00UdEv4UkQ5+EfZdLRGmnrIqsUJ0QRHVUSPZIESihT4J47ns3elRclKm/MSC7EvpJK6xGWmE1/D2VRDtdC52QRBexJn2ia+7O7RdECoG4sorLEfQG4Rw78QwV94WQyIxlYRmxVhtWEiTc3snM2Z6Goirn5gCHDJWkpCQkJiY6dSJ7DB06FEOHDuU9LpPJsGDBAixYsIBXRqPRYOnSpVi6dCmvTGBgINauXWtXl+joaGzbtk1QZ049nfpWw3Gtyn2DjxgVF68SVUF0jweDPEeFwEATaR8asnc6+3fhzotFgm80JlUMLgYh3VkVVKx8LKKCbyJVUBYr9EOScyTG2CRWGEWsAmskiLWXlFjG1Z2Ms0YK4GCOSrt27RAaGopRo0bhyy+/xPnz550+8e3I7XqjkvyuJIIiRR4ewitkhCDbb8R144FkMgJIvQauGU4K5Y33CaJwgn0ZY9+QTVv2TkdW8ZOgbwj0IKuaSiIjzrlE8wgIi4gS+jF6VFzXhQSxPFtijaVkRqWwDMm44+0tvHKK4hwOeVQWLlyIffv24ffff8dPP/0EmUyG0NBQ9OnTh/1PaDnn7Yw7i6e5E7F+F0nlRjEQw31P+pvF2pHX3vlMdVTEGFDrRZq0xPJgiJWvQGRgiGaEiGM4Ed1hIsR+xKqeLNYKLbGKJJIgXihKWIZkt3qKczhkqMybNw/z5s2DTqfDkSNH8Pfff2Pfvn349ddfsXHjRshkMkRGRqJPnz7o3bs3Jk2a1FB6S5Lb16Mizg/Lr3Z911mxqmMK/SZRDRUXjRmToUJkQAgcNzCM8I68pmRaFy87yYRENPmRnEu0XBcCfUSasN1R0dN4ImF7R6w8NLIkYpHaEcnIPZYtXKSOKIlfhBw8CjdOJdN6eHjg3nvvxb333gvAuFz48OHD2Lt3L/bs2YN169Zh/fr1d5yh4o59XxoDKRlgZIOccDtCMqT7V4i2XNp+DX0yZSBsqNQbGMGcBpK2SLqHzKvgvpyQ/RkE1Zzd+AZOMlyIklsCQC5CS2IlPosVjiFBNMOTKPFZDjKzmuIootRRSUtLQ1JSEs6ePYukpCQwDGOx+/GdQmaxcDn1WxEpGSpJucK5MCSTn9DbrLihH9fCEgqlMfmV5A08KZe/SiTgWOjHrqEilmdLtGXFwu2QINZKErFCP6LlsRDICCFaSFAkQ48Esdr5h2AlptbLS5RzUWxxyqOSmpqKPXv2YO/evdi7dy/y8/MREhKC+++/H/Pnz0evXr3Qtm1bsXWVPCeuCm/zfSviNhe1SGSVEOzaK/CTSJNp60WaRO3J1N9wKZOolCuw6aUj4Rj7110kz4MIRqVRGzfmNBAYYH+cF2dPl8xi4bwHorCOCK+kYhXnc2syrUjtkBQCLC27Pcd/KeCQoTJ27Fjs2bMHeXl5CA8Px/33348FCxagV69eaNOmTUPpSGlkpORRISGvgmCHajcuT3a1Dgh7SITr4MgyaHtqXy4S9h4SbJ5MNKGT3H+/JQtXKSWBLBnUfUbRxeviJGiK4VERb+kxQTsiLdd350vW2SIa9mkoHDJUNmzYAG9vb8yaNQvPPvss4uLiGkovioQg2fH5VkM46ZSsHbGSae1NWnK58XVYjCG33sAIu+dFGtz3Z5SI0o47V9ORGJX70ktEOZc77X+hTQlJ2HOpWFBGrOX6YiXlkuaaUaSNQw7BJUuWoG/fvli5ciVatWqFpk2bYuzYsVixYgUuXLjQUDpSKKIjNBCSJka7o46KybcvxnytNzCCA7yIDhxRcOdk406jyF0F30jIKhUnv06ssM6RLOGVOCTklQuHgSnSxyGPyksvvYSXXnoJDMPg1KlTbI7Ka6+9htLSUoSFhaFXr17sfzQcRJEq18rsh4fY/W4EBl4Sj8pfF4oEZexNxvV6Uwl912c2Eo/KzdCPNEwVkpwQsaioFd4/RizcZRSRnMWVqqHmkGz/QeKZqdaJs/M2SYiSIn2cSqaVyWTo2LEjOnbsyBouJ0+exN69e7Fz50688MILAG4mAVIotxyMxf94KajQiXK6bII3WrHmNcFmCH+7u3Cnl+NApvASZrEgTdgWA5G2IZMUErGjKW7A5U0JDQYDjh07xq4COnDgAAwGg+AmWBSKlDHNIUKD4RmB5cCk2EuaVMhvLE8W5UzCv4kkmdad3GrJ3KSIVXeJZKi9HYfj27USOMUWhw0Vg8GA//77jy3uduDAAVRWVoJhGISEhOCBBx5gy+lTKLcqjIS8CgbmhtkkmjLC4aw6vatbEorHPyIlr0oNd020pTX1ECkFRVJI5f6kNDwOGSpDhgzB/v37UVFRAYZhEBAQgP79+7OGSUPsrEyhNAYMYY6KOzDlaIhXK0RYZtPpPOm4VG5TxPIU0ctEud1xyFA5cOAAevXqxRom7du3pyEeym2J1Fa+AO4NgXx/Ihej2oW674R3IOfyxAkb3o7lA0gQq54NRfo4ZKgUFRWxNR0olNsZMYusuYpcoRC1veJqsiR3+qbesAitPKPYh96etw46F/e4cMhQ6d+/P7GsTCbD7t27HVaIQpECpjCLFGpN6k3Lk0Uama+UkCUs0ImAImWoIS19qnV6eHooUENSptoODhkqe/fuha+vL6Kiolw6KYUidUxeZSnkqJgQK0eF+HwS+u0UijVeKnE9jRTxeWnrRXz5cLzLRqVDhkrz5s1x+fJl+Pn5YdKkSXj88cfhRXeMpFAaFJmIlWkdgZopFClzO9aGud24XFSNkpp6KFzMZXUo4SQtLQ179uxB8+bNMW3aNEREROCZZ57BwYMHXVKCQpEaNyvTNrIiAExbyrlbFUn8dAqFB5pLe2ugkMlcXorvcGZsr1698N133yEnJwcffPABzp49i3vvvRdt2rTBhx9+iLy8PJcUotwZqBQyNPPXYMRdIY2til2kMBbqb5QwdbsuUvjxFAoPtODbrcPSg9kufd/pJTy+vr74v//7Pxw5cgRnzpxBv3798Prrr2PKlCkOtbNgwQLIZDKL/8LDw9njDMNgwYIFiIyMhKenJ3r37o1z585ZtFFbW4tp06YhODgYXl5eGD58OLKzLTumuLgY48aNg5+fH/z8/DBu3DiUlJRYyFy5cgXDhg2Dl5cXgoODMX36dNTV0cz8hmDT2Lb4amRrTOnetLFV4URqOSr5FXVud+9I45dTKNxQQ+XWQM8w+NfFoo0urzVOSUnBmjVr8NNPP4FhGMTHxzvcxl133YWcnBz2v7Nnz7LHPvjgA3z88cdYtmwZjh07hvDwcAwYMADl5eWszIwZM7B582Zs3LiRLUg3dOhQdrUEAIwZMwanTp3C9u3bsX37dpw6dQrjxo1jj+v1egwZMgSVlZXYv38/Nm7ciJ9//hkzZ850smco9vBSKaCQcJCZDf00sh4AUKMHntx4DrvShDdzExM6D1CkDA393BqIcZ2c2uunoqICGzZswKpVq3DkyBHExcVh+vTpmDhxIiIjIx1XQqm08KKYYBgGn376KebOnYuRI0cCANasWYOwsDCsX78ezz33HEpLS/HNN9/g+++/Z5dPr127FlFRUdi1axcGDRqElJQUbN++HYcPH0bXrl0BACtWrED37t2RmpqK+Ph47NixA8nJycjKymJ/w5IlSzBx4kS8++678PX1daarKLco/9ufhR7N/O/oydrdq4woFEegBd9uDcTwfDnkUfnnn38wYcIEhIeHY8aMGWjVqhX27NmDixcv4vXXX3fKSAGAixcvIjIyErGxsXjiiSdw+fJlAEB6ejpyc3MxcOBAVlatVqNXr15sAu/x48eh0+ksZCIjI5GYmMjKHDp0CH5+fqyRAgDdunWDn5+fhUxiYqLFbxg0aBBqa2tx/Phxp36XFGkX7i35vBApUFxdj88OZN3RU/WdbKRRpA+1U4woJeyZBsQZRxzyqPTu3Ru+vr4YO3YsRo8ezXoZTpw4wSnfqVMnwTa7du2K7777Dq1atUJeXh7eeecd9OjRA+fOnUNubi4AICwszOI7YWFhyMzMBADk5uZCpVIhICDARsb0/dzcXISG2pYDDw0NtZCxPk9AQABUKhUrc6vzYpcA9Izxx7dHrjS2KkhOTgYAp41bd7At5TpiPO7M8uQAUFNzG+5kR7ltqKb3JwCgd4Qcu67qhQUbidQLF11uw+HQT1lZGVauXImVK1fyyjAMA5lMZpEjwscDDzzA/rtt27bo3r074uLisGbNGnTr1g0AbPYTMrVvD2sZLnlnZG5V/je8FdqEGmvehIbWAFk5LrepUcqdrjiYkJDg8vndgcw7CIBrGeu3Kmq1BoA4+9FQKGLjoVIDVdRYebZ3G+zbeA46vTRdTM3jWgAnkl1qwyFDZfXq1S6djAQvLy+0bdsWFy9exIgRIwAYvR0RERGsTH5+Puv9CA8PR11dHYqLiy28Kvn5+ejRowcrw7VsuqCgwKKdI0eOWBwvLi6GTqez8bTcigRpPdh/i2F3tY/wxqXCatcbAvDM3ZFYeeyaKG2JTcoduuEbQHNUKNKGdCuI2x1/Tw+sfiwBpTX1mLol1eX2Fg2Ow+vbL4mgmZGT18qFhQRwyFCZMGGCyycUora2FikpKbjvvvsQGxuL8PBw7Ny5Ex07dgQA1NXVYd++fVi8eDEAoHPnzvDw8MDOnTsxatQoAEBOTg6SkpLwwQcfAAC6d++O0tJSHD16FPfccw8A4MiRIygtLWWNme7du+Pdd99FTk4OaxTt2LEDarUanTt3bvDf3dA4GsYM0nqgsEonWnv2GNk2VLKGirtX2kgJmgNAodwahHqrEOqtEqWtEC8PYSEH+OxAlsttOLXqR0xmzZqFYcOGITo6Gvn5+XjnnXdQVlaGCRMmQCaTYcaMGVi0aBFatmyJli1bYtGiRdBqtRgzZgwAwM/PD08//TRmzpyJoKAgBAYGYtasWWjbti27CqhNmzYYPHgwJk+ejOXLlwMAnn32WQwdOpRdTj1w4EAkJCRg3Lhx+PDDD1FUVIRZs2Zh8uTJt8WKH0dKGAdrPRDiLWSoiGepKOUydG/mh0OZpaK1SXEdHbVUKJQ7DinuoeRyHRVXyc7OxujRoxEfH4+RI0dCpVLh8OHDaNasGQDg1VdfxYwZMzBlyhR06dIFV69exY4dO+Dj48O28cknn2DEiBEYNWoUevbsCa1Wi61bt0KhuNnh69atQ9u2bTFw4EAMHDgQ7dq1w/fff88eVygU+P3336HRaNCzZ0+MGjUKI0aMwEcffeS+zhBgfCfbJdyAscorADT1U/N+Vy43z8Wxfx6SG/XZrk14j30x4mYtnUGtAgXbAiCNgiUc2OvT2x26/JNCaXye78Y/1orNiLtCEOwljmdGTBrdo7Jx40a7x2UyGRYsWIAFCxbwymg0GixduhRLly7llQkMDMTatWvtnis6Ohrbtm2zK9NYvD2wOcJ9VPjuhO0KpP8Nb4Uofw1UCjl2XizEh/tsV/UozIwTGbgtFQ+5DHqGwWu9m2HpQW533f+Gt4KHXIbYQE9e26JFsBbz+sXialkNHkoIgY9aiZ/O5gv+Rini6mZatzLUUKFQGp/7Yv3x5eGrRLIxARpkFNvm7qx6rA0m/Zgi+H2pVgpvdEOFIswPYxPh7+kBhmHgr1GipKbe4rhcJoNKYXSOaZTc3hDzUA3f1Lv2ibugMzAI9VbxGjOmlUNC3BfrTyRnQqqJm3dy+KP+Dv7tFIpUkEGGZgEaZHIYINa82T+W0yBp6qfB14+0Rp2ewQs8Cbcz7492WdeGotFDPxT7vDOoOfw9jclNMpkM/xveykZGQWCEmJer5ytdH6D1YBOy5G6+M6RaXOxaWW1jq9BoUI8KhdL4yGTA+w+0IJJt6qfB6Pbcq1RjAjzRKljL+91BrYKc0s8dUENF4lh7NjwUtkYGiVFhbpw8EC98Q3oQLOtxduWPO2OuFOehHhUKpfGRyyzLSwhxO0araeingQnXyjGylTe0HnKnbqAgeTUKC2+uvtHVG/DKPf4WMrKaMhTWG+t9hHvobI4DQElRoUXhuhUPRuLC9SoLmcLCQvbfI+M06N/U9vYwl3mhoy/nZGYuAwBdQ4BYM506hsttZIbFqnB/hK3egNFjpG8AlwvDAFU6A365UIHcKucK193OUEOFQml8HC2R31AFSv00SpTX1jdK2QJqqDQg4Vo5nu3gj9DgIEDmnPMqzE9tsQqn3mBAM7llnkhooAYeN3JU1LX1MKjrbNoJtnL5+dQbUOtxM+bppZIjyE/D/l3j4Y3KWtvKwkFBN9tpBi3nZGYuAwAGdR08fW7m1VjrAgA1Si/419kaCx4KGWICNLh4XZzicjYwBgRrlVhxqgQ51FixgIZ+KJSGpX2ENyJ81Nh+oZDz+L0xfvBWiztNv3hvFP6337naJo01JNDQTwMyspU3QoODoPIQc126SNayVTPhPmp7h7mbIFTFWQM/OkCNaH9Nw25hIJOjeWQo3u0bISx7h5GUd+dW5b2doZuSSoPFD7TAh0Na4qX7ojC6A3deybx+sQ63KzRaDm4VJFiCYtHgOM52SVICGgJqqDQgWg85IJOjia9wLQ5/TzKrmes2cebWsf6OdYItkaHC8ZlKafupM4ZGsJcHNEoFb+KvmMjkcmiUcjzRQnr1AygUsVEr6bDf0DxMYAx2bGKsBSaTyfBUl0i0C/e2kWmIlzSFXIYuTXzsynRp6otof43N5wsHNhddHxLoHduAmO4xklvNR81t4YpxmwZoHXcdciXtWsP1DHEZZc7YGgGEhptYyGQy6A009EOhUFznCZ6VN/bo19J+cUx3G5jWU4BMZjRgnr3H/TveU0PFDQhZxWqlTLRMbVOuijlBnrYZ40KnC+T4jrPnJwsj3ZRSymU2faYkMJxcxVNj+wZBoVAojqJSyvFGvxgkhpHVnQKEx8nWIfxLiy3acdYdTviVR9qGYlS7UMcbcAFqqDQwAZ5K3hvHV6NAoFaJSF815IR3jpCUWilHoLUHxYl4kVwuQ6Sv/VCIJ2HujbdZPDSIZ8Mrc6+LgWOFT1Oe8FmwwAZaKoUMcUGe8PNU8m62ZTqblxf5oEKh3KrchqtX3cpggnojchlwf2wAPh7WCm05Qjp837HHK72aEbVj3cwjCbaeGqdyEE0RApkMz9zj3hIT1FBpQOJDtAj28uC9KTRKOYK9VPBQyMnDIwRGRyDBmnu+yrMWMgKmeTDh2v5rV7PRLb4pctPO8YZ0zCvnciWWq5RyznCUv6cSQV4e8FLx38oKuQxh3ioECOh7vZA7855CoVBMPNkpHJ8Mawk/DX942plNW4W+EuqtwpMdLfd7s1fAzURXnwqOcznudiE5V0NBDZUGomczP3iplJDJbMMYJsw/dzZpSi4T3o/G+ujUqVMxftyTTp3P4txyGcJ8yBNQPZX8D3CgmecpwoE25TIZgrQeaOJHwzYUCgl3skflyY7h2DA6EYnhzntP5TLgrjBv/PhkW/Ti2SrEfJgjfwd1vMjmm/05VgVZjbEqkcLm03tGidKOM1BDpYEgWW5unkDL51ERsl+iOJbvNtRApPFw7XZRKvnfQJQKOZr5axDlr3Z6m3G+hGRzQrz5vSr+/v5OnZciXTaMTmxsFaTHHWqpNAvQ4PH2YQjy8hAsF/9s1ybo1yKA85j5eOvNM+aYv5A1ZH6dacsTezRp4lyYxnxaSQz3atRdlamh0kBYGx5aq9BEhK/KcqNAmQxeHDe9xirT22ZZMcEz4Ii35sCBA+jfvz/Cw8PRud1d+PyjRaivNxZri/RRYdeuXXjggQcQExODuLg4PD1+LLKvZFi0cfz4cfTq1QsRERHo27cvzpw5Q3RulVIOTw+F094lkoc2wE6SsE5nWyiPcotzh07KFFue69qEXTmj03O/SoZ4eWDBgFg8fFcIfHlCOySTpvn4TxKKFxPrW7662rlimRbtNHLtR2qoNBDWIY4Iq4JqXOGaSKuQR5S/WnjS5jju7ER/7do1PP744+jYsSP++ecfLFr8Ibb+tBGrv/wfAKPXo6qqClOmTMHu3buxZcsWyGRyvDb1GRhuLO2trKzE6NGj0aJFC/z999947bXX8OabbwIAa/A0FFw1V4iWWd/4f2VllV05yq2HvavfLtwbYQTGLeX2o07PXYrg46Gt0KOZPxRyGep5jBnLsA5PWN/s348kurfAnrVGRUVFgjJShxoqDYT1pElSuMzawOAyZhoyzLNq1So0adIEH3zwAVq1aoUHHnwQz0ybiQ2rvmYNkeHDh2PYsGGIi4tD27ZtsfjjT3Dpwnmkp10AAPz444/Q6/VYunQp2rRpg0GDBmHatGkiankTX41wqIfEy2JaOdRIRRcpDQjfhAQAr/Zuxuu6p4jL5EaovWEPvvvCfHjl2+vK/CWUbwwyH6fjgrR42I3GijPvqa/3ibF7vLE306CGSgNxK056Fy5cQJcuXdiHTAagfee7UVVVifzcHABAeno6Jk+ejI4dOyI6Ohr3d+0CAMjLucq2kZiYCK32Zob43XffDQBQq4Ur9NrD+mEJEYiZ+nsqOeu6mBOkvSnTNFK4jH6Un2u/geJe+Nzuk+6OQKi3Cq8SLPlMDPfiLXHepakPtj3V3iUd3U3PGH+3natPXADe7B+Lx9o5XgDNnG8ebYOtE9sjNpA7aT7Ey4Ozsqs55lUP1DzjgrmMjseYMR/b20fYr/Bq4u6mvkRyQpC88Iabeeaj/NRo06aNjYy1MXN/c3+7Mlx7wjbjqFzbUFBDpYEQWp4mVlEeZwvFcYWHGIaxWYnE3LhDTZ+PHj0aRUVF+PTTT7Fz505s/n07AECn07Ft8FFXJ14OiJdauLw+Sd+YGzLXC/KFz2sn0Xdo6+BbzqV6u6NSyPHFiHibz023aWygJxYO4C8LvviBFvh4aCu0DOJemjmle1OoFHJMuvvW2SuqVbAWcwTeoOd10eKBeOF6IfYI0npgTp8Y3OuiYfRQQjCi/DVQK+V4Mo57ynq8fRje6BeDp7pE2F02bOKB1sGcYWHG7HXInyefzXyM7NjEB0NaC/eTM+NCQqjtyiSS6rS9mgegW7QvmvqpMb9/c6SlpdnVx0et4JyvhFYhvTPIdj+ghoIaKg2EGB4Vd0968fHxOHbs2E3jBMCZE/9B6+WNkLBwFBUV4cKFC5g1axZ69eqF+Ph4lJWU2LSRlJRkkcD133//AbBvxDhKQ/QNY7DdLdqal++P5j3WLsIbfz3T0WU9+FYb3OoMbR2MuX1j0CfO9d/nyMZ6LQTqP/AVIRzVLhQdIo1v6bV8oYIbd+IjiaFEq86kQp+4AGwZ3473eJBKjxn3RuEugsqq3Zv5cX7OOBgw+HhoS552bqKv1/F+39/TA6M7hGMWzzNqro9GKcd3j99l91x8XjTrsf3pu4XDWs68UM7jWHpMYqjIZTK8NTAOqx5LQHSAhn2JNEcpl5v9m698hv3zhPmoiHIAxYAaKg2EMwV/nMHZs5SVleFCyjn2v7Nnz2LChAm4evUqXnvtNVy4cAHbt/+BlUuXYPRTkyGXy+Hv74/AwECsWbMGly9fxj///IN3Fs63aPfRRx+FXC7H9OnTcf78eezcuRPLli0DAMjl0r7dvDyFXZkxAZ54j2NnUTH5v25N8eK9rtcsWPpQKyI5H7UCo53Ym8RRpt8bhV7NAwTf5gH+wdNEPEE5cXsTiLnNzHdX3hXmzb4919bb3wfKQyHHU124zxfi5WHcoJQQvgrKU7s3xf91a4I/J3WArwhGkdaOd9Db2/jbPxrCbTyYaB/hjQVctTycgM+gNL9WXlpuw8lcRk/4QiRUX8RHrcTyka1tPrce20nGemcWOARxhC35Qlb28Pa2DYmN7xzOPmNv8OzQbF5Rl89gddfLtHt3fruDEAxLuEkPPvbv34/9+wdZfDZ69Ghs2rQJ8+fPx/333w9/f38Me/QJPPX8iwCMhsbKlSsxe/Zs9OzZEy1atMD8t97FqEdGsG14e3tj/fr1mDlzJnr37o34+HjMnz8fEyZMsFtHRQoE+PkBsK3iaA3fTtem4THAU4niav4VTmHeKrz3QBxe3noRJTW2cjIAQ1oHY/Wxayir5ffyDG0djHtj/TD7z0ucx0lc4DvMPEAbTucJyruDrlG+eHtQHAauPMkr0ycuACeulmPnRdsVDSYet2N8mU9lJHMIv6Fys6XB8UE4cqUUR7LKLCS+fLg1VEo5vjueg5/O2g8vBmk9eCfah8y8SEKGk6uEhBjPZW8c++nJtvBR2ykn4KADlW8KNm8mKCgQQIldGb4kWOtu5TQwrGS4jBnrr8kJ3OdivaKZLw6wLl3Bh+lamhPspcK3oxJQrdOjWYAn5/fGdQpHVkkNAGM1Xi6ooXKL4yaPmFOW+ueff47PP/8c1To9ymv18NMoLVyKu3btAgDoDQwuFVquwe/duzcOHz7M/l1Zp8fh1GwLmbvvvhv//POPxWdFRUVOr+dvSMy7ryCfbKLmq8FgGuUWDGiOF3+7wPv957o1QVM/DYbfFYLvjueQqmrBx0NbIvHGG098iBapBbZLq0kqXTpCswANMotrRG3TmkWD49BZYAv6+BAt5DIZXrovmtdQ6dfEvsfB/ArW8VxP8z2n+FYHmX9TKZfhjX6xGPbtaQsZucw4qUzoHIGtyQWo5TmfXGasNPrmjst2dQfA24ZYpKenIyEhwa4MX50REw5ryHe7mjV0NTubR+gmpBM41+msdeYaX61XY5KE+UmGaZJ22oZ74f5YfyTlVWAejyfEGr5rKbQi0tNDgbeF8lBkMpj3mq9aYfflylkk5Yt/7733IJPJMGPGDPYzhmGwYMECREZGwtPTE71798a5c+csvldbW4tp06YhODgYXl5eGD58OLKtbuji4mKMGzcOfn5+8PPzw7hx41BilV9x5coVDBs2DF5eXggODsb06dOdTgAVdAe6MIeIVRLZ00OBUG8Vb9xTLrtZh4TPi+BOz5D5ucTMdzFBklEPADqBN7Y2oV54qgt3cuWjbUPR80ZMX8fzVmy6dewZoYlmblm+N0gxo49qhQyfDW+FBQO4B8fxPG9cjuCjVqBLU19B49s0QNuTGtTUvqHSPfrmKgwS70SfuEDOva2sb0Oue8j0e9RKOfrE2W4QBwCbx7fDuicS0SbUi3NTzlsRR38G31Yg5rklvLaM2ck6N/FF80BbL4GtEcLVjrCM9WdCW5gYv2Mp82hb292H7RWjNG/njX6x2DA6EXeFkW126E6i/DVQN8BbumQMlWPHjuHrr79Gu3aWCV4ffPABPv74YyxbtgzHjh1DeHg4BgwYgPLyclZmxowZ2Lx5MzZu3Ij9+/ejoqICQ4cOhV5/07IbM2YMTp06he3bt2P79u04deoUxo0bxx7X6/UYMmQIKisrsX//fmzcuBE///wzZs6c6dTvEUoYdOVtt4mfGoFaJaL9G3aprEwmQ5SfGhG+Kt5dih1JGvbwcK1Co+UOywRfcHCgbBIaTCTHt2zRHL6dpfu3CGQHLb5aDo7mN7nDUPnuibvg6aFAj2b+nPc26U7aJhY/2MLmM5KJrXWIln0T5Lv3BrYMREwUf9nw4QnBiDNbxVPDY6hYe0u+5MhXsFaZSyfzj3QG7nN5qRRsUq/1xnNc8OUMPN+tCUa1CxWsiyFEZOTNfJuhrcmeCyGE9tdRyGX4hCeh1kR4uHAulUIuwxcP86/0MsH9nFkKcUlYf0YyBlpPtFx1ZcyXXicKJDE74kk3v5ZiY61FQ6VmSsJQqaiowNixY7FixQoEBNwcBBmGwaeffoq5c+di5MiRSExMxJo1a1BVVYX169cDAEpLS/HNN99gyZIl6N+/Pzp27Ii1a9fi7NmzbAgjJSUF27dvx8qVK9G9e3d0794dK1aswLZt25CamgoA2LFjB5KTk7F27Vp07NgR/fv3x5IlS7BixQqUlZXZKm2HNiGeaM2xtMwcRzPizfFQGHdd1jg4OTiDUiGHj1rJO3mqlXJ43kgUjPC170p01QtirgPfW6e5mo5G8WN8ZER5HXwxXXON+DYrM7/ufCEHR9HzGSqitG5EZZbE58ExMlfWOebu7Rjp41CCqQnL3BIZZx4KA/tL4fs0tzS02vLV37CZ2Ehk7Oc01OiE78qhbYLRpan98Nes+7nrvzycGIpn7mmC3oQrq/g8Yeb993/dhPeK4VqxY31XLujPvwzcxF0c18K8Ha4VLIDtiwvXdbDOQ+Ua0oQSZTs38bEtumn19z1RtjVThL4DGFctzekTgwEtAzGT5/o6g5hlIYSQOzjqeBKOAZLIUZk6dSqGDBmC/v3745133mE/T09PR25uLgYOHMh+plar0atXLxw8eBDPPfccjh8/Dp1OZyETGRmJxMREHDx4EIMGDcKhQ4fg5+eHrl27sjLdunWDn58fDh48iPj4eBw6dAiJiYkW1uegQYNQW1uL48ePo0+fPsS/p+TsP8hor4FWq2XzMqy9CQYDg9raWhgMBsjlcnh4eKC2thYKGWCav3S1taiXGX+zTqeDwWCATCaDWq1GTY0xV0CpNO7QbHqATbIhnjKU1RkQ5KVmdbCWValU0Ov10Ov1kMlk0Gg0rKxCoYBCoWBvcnNZAPD09ERNTQ0YhkGYVgGZ3AP1ujpUV+ugUqlgMBjYkvkm2fr6ejAMA6VSidraWrZfGIZhZTUaDWpra8EwjEW/AFahHwMDhmFQV1dn0YfmEVO93sD+HvM+NKeurg46OQOdTofMzExMT/DG2yf4r21eXh7UajUmxSuxKtUyETYnJxdoEYjk5GQAwOvdA7HoUJHV9/NRm1cFhUKBEXc1w9aU6zbnSE09j5Yx0WB43r4BoKqqChkZGQCAWh23kXDx4kX+H3IDvV6PjIwMto/5uJB6HomtWyErKwslJeU2x/NKhJOQTf0SEhICpVJpcy3q9XqkpaWhefPmOH/+PGcbBr0B2dnZKCsrg1KpxNN3t8ImqyTgkpISpKfnQqvVorS0FKWlpRbHMzIz4K8PgJ+fH65cuQIA+GBAU7y60zJcfPXaNSRXX4Ovry8CAwNxMS3dRp+0S2lo2ikBly9fRl1dHecKi+vXr6O8uBAAUKPj9iomJycjLCwMDMMgPz8fXXwN+M9KRqfTsdc0NDQU/9c5CF8dL7RpR61WIyYmhvM8gHHvl4KCAlRUVOBubyV+1ShRapXUnZ6ejuvXryMmJgZFRUUI9ZQhv9rSGrh27Rp8fHyQlZUFOYyGnLnBwDAMUlNTodfr4evra/ESysWFCxc4t9mora1DXl4eCgsLcbWoHIDtC1FeXi6SFdcRERGB+vp6FBQU2MgE1hWirs6TrSsSFGIZfokJUKP6+lUkZ9dAo9EgOjoaaVbP0JjoWiQnJ6N58+bIy8tDZWUlVCpLfZ5N1KKkpATXrl0DAMTGxiLfKv/N9CwEBgZCq9WyqQr3NGuGlmoFSq9eQkWuAvHx8UhJSQHDMPD394evry97z0ZFRaG8vBwlJSWQyWRo06aNRX8HBgYiIyMD5eXlUKuN84CpnH6bNm2QlpYGnU4Hb29vhISEID3deH9HRkairq4O168bx6b4+Hh2jPDy8kJ4eDguXTIl8Fubo4xDocs3u/qgrqJUUK7RDZWNGzfixIkTOHbsmM2x3NxcAEBYmOVbU1hYGDIzM1kZlUpl8xCEhYWx38/NzUVoqG1MMDQ01ELG+jwBAQFQqVSsDClDhw5FTEwkCgsL4elp/vZtbtnKbCq1enp6oqmHAUVVOnipFNCavd1zyZpjvqJGrVZDrQY01dXwVCthfZnNZRUKS6+Mdbvmf1vLajSWy3k9lJay5saZyQgyPdTW57GW5dIh1MOAjBvJnGG+atZoM0cuk918UGQyeJotOWZlK24mnqpUKnh4KOHh4QEfHx+ENmsBnLDMgTLHdI88cZ8/VqVarkoJDze+nZoS11rUGwArQyUsLNQi7DC7dzO8vzfTQqZN69bw9FDcWM7NbaxotVr2PMypJE6Z+FatgP+4j5lQKBSIi7uRMHeQf5VN69at4eGhQPPmzeGflQkUWP6ugW3CsTPdtrCUOdYJfQpFFmAWnpXL5WjRosVNWQ595Ao5mjZtavc8fn5+8PHxgLe3N7y9vY27x5q11Tw2Fk1ueDwtdbI0VCIjI5Fg5hlr06Y1cNRyg824uDgLvY1YGg8hISGIijDeN7WXuJOszfUIDg5GdXYZkGy5msvDw8NCzqe40OZc5sdfvDcK/9ufZXMuT09PREffrDXSISsd+9JL2L9bh2jh46Nm29JqtVCpyoBqS2PW9FLH3odW14uBcZIjYWjrYLRqdWNJvlU7KpUKYWFhCAsLQ+Xpc7AcR42EhoUjIeHmGB8SEmLRztePtEbMDU+oSV+jJ/Jm/3w6LN5myXZ8q1bA8ZvPUNu7btZeadbMzOux9+a5opsY89PMd2Nv1iQCwM0J2fpZMP/by8vSG29dWdbiHvDxsXi5tu7vhIQEJCcns7mZpjEKAFq2bGkja475nMmOEVaysmOnYW6sPNkpAvP+ugTSuHubuBicPn1aUK5RQz9ZWVl48cUXsXbtWpvJyRxrN5l1BVUuuKqsiiFDAt8y3ACzhFS+BFa1Uo4IX7VgRj0J9vq0MXBVH5VSjpgADZoFaHhzIsx3qXY0qSs+Pt7utX5nkH3XtXXtD5JkvUQ7Zb9Jb7suPOW5HY0X2/t9Qs9AuwhvjO/c8NVZSV7WhCZI0m6xDs9yjg8E7Zg/6Y+2s31h4vwOSYKmwC95MD5IMITExdy+sTb950wY0UdNPoZNt1M3yPyad0q0zROyEeLAU2k7Xlh3MVftHrFyLkj2HGsoSI1FZzDvHn+NEh0iHb/fSGhUQ+X48ePIz89H586doVQqoVQqsW/fPnz22WdQKpXs26u1RyM/P589Fh4ejrq6OhQXF9uVycuzXXpaUFBgIWN9nuLiYuh0OhtPi7MEeXkgzEeFaH818QoTVxBy57sbMfRRKeV2qzOGeKmg8ZBDq5ITZdGbk5GRwftARPqqcE8UdwVOEz1jLI+TTGz2bgPSO+SZeyI5jTKhomnW3BPlx1uN07wl7pUQMqJS4o7AlcBNktvFMGDDYlyQTj5NfK28dTznEsTsfN2i/TC0jXByqhgTpEwmQ+sQ4cqy5gRpjWOUvf7jP5/l36/3jXG4DSEyMjLwSi/byrNCl4HznhX8QDxDxUulYHOhHic0VsXCmWvpDFy5OWLRqIZKv379cPbsWZw6dYr9r0uXLhg7dixOnTqF5s2bIzw8HDt37mS/U1dXh3379qFHjx4AgM6dO8PDw8NCJicnB0lJSaxM9+7dUVpaiqNHj7IyR44cQWlpqYVMUlIScnJu1rXYsWMH1Go1OnfuLMrvlcuMyZruSIIFGmYJryu4Qx+FXIZofw2a+mmICjGZU1tbyzswRfraX2G1bES8zQaIBLmX9t+KCdX31Sg5991QOVHFkm8vI3csQ7fuG66qqKQeFXtGMYmHtFdzf4sQnfF7tnJ8VWQtvmf2b7lMhsGthA0661tXaMM9sbHuP0e9yr1i/dFKYOsCUkLNNtmrra3FgJaOG8R8xrU5XF4sMSuMvzc4Dl+MiMckgpL7YtKQL6zmGyCSLERwlkbNUfHx8UFiYqLFZ15eXggKCmI/nzFjBhYtWoSWLVuiZcuWWLRoEbRaLcaMGQPAGI9++umnMXPmTAQFBSEwMBCzZs1C27Zt0b9/fwDGGN/gwYMxefJkLF++HADw7LPPYujQoaxbbODAgUhISMC4cePw4YcfoqioCLNmzcLkyZPh69twlmJDImbJ+mHDhiExMRHvvfeeJPRxhPfffx9//PGHTRE6a7y8vMiWPXPgyeHlIVklwjUOktRlsMamWqZMvHo7xhOI1xRfk9ZGCJdxyFfPxxwvD4VNnN/eebkY18k2jGU9ac26PxreBOEN2xUfBApYafmmSGXqSdux138kBPDsWu0M5jVH+PQSmiRJVqOQLEXmI8pPjazSWs6NBE2olHLBfacaAlevpT3m9InBi79dgNZDgTE3ltWTFCNUymW8taY45Z3W0E28+uqrqK6uxpQpU1BcXIyuXbtix44d8PG5GQv75JNPoFQqMWrUKFRXV6Nfv3749ttvLZI/161bh+nTp7Org4YPH87uQQMYkwp///13TJkyBT179oSnpyfGjBmDjz76yH0/VmRcrVsiNlLTB7A0JsLDw1FWT1Z+2xqSNzaAK+/B8viEzhFQCVTW5NqXx/pcXz7c2qmqxXyQvFn6a5Ro5q9BZolz1WtJbMRpPYX3QBrfORyecv4VU0R1LwjCAN2i7YcCxTw/V86aM5eXdCdj86RLLl7rLd7yWXssfqCFRaVZLr2Uchn6teAupMfC01fhPirkltch3EfFU6yPTM8PHmyJg+mFuC9O3PCnGAhdS1doFuCJDWMS4aGQs6Fmoeq0vZv7Y9b9zaBSyi1qndlDcobK3r17Lf6WyWRYsGABFixYwPsdjUaDpUuXYunSpbwygYGBWLt2rd1zR0dHY9u2bY6oK2lqa2ttVtc0JlLTB7AMvVy6dAlt2rRB80ANLhc5NtmSFvCL8LH0Elh/6wkzI4Svzac4XMfWkrEclTmtaR5IntxM8utkMhmWDG2Ji9er8O3xHIuy/qMI4vJclV/NGdsx3Kb/rHmlVzT8PT2QnJxssYphdu9m+GBfJiJ81Ij2F/7dJG/XJAZHbIDGZjsN6+vKVaXUGSOEK3fLWVv10qVLvCX0FTLhgpZiRXmt9efS67PhrQRz/vhq9rzRLxYHMkrwQDy3gUGa5xXk5YE4eRH8PRvOKHAWe9dSDKwXNrzauxne+It/GwiFXCb4MmaNJAq+UaRFZWUlnn/+eURFRaFNmzYWnifAmCc0f/583HXXXWjatCn69++P/fv3s8fXr1+PmJgY/PXXX7jnnnvQpEkTTJgwAVVVVdiwYQPat2+P2NhYvPbaaxYW9Q8//IC+ffsiOjoarVu3xuTJky3qIezfvx+BgYHYt28f+vbtiyZNmmDQoEE29UI+/fRTxMfHIzo6GtOmTbMbo7Ueh2QyGT4d7niWPMl49kqvaJs3Y9sCUw6fGoBzE5LgPh5857KaaGfefzO50VejROemvjbhq7EE1Vbf6Bdj9zhJcSgtT/5X3xaB+GFsWywf2doml4gLLm8USdEuaz4Y0lIw9PNsV9uCas7kRvxvGNlu2c5Qb1bzpktTX7ftDk8CiSp8qwRbBWvxVJdIhPMYwJ4eCtbIaUZg4FKMSflv2tmHyJl7hxoqtzHOhlrmz5+Pf//9F9999x1+/vlnHDhwwGKt+wsvvIAjR45g5cqV+Pfff/HQQw/hscceMysCZCwqtXz5cqxcuRI//vgjDhw4gMmTJ2Pnzp3YtGkTvvrqK6xZswa//vor+526ujrMmTMH//zzD77//ntkZmZi6tSpNvq98847ePvtt7F7924olUpMmzaNPbZ582a8//77mDt3Lnbv3o3w8HB88803vL/VfBIxuUhJNzWzbEhYhCRUYLFc3oHTO/Pwh3iRL5m01/wgjuRQc/n4EC3nRGEu072Zn03yqitwubt9NUriNzkiDxKBDFfuBNEmdgRtW9M8yNaL5qw5Yd1/lXU3DRXrWiMmzPO7xFrUaO0p4bqufPf+/Tdq4Ah5f4RY+lA8RrULFQx3NWSIxRUaQ68ALX+wxpl7Q3Khn9sBvjetqVvOo7jKtvJiQ8GAgQwyBGiV+HwET/0BKyoqKrB27Vp88cUXbDXeL774gk1uTk9Px88//4ykpCRERBiToaZNm4a///4b69evx7x58wAYq2guWbIEsbFGy3r48OHYtGkTUlNT4e3tjdatW+Pee+/F/v37MXLkSADAk08+yeoRExOD999/H/3790dFRYVFxc833ngDPXv2BGBMtn788cdRU2OsJvnVV19h7NixGD9+PABg7ty52Lt3r4VXxU+jQGmN0ZPjYeaXt66U6gjOTmx2H1oRBvsvH47H85tTieX5Tsm3PJmkVg1JGIBvtZGjmE7lyrUEyN7SnXUqkHhiiM7v3OltMO8pUw6Vdf9VmW2R4EWwapHPmHEU65CNI9d1dp8YPNK2Ci04DDhHiPLX4Jl7hLcRcPWeayikppczL1XUUBGBCZ0j8PUx4eq1xVX1uF7FvVeFVMjIyEBdXR3uuece9rOAgAC28ubp06fBMIzFccCYf2JeHVir1bJGCnCjOmdUlIXBERoaypZpBoAzZ85g8eLFOHv2LEpKStgHLDs7G61b3zS07jKrDmmqcXP9+nU0bdoUFy5cwFNPPWWh2913320Rmgr2UkGjrIfGQ2Hx0OTn5yM4mLvGBddcO71nFD47kIUoPzVRQSeScILFMcEWb8Jn8DjqpeCzKfj0dOsSeAc2orR3LUkgyTlyNlmZ5I2SZOUX0V5RBO0UVt4ck/xveICs++/B1sH4NdkYhu0aLbwK0suJfZy4sA7lcV1Xvr5SymVoI7Dnmpi4es81FI2hl73nhyR/zhpqqIjAw4mhOJ1bhSNZxs0L24RyTw723GENgamqriPnFZp4DAYDFAoF/v77b5uS+ubL4Kyr88pkMs7PTMZIZWUlHnnkEfTp0wfLly9HUFAQsrOz8eijj9psRGYe0jJNFo68NSjkMvg5WAyOiyGtg9Ax0gdBXh6ElUTJPnMGV3bjbggsNoeUWD0fEmrqhVcjOJ1PRCDT1Cwf4m6eysNlNcLeWa4NJK0Z0CoQyfmVAICH7uJOeh7fORz1BgNCvVXoyhPCDPbywPUbRk+knzg7u5N42jQiGUUU8eAbDoO0HkQFD62hhopIzLw/Gt8ez0Ezfw3ieapBkoZfxMK0WZ8jxMbGwsPDA8eOHWP3VCkpKcGlS5fQo0cPtGvXDnq9HtevX0f37t0datueLhcvXkRhYSHefPNN9rynTp1yqH0AaNWqFf777z888cQT7Gf//We9vRs31ntfCCGTydDEgQGZqwCdPfumRZAWBZWlhLoQq2G/HY7PEsPt1CThObG32QRTbmepIguBMeOAQ8XhawkYK9FeLTOGCPm2sHihR1MsO5iN+2L9eQvq/W94K/x0Nh+DWnEvmSXxxGiUcrz/QBz2XirBw4khnDJ9WwRg1X/XYGD4E5ETwm5eu5bB3G+yA1oEIq+8DmqlHINv6Gzdfz5qJV6817YirDnz+8di/s7LaBGkRXceY8ZDLoPOqliR9XL7V3pF49N/s3B/c3+b68B1Xe1VqnYnztxz7qAx9OK6w4e2Cca0Hk2d8kRSQ0Uk/D09MEPgQXY3Op3OZtM+Iby9vfHkk09i/vz5CAwMREhICN59913WyGjRogUee+wxPP/883j77bfRrl07FBYW4t9//0VCQgIGDBjA27Y9b03Tpk2hUqmwYsUKPPXUU0hJSXGqhs1zzz2HqVOnokOHDujWrRt+/PFHnD9/3u5usiaysrLQvLlxv5snO4Zj7cmb4Txn356f6hKB1f/loFMTH84kXXsP7fSeUTh0hdBQsXPstd7N8PWRqwj28sDF69VE7Znz3uAWFn+b/w6+4k6+ZoXQymu53/zNXfY6kjAGAaYcC/NrScq7g+Ow5ngOOkT68G6/MDwhBP1aBPIudwWANqFemGdn1QPpON2piS86NeEPswR7qfDlw61RXK1DR549VtqGe2PEXSE4k1PBa2iolHKbaqnO9F98iBc2jE60e09/8GALfPjPFXRp6oORiaFIu16Fbs0sjZoBLYNwf2wApwHCpZdTye8NgDN95g4aQy/rW+Cvpzu4VNeJGiq3Mc4mUS1cuBCVlZUYO3YsvL29MWXKFJSVlbHHly1bho8++gjz5s1DTk4OAgMDcffdd9s1UgD7hkpwcDA+//xzvP322/j666/Rrl07vPXWW2wFYlJGjhyJjIwMLFy4ELW1tRg2bBgmTZqEv//+W/C7NTU3a6c80T4Mh66U4lKhcWJ/KIH7rVaI0R3CMbhVEO8bur0hNsjLAx0ivXHqWoXgeezVkejXIhB94wJwMLMUC3elC7ZljfWEQbJMeGibYOy4aNxhmS8RMVDrgZIb4Qu+3K0+cQHYc8m4j5fQNgbATe+N+bUkJdJXjTl9YgTlXE38dabyMB+xgZ6Ihf2Y/5Tu9neb5sKZ/gOEvUV3hXvj21E3a3rwXVM+LwmXXqJWYHYBZ/usoWkMvaxD0a4Wn6SGym2MsyXrvb298dVXX1l8Nn36dPbfHh4emDNnDubMmcP5/TFjxtgYGLNnz8ZLL71k8dnnn39u8fcjjzyCRx55xOKzoqIi9t/33nuvxd8A0LZtW5vPXn75Zbz88ssWn9krGGjCvBidSinHkiEt8cOZPITZicuTYK+cuFChKmvbjqs4GACLEFQ3jmRHmUyGmICbeQ+9mvvbPa89SFZ0tA71wpv9Y1FUpcNAnhDIM/dE4vXtxiXtfHVWRtwVgkuF1WgVorXZ9NGEp4cc1TpLo1xqhQXNacg9UcRCqv1n0kujlKOm3njNxazA7ApS7zO3IvIlkf4TQ3EaqZWsl5o+1phyY0xoVQpM7NKwG4gp5DK80KMp9lwqxjMcFWeHJ4TgdI7Ro/JUlwiM7sA9oasUcnz5cDwOZJRiME+VzSZ+Gszp0wx5FXUY1sY5DxEAJIbdXLnVPYp/W3ehcu1dmvrizX6xqNMb0KkJdzttQr2w8tE2dtt5/4EWmLXtIvw9leh7o2aG9bWUElLJqbCHVPvPpNcnw1piy7kC4dL5bkTqfeZOxDYdqaFyGyO1kvVS08eaixcvNmipaT6GJ4RgOE9o6d4YP4xqrkRYeDiGCGTLxwVpBZcj94lzfWBPCPPCM3dH4nJRNXoFVLrU1r03inK5QptQL/zwZFt4KGRsgmtjXUtSJrdW4kS5Jx7h8ZA1NlLtP5NecUFazLzfPfsNkSL1PnMnzQI0UClkqNMzvF5gR6CGCoUiYWQyGXqEK5DgZI6Mo5AWYxp1Y6VGcnJyQ6pDjFgF49zFXYEKPHZvC2FBCuUWRKWQY/nINrhwvQo9mjkfNjdBDZXbGOu6JY2N1PSxJjRUmm+37tQrwNOxa0T7zDmofs4hVb0A6erWWHo18VM7VL7BHtIPllKcRipJZiakpo81UtXPnXrFhzhWyZb2mXNQ/ZxDqnoB0tVNqno5AjVUGhC3lhfnwLqia2MjNX3MYRgGeXl5ja0GJ+7Uq4mfBuM6kW9iRvvMOah+ziFVvQDp6iZVvRyBGioNiIeHB8rKyhrdYKHwwzAMysrKJL8iyZ0MbS29/UooFMqdi7STBm5x/Pz8UFVVhcLCQgDud8Hp9XpUVVW59Zz2kJo+JgNSq9VCq9VCo9EIfKNxiIuLc+v5zPdOEar54W7dSJGqXiaofs4hVb0A6eomVb0cgRoqDYxpEmwMMjIyiErHuwup6WNNTk6OJPVzt16eHgq82qsZjlwpxbhOEXZlaZ85B9XPOaSqFyBd3aSqlyPQ0I8L1NbWWvxfStTW1mLp0qWS0U1q+lgjVf0aS6/+LQMxt18sogP4vUy0z5yD6uccUtULkK5uUtXLBOkcSg0VF6irq7P4v5Sora3F6tWrJXODSk0fa6Sqn1T1AqSrm1T1MkH1cw6p6gVIVzep6mWCdA6lhkoDsHLlyltKxp26fPfdd247150q405dSJBS39yKMlLShcrcWtfzVhxvuaCGSgMgtQtPH5w7S6axB5WGOtedKiMlXajMrXU9b8XxlguaTOsCplUjBoMBer2e/Vyj0Vj8zUVDyxgMBmi1WhgMBsF23KGvSR8p9A2XjHl/WX+nMXXm0ksK15NPt8bUxyQjpFdj34PW+knleppkpNp/fHo19vW01k1q11PoGW3s8Q0QrjkmY2iRD6cpLS3Ff//919hqUCgUCoVyy9KlSxf4+fHvCUQNFRcwGAyoq6uDQqG4LcoUUygUCoXiLhiGgV6vh0qlglzOn4lCDRUKhUKhUCiShSbTUigUCoVCkSzUUKFQKBQKhSJZqKFCoVAoFApFslBD5Q5CJpNhy5Ytja0GhdIo0PufQrk1oYYKDxMnTsSIESMaWw0bJk6cCJlMZvNfWlpao+nyf//3fzbHpkyZAplMhokTJ7pdLy4OHjwIhUKBwYMHN6oet1KfSfUZMCFF/aRyn1mTn5+P5557DtHR0VCr1QgPD8egQYNw6NChxlYNAJCVlYWnn34akZGRUKlUaNasGV588UV253kh9u7dC5lMhpKSEtF0Mj2r77//vsXnW7ZsadRVnuZzgIeHB8LCwjBgwACsWrWKrUtyu0ENlVuQwYMHIycnx+K/2NjYRtElKioKGzduRHV1NftZTU0NNmzYgOjoaJfa1ul0rqrHsmrVKkybNg379+/HlStXXGrLVCDOWRqyzyiNi5j3mZg88sgjOH36NNasWYMLFy7gt99+Q+/evVFUVNTYquHy5cvo0qULLly4gA0bNiAtLQ1fffUVdu/eje7duzeqjhqNBosXL0ZxcXGj6cCFaQ7IyMjAn3/+iT59+uDFF1/E0KFDUV9f39jqiQ41VAjYvn077r33Xvj7+yMoKAhDhw7FpUuX2OMZGRmQyWT45Zdf0KdPH2i1WrRv377B3lZMb0Tm/ykUCmzduhWdO3eGRqNB8+bNsXDhQpubNicnBw888AA8PT0RGxuLH3/80SVdOnXqhOjoaPzyyy/sZ7/88guioqLQsWNH9jPSPvzhhx/Qu3dvaDQarF271iXdTFRWVuKHH37A888/j6FDh+Lbb79lj5nexH7//Xe0b98eGo0GXbt2xdmzZ1mZb7/9Fv7+/ti2bRsSEhKgVquRmZnptD5i9Vnfvn3xwgsvWLRdWFgItVqNv//+22n9uIiJicGnn35q8VmHDh2wYMEC9m+ZTIaVK1fi4YcfhlarRcuWLfHbb7+Jqocr+jU09u4z0z1kDteb+TvvvIPQ0FD4+PjgmWeewezZs9GhQweX9CopKcH+/fuxePFi9OnTB82aNcM999yDOXPmYMiQIQCMxSufffZZhIaGwtfXF3379sXp06fZNhYsWIAOHTpg+fLliIqKglarxWOPPSaKB2Pq1KlQqVTYsWMHevXqhejoaDzwwAPYtWsXrl69irlz5wIwbrD36quvIioqCmq1Gi1btsQ333yDjIwM9OnTBwAQEBAgqleyf//+CA8Px3vvvccr8/PPP+Ouu+6CWq1GTEwMlixZwh6bM2cOunXrZvOddu3aYf78+U7rZZoDmjRpgk6dOuH111/Hr7/+ij///JO974SuKQD89ttv6NKlCzQaDYKDgzFy5EindWpIqKFCQGVlJV5++WUcO3YMu3fvhlwux8MPP2zzVj137lzMmjULp06dQqtWrTB69Gi3Wbd//fUXnnzySUyfPh3JyclYvnw5vv32W7z77rsWcvPmzWPfrp588kmMHj0aKSkpLp37qaeewurVq9m/V61ahUmTJlnIkPbha6+9hunTpyMlJQWDBg1ySS8TmzZtQnx8POLj4/Hkk09i9erVNiWbX3nlFXz00Uc4duwYQkNDMXz4cAuPTlVVFd577z2sXLkS586dQ2hoqEs6idFnzzzzDNavX2+xM+q6desQGRnJDtzuZuHChRg1ahTOnDmDBx98EGPHjpXEW7s7ILnP7LFu3Tq8++67WLx4MY4fP47o6Gh8+eWXLuvl7e0Nb29vbNmyhXMXXYZhMGTIEOTm5uKPP/7A8ePH0alTJ/Tr18/i2qWlpeGHH37A1q1bsX37dpw6dQpTp051SbeioiL89ddfmDJlCjw9PS2OhYeHY+zYsdi0aRMYhsH48eOxceNGfPbZZ0hJScFXX30Fb29vREVF4eeffwYApKamIicnB//73/9c0suEQqHAokWLsHTpUmRnZ9scP378OEaNGoUnnngCZ8+exYIFCzBv3jzWWBg7diyOHDli8YJx7tw5nD17FmPHjhVFRxN9+/ZF+/bt8csvvxBd099//x0jR47EkCFDcPLkSezevRtdunQRVSfRYCicTJgwgXnooYc4j+Xn5zMAmLNnzzIMwzDp6ekMAGblypWszLlz5xgATEpKiuh6KRQKxsvLi/3v0UcfZe677z5m0aJFFrLff/89ExERwf4NgPm///s/C5muXbsyzz//vNO6PPTQQ0xBQQGjVquZ9PR0JiMjg9FoNExBQQHz0EMPMRMmTOD8Ll8ffvrpp07pYo8ePXqw7ep0OiY4OJjZuXMnwzAMs2fPHgYAs3HjRla+sLCQ8fT0ZDZt2sQwDMOsXr2aAcCcOnXKZV3E7LOamhomMDCQ1ZNhGKZDhw7MggULXNbTXFeGYZhmzZoxn3zyicXx9u3bM/Pnz2f/BsC88cYb7N8VFRWMTCZj/vzzT1H0EUO/zZs3N4guDGP/Plu9ejXj5+dnIb9582bGfAju2rUrM3XqVAuZnj17Mu3bt3dZt59++okJCAhgNBoN06NHD2bOnDnM6dOnGYZhmN27dzO+vr5MTU2NxXfi4uKY5cuXMwzDMPPnz2cUCgWTlZXFHv/zzz8ZuVzO5OTkOK3X4cOH7V6Xjz/+mAHAHDlyhAHA9qc1pue4uLjYaV2sMb+/unXrxkyaNIlhGMvrNmbMGGbAgAEW33vllVeYhIQE9u927doxb731Fvv3nDlzmLvvvlsUvax5/PHHmTZt2hBd0+7duzNjx451Wg93Qj0qBFy6dAljxoxB8+bN4evry+aDWMeg27Vrx/47IiICgDGJTWz69OmDU6dOsf999tlnOH78ON566y327cnb2xuTJ09GTk4Oqqqq2O92797doq3u3bu77FEJDg7GkCFDsGbNGqxevRpDhgxBcHCwhQxpH4pt0aempuLo0aN44oknAABKpRKPP/44Vq1aZSFn3i+BgYGIj4+36BeVSmVxfV1FjD5Tq9V48skn2d9y6tQpnD59ulGTcc37yMvLCz4+Pg3yDEgN0vtMqI177rnH4jPrv53lkUcewbVr1/Dbb79h0KBB2Lt3Lzp16oRvv/0Wx48fR0VFBYKCgizGj/T0dAtPQHR0NJo2bcr+3b17dxgMBqSmpoqiIxfMDY9Ueno6FAoFevXq1WDnssfixYuxZs0aJCcnW3yekpKCnj17WnzWs2dPXLx4kd18b+zYsVi3bh0A4+/ZsGGD6N4UEwzDQCaTEV3TU6dOoV+/fg2ih9jQ3ZMJGDZsGKKiorBixQpERkbCYDAgMTERdXV1FnIeHh7sv02x54bIwvby8kKLFi0sPjMYDFi4cCFnjFGj0dhtT4wM9kmTJrH5Ep9//rnNcdI+9PLyclkXc7755hvU19ejSZMm7GcMw8DDw0MwQc68Xzw9PUXP9Bejz5555hl06NAB2dnZWLVqFfr164dmzZqJqicAyOVymzAGV7Kz+TMAGPvQHSsRSPVrKITuM1L9rO8x6++4gkajwYABAzBgwAC8+eabeOaZZzB//nxMmTIFERER2Lt3r813rPNquHR15blo0aIFZDIZkpOTOVdwnT9/HgEBAdBqtU6fQwzuv/9+DBo0CK+//rrFi4DJMDDH+pqNGTMGs2fPxokTJ1BdXY2srCzWoBWblJQUxMbGwmAwCF5T61CblKGGigCFhYVISUnB8uXLcd999wEA9u/f38ha2dKpUyekpqbaGDDWHD58GOPHj7f42zyB01kGDx7MTqDWuSWN1Yf19fX47rvvsGTJEgwcONDi2COPPIJ169YhMTERgLEfTCtuiouLceHCBbRu3bpB9ROjz9q2bYsuXbpgxYoVWL9+PZYuXdoguoaEhCAnJ4f9u6ysDOnp6Q1yLmdoTP1I7rO4uDiUl5ejsrKSNcZPnTplIRsfH4+jR49i3Lhx7GcNuTt7QkICtmzZgk6dOiE3NxdKpRIxMTG88leuXMG1a9cQGRkJADh06BDkcjlatWrltA5BQUEYMGAAvvjiC7z00ksWk2dubi7WrVuH8ePHo23btjAYDNi3bx/69+9v045KpQIA1ovRELz//vvo0KGDxe9NSEiweS4PHjyIVq1aQaFQAACaNm2K+++/H+vWrUN1dTX69++PsLAw0fX7+++/cfbsWbz00kto2rSp4DVt164ddu/ejaeeekp0XcSGGioCBAQEICgoCF9//TUiIiJw5coVzJ49u7HVsuHNN9/E0KFDERUVhcceewxyuRxnzpzB2bNn8c4777ByP/74I7p06YJ7770X69atw9GjR/HNN9+4fH6FQsGGSkwPqInG6sNt27ahuLgYTz/9tM0W4o8++ii++eYbfPLJJwCAt956C0FBQQgLC8PcuXMRHBzc4DU6xOqzZ555Bi+88AK0Wi0efvjhBtG1b9+++PbbbzFs2DAEBARg3rx5Njo3Jo2pH8l9tnv3bmi1Wrz++uuYNm0ajh49arEqCACmTZuGyZMno0uXLujRowc2bdqEM2fOoHnz5i7pV1hYiMceewyTJk1Cu3bt4OPjg//++w8ffPABHnroIfTv3x/du3fHiBEjsHjxYsTHx+PatWv4448/MGLECDYcq9FoMGHCBHz00UcoKyvD9OnTMWrUKISHh7uk37Jly9CjRw8MGjQI77zzDmJjY3Hu3Dm88soraNKkCd59910EBgZiwoQJmDRpEj777DO0b98emZmZyM/Px6hRo9CsWTPIZDJs27YNDz74IDw9PeHt7e2SXta0bdsWY8eOtXgZmDlzJu6++268/fbbePzxx3Ho0CEsW7YMX3zxhcV3x44diwULFqCuro4dc1yhtrYWubm50Ov1yMvLw/bt2/Hee+9h6NChGD9+PORyueA1nT9/Pvr164e4uDg88cQTqK+vx59//olXX33VZf1Ep5FyYyTPuHHjmEceeYRhGIbZuXMn06ZNG0atVjPt2rVj9u7da5EAZkoEPXnyJPv94uJiBgCzZ88eUfWyl0i1fft2pkePHoynpyfj6+vL3HPPPczXX3/NHgfAfP7558yAAQMYtVrNNGvWjNmwYUOD6MIwjEViqDN96CpDhw5lHnzwQc5jx48fZwAwS5YsYQAwW7duZe666y5GpVIxd999t0XiLFcipLOI2WcmysvLGa1Wy0yZMkUUHU2YPwOlpaXMqFGjGF9fXyYqKor59ttviZJV/fz8mNWrV4uql5j6iQHJfXb8+HFm8+bNTIsWLRiNRsMMHTqU+frrrxnrIfitt95igoODGW9vb2bSpEnM9OnTmW7durmkX01NDTN79mymU6dOjJ+fH6PVapn4+HjmjTfeYKqqqhiGYZiysjJm2rRpTGRkJOPh4cFERUUxY8eOZa5cucIwjDGZtn379swXX3zBREZGMhqNhhk5ciRTVFTkkm4mMjIymIkTJzLh4eHs+adNm8Zcv36dlamurmZeeuklJiIiglGpVEyLFi2YVatWscffeustJjw8nJHJZLwJ6Y7A9axmZGQwarXa4rr99NNPTEJCAuPh4cFER0czH374oU1bxcXFjFqtZrRaLVNeXu6yXgAYAIxSqWRCQkKY/v37M6tWrWL0ej0rJ3RNGYZhfv75Z6ZDhw6MSqVigoODmZEjR7qkW0MhYxgRg6C3EYMHD0aLFi2wbNmyxlaF0oDs3bsXffr0QXFxsd14vJTJyspCTEwMjh07hk6dOonWrtSfAanrJwYDBgxAeHg4vv/++0bVY8GCBdiyZYtNuIpCcQc09GNFcXExDh48iL1793KWOadQpIJOp0NOTg5mz56Nbt26iWakSP0ZkLp+zlJVVYWvvvoKgwYNgkKhwIYNG7Br1y7s3LmzsVWjUBoVaqhYMWnSJBw7dgwzZ87EQw891NjqUCi8HDhwAH369EGrVq3w008/idau1J8BqevnLDKZDH/88Qfeeecd1NbWIj4+Hj///DNn8iiFcidBQz8UCoVCoVAkCy34RqFQKBQKRbJQQ4VCoVAoFIpkuaMNlffeew933303fHx8EBoaihEjRtiUg2YYBgsWLEBkZCQ8PT3Ru3dvnDt3zkLm66+/Ru/eveHr6wuZTMa5o2hMTAxkMpnFf1Ksx0KhUCgUipS4ow2Vffv2YerUqTh8+DB27tyJ+vp6DBw4EJWVlazMBx98gI8//hjLli3DsWPHEB4ejgEDBqC8vJyVqaqqwuDBg/H666/bPd9bb72FnJwc9r833nijwX4bhUKhUCi3AzSZ1oyCggKEhoZi3759uP/++8EwDCIjIzFjxgy89tprAIwVAcPCwrB48WI899xzFt+3V5MjJiYGM2bMwIwZM9z0aygUCoVCufW5oz0q1pSWlgIw7p4LGHfszM3Ntdi/Q61Wo1evXjh48KDD7S9evBhBQUHo0KED3n33XZsN+SgUCoVCoVhC66jcgGEYvPzyy7j33nvZjepyc3MBwGYDqbCwMGRmZjrU/osvvohOnTohICAAR48exZw5c5Ceno6VK1eK8wMoFAqFQrkNoYbKDV544QWcOXOGc4darm28Hd3a/KWXXmL/3a5dOwQEBODRRx9lvSwUCoVCoVBsoaEfGHct/e2337Bnzx40bdqU/dy0K6jJs2IiPz/f5W26u3XrBgBIS0tzqR0KhUKhUG5n7mhDhWEYvPDCC/jll1/w999/IzY21uJ4bGwswsPDLfbaqKurw759+9CjRw+Xzn3y5EkAQEREhEvtUCgUCoVyO3NHh36mTp2K9evX49dff4WPjw/rOfHz84OnpydkMhlmzJiBRYsWoWXLlmjZsiUWLVoErVaLMWPGsO3k5uYiNzeX9Y6cPXsWPj4+iI6ORmBgIA4dOoTDhw+jT58+8PPzw7Fjx/DSSy9h+PDhiI6ObpTfTqFQKBTKrcAdvTyZL89k9erVmDhxIgCj12XhwoVYvnw5iouL0bVrV3z++edswi1g3AJ94cKFvO2cOHECU6ZMwfnz51FbW4tmzZrhiSeewKuvvgqtVtsgv41CoVAolNuBO9pQoVAoFAqFIm3u6BwVCoVCoVAo0oYaKhQKhUKhUCQLNVQoFAqFQqFIFmqoUCgUCoVCkSzUUKFQKBQKhSJZqKFCoVAoFApFslBDhUKhUCgUimShhgqFQqFQKBTJQg0VCoVCucHEiRPh7e0tapuLFi3Cli1bRG2TQrmToIYKhUKhNCDUUKFQXIMaKhQKhUKhUCQLNVQoFIpoFBQU4Nlnn0VUVBTUajVCQkLQs2dP7Nq1CwDQu3dvJCYm4tixY7jvvvug1WrRvHlzvP/++zAYDGw7NTU1mDlzJjp06AA/Pz8EBgaie/fu+PXXX23OKZPJ8MILL2D58uVo1aoV1Go1EhISsHHjRgu5qqoqzJo1C7GxsdBoNAgMDESXLl2wYcMGmzbT0tLw4IMPwtvbG1FRUZg5cyZqa2stZIqKijBlyhQ0adIEKpUKzZs3x9y5cy3kZDIZKisrsWbNGshkMshkMvTu3duVLqZQ7jiUja0AhUK5fRg3bhxOnDiBd999F61atUJJSQlOnDiBwsJCViY3Nxdjx47FzJkzMX/+fGzevBlz5sxBZGQkxo8fDwCora1FUVERZs2ahSZNmqCurg67du3CyJEjsXr1albOxG+//YY9e/bgrbfegpeXF7744guMHj0aSqUSjz76KADg5Zdfxvfff4933nkHHTt2RGVlJZKSkix0AwCdTofhw4fj6aefxsyZM/HPP//g7bffhp+fH958800ARkOqT58+uHTpEhYuXIh27drh33//xXvvvYdTp07h999/BwAcOnQIffv2RZ8+fTBv3jwAgK+vb8N0PoVyu8JQKBSKSHh7ezMzZszgPd6rVy8GAHPkyBGLzxMSEphBgwbxfq++vp7R6XTM008/zXTs2NHiGADG09OTyc3NtZBv3bo106JFC/azxMREZsSIEXb1nzBhAgOA+eGHHyw+f/DBB5n4+Hj276+++opTbvHixQwAZseOHexnXl5ezIQJE+yel0Kh8ENDPxQKRTTuuecefPvtt3jnnXdw+PBh6HQ6G5nw8HDcc889Fp+1a9cOmZmZFp/9+OOP6NmzJ7y9vaFUKuHh4YFvvvkGKSkpNm3269cPYWFh7N8KhQKPP/440tLSkJ2dzer2559/Yvbs2di7dy+qq6s5f4NMJsOwYcPs6vf333/Dy8uL9daYmDhxIgBg9+7dnG1TKBTHoYYKhUIRjU2bNmHChAlYuXIlunfvjsDAQIwfPx65ubmsTFBQkM331Gq1heHwyy+/YNSoUWjSpAnWrl2LQ4cO4dixY5g0aRJqampsvh8eHs77mSm089lnn+G1117Dli1b0KdPHwQGBmLEiBG4ePGixfe0Wi00Go2NfubnLSwsRHh4OGQymYVcaGgolEqlTTiJQqE4DzVUKBSKaAQHB+PTTz9FRkYGMjMz8d577+GXX35hPQ2krF27FrGxsdi0aRNGjBiBbt26oUuXLjYJrSbMDSHrz0yGkZeXFxYuXIjz588jNzcXX375JQ4fPmzjPSEhKCgIeXl5YBjG4vP8/HzU19cjODjY4TYpFAo31FChUCgNQnR0NF544QUMGDAAJ06ccOi7MpkMKpXKwmORm5vLueoHMIZa8vLy2L/1ej02bdqEuLg4NG3a1EY+LCwMEydOxOjRo5GamoqqqiqH9OvXrx8qKips6qN899137HET1t4iCoXiGHTVD4VCEYXS0lL06dMHY8aMQevWreHj44Njx45h+/btGDlypENtDR06FL/88gumTJmCRx99FFlZWXj77bcRERFhE6oBjJ6cvn37Yt68eeyqn/Pnz1ssUe7atSuGDh2Kdu3aISAgACkpKfj+++/RvXt3aLVah/QbP348Pv/8c0yYMAEZGRlo27Yt9u/fj0WLFuHBBx9E//79Wdm2bdti79692Lp1KyIiIuDj44P4+HiHzkeh3MlQQ4VCoYiCRqNB165d8f333yMjIwM6nQ7R0dF47bXX8OqrrzrU1lNPPYX8/Hx89dVXWLVqFZo3b47Zs2cjOzsbCxcutJEfPnw47rrrLrzxxhu4cuUK4uLisG7dOjz++OOsTN++ffHbb7/hk08+QVVVFZo0aYLx48dj7ty5Tv3WPXv2YO7cufjwww9RUFCAJk2aYNasWZg/f76F7P/+9z9MnToVTzzxBKqqqtCrVy/s3bvX4XNSKHcqMsY6yEqhUCi3EDKZDFOnTsWyZcsaWxUKhdIA0BwVCoVCoVAokoUaKhQKhUKhUCQLzVGhUCi3NDR6TaHc3lCPCoVCoVAoFMlCDRUKhUKhUCiShRoqFAqFQqFQJAs1VCgUCoVCoUgWaqhQKBQKhUKRLNRQoVAoFAqFIlmooUKhUCgUCkWyUEOFQqFQKBSKZPl/zbRjLNMI2qkAAAAASUVORK5CYII=",
+      "text/plain": [
+       "<Figure size 600x200 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
    "source": [
     "n.loads_t.p_set.plot(figsize=(6, 2), ylabel=\"MW\")"
    ]
@@ -513,7 +785,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 23,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -538,7 +810,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 24,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -565,9 +837,30 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
+   "execution_count": 25,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<Axes: xlabel='snapshot', ylabel='CF'>"
+      ]
+     },
+     "execution_count": 25,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 600x200 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
    "source": [
     "n.generators_t.p_max_pu.loc[\"2015-03\"].plot(figsize=(6, 2), ylabel=\"CF\")"
    ]
@@ -588,9 +881,66 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
+   "execution_count": 26,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "INFO:linopy.model: Solve linear problem using Highs solver\n",
+      "INFO:linopy.io: Writing time: 0.11s\n",
+      "INFO:linopy.solvers:Log file at /tmp/highs.log.\n",
+      "INFO:linopy.constants: Optimization successful: \n",
+      "Status: ok\n",
+      "Termination condition: optimal\n",
+      "Solution: 8764 primals, 19714 duals\n",
+      "Objective: 2.97e+10\n",
+      "Solver model: available\n",
+      "Solver message: optimal\n",
+      "\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Running HiGHS 1.5.3 [date: 2023-05-16, git hash: 594fa5a9d-dirty]\n",
+      "Copyright (c) 2023 HiGHS under MIT licence terms\n",
+      "Presolving model\n",
+      "9900 rows, 7714 cols, 23130 nonzeros\n",
+      "9900 rows, 7714 cols, 23130 nonzeros\n",
+      "Presolve : Reductions: rows 9900(-9814); columns 7714(-1050); elements 23130(-10864)\n",
+      "Solving the presolved LP\n",
+      "Using EKK dual simplex solver - serial\n",
+      "  Iteration        Objective     Infeasibilities num(sum)\n",
+      "          0     0.0000000000e+00 Pr: 2190(1.18969e+09) 0s\n",
+      "       7503     2.9707818396e+10 Pr: 0(0) 0s\n",
+      "Solving the original LP from the solution after postsolve\n",
+      "Model   status      : Optimal\n",
+      "Simplex   iterations: 7503\n",
+      "Objective value     :  2.9707818396e+10\n",
+      "HiGHS run time      :          0.18\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "INFO:pypsa.optimization.optimize:The shadow-prices of the constraints Generator-ext-p-lower, Generator-ext-p-upper were not assigned to the network.\n"
+     ]
+    },
+    {
+     "data": {
+      "text/plain": [
+       "('ok', 'optimal')"
+      ]
+     },
+     "execution_count": 26,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
    "source": [
     "n.optimize(solver_name=\"highs\")"
    ]
@@ -611,9 +961,20 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
+   "execution_count": 27,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "29.70781839594502"
+      ]
+     },
+     "execution_count": 27,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
    "source": [
     "n.objective / 1e9"
    ]
@@ -627,9 +988,25 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
+   "execution_count": 28,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "Generator\n",
+       "OCGT       70.032006\n",
+       "onwind     -0.000000\n",
+       "offwind    54.515679\n",
+       "solar      88.042846\n",
+       "Name: p_nom_opt, dtype: float64"
+      ]
+     },
+     "execution_count": 28,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
    "source": [
     "n.generators.p_nom_opt.div(1e3)  # GW"
    ]
@@ -643,9 +1020,25 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
+   "execution_count": 29,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "Generator\n",
+       "OCGT       220.726908\n",
+       "onwind       0.000000\n",
+       "offwind    163.375462\n",
+       "solar       94.823370\n",
+       "Name: generators, dtype: float64"
+      ]
+     },
+     "execution_count": 29,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
    "source": [
     "n.snapshot_weightings.generators @ n.generators_t.p.div(1e6)  # TWh"
    ]
@@ -654,54 +1047,32 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "While we get the objective value through `n.objective`, in many cases we want to know how the costs are distributed across the technologies"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "opex = n.snapshot_weightings.generators @ (\n",
-    "    n.generators_t.p * n.generators.marginal_cost\n",
-    ").div(\n",
-    "    1e6\n",
-    ")  # M€/a"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "capex = (n.generators.p_nom_opt * n.generators.capital_cost).div(1e6)  # M€/a"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "capex + opex"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "If you have the newest version of PyPSA installed, you can also run the following to determine the total system cost by technology:"
+    "While we get the objective value through `n.objective`, in many cases we want to know how the costs are distributed across the technologies. We can use the statistics module for this:"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "(n.statistics.capex() + n.statistics.opex(aggregate_time=\"sum\")).div(1e6)"
+   "execution_count": 35,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "           carrier\n",
+       "Generator  OCGT       16990.065781\n",
+       "           offwind     8622.248279\n",
+       "           onwind         0.000000\n",
+       "           solar       4095.504337\n",
+       "dtype: float64"
+      ]
+     },
+     "execution_count": 35,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "(n.statistics.capex() + n.statistics.opex()).div(1e6)"
    ]
   },
   {
@@ -713,7 +1084,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 36,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -726,9 +1097,20 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
+   "execution_count": 37,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "106.59494598003647"
+      ]
+     },
+     "execution_count": 37,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
    "source": [
     "n.snapshot_weightings.generators @ emissions.sum(axis=1).div(1e6)  # Mt"
    ]
@@ -749,7 +1131,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 38,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -797,9 +1179,20 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
+   "execution_count": 39,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 600x300 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
    "source": [
     "plot_dispatch(n)"
    ]
@@ -829,7 +1222,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 40,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -857,7 +1250,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 41,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -890,31 +1283,127 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 42,
    "metadata": {
     "tags": [
      "hide-output"
     ]
    },
-   "outputs": [],
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "INFO:linopy.model: Solve linear problem using Highs solver\n",
+      "INFO:linopy.io:Writing objective.\n",
+      "Writing constraints.: 100%|\u001b[38;2;128;191;255m██████████\u001b[0m| 14/14 [00:00<00:00, 62.48it/s]\n",
+      "Writing continuous variables.: 100%|\u001b[38;2;128;191;255m██████████\u001b[0m| 7/7 [00:00<00:00, 185.53it/s]\n",
+      "INFO:linopy.io: Writing time: 0.28s\n",
+      "INFO:linopy.solvers:Log file at /tmp/highs.log.\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Running HiGHS 1.5.3 [date: 2023-05-16, git hash: 594fa5a9d-dirty]\n",
+      "Copyright (c) 2023 HiGHS under MIT licence terms\n",
+      "Presolving model\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "INFO:linopy.constants: Optimization successful: \n",
+      "Status: ok\n",
+      "Termination condition: optimal\n",
+      "Solution: 21906 primals, 50376 duals\n",
+      "Objective: 2.97e+10\n",
+      "Solver model: available\n",
+      "Solver message: optimal\n",
+      "\n",
+      "INFO:pypsa.optimization.optimize:The shadow-prices of the constraints Generator-ext-p-lower, Generator-ext-p-upper, StorageUnit-ext-p_dispatch-lower, StorageUnit-ext-p_dispatch-upper, StorageUnit-ext-p_store-lower, StorageUnit-ext-p_store-upper, StorageUnit-ext-state_of_charge-lower, StorageUnit-ext-state_of_charge-upper, StorageUnit-energy_balance were not assigned to the network.\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "27420 rows, 20856 cols, 75690 nonzeros\n",
+      "27420 rows, 20856 cols, 75690 nonzeros\n",
+      "Presolve : Reductions: rows 27420(-22956); columns 20856(-1050); elements 75690(-24006)\n",
+      "Solving the presolved LP\n",
+      "Using EKK dual simplex solver - serial\n",
+      "  Iteration        Objective     Infeasibilities num(sum)\n",
+      "          0     0.0000000000e+00 Pr: 2190(1.43191e+09) 0s\n",
+      "      27008     2.9707818396e+10 Pr: 0(0); Du: 0(2.72262e-12) 2s\n",
+      "Solving the original LP from the solution after postsolve\n",
+      "Model   status      : Optimal\n",
+      "Simplex   iterations: 27008\n",
+      "Objective value     :  2.9707818396e+10\n",
+      "HiGHS run time      :          2.64\n"
+     ]
+    },
+    {
+     "data": {
+      "text/plain": [
+       "('ok', 'optimal')"
+      ]
+     },
+     "execution_count": 42,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
    "source": [
     "n.optimize(solver_name=\"highs\")"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
+   "execution_count": 43,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "Generator\n",
+       "OCGT       70032.005583\n",
+       "onwind        -0.000000\n",
+       "offwind    54515.678802\n",
+       "solar      88042.845735\n",
+       "Name: p_nom_opt, dtype: float64"
+      ]
+     },
+     "execution_count": 43,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
    "source": [
     "n.generators.p_nom_opt  # MW"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
+   "execution_count": 44,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "StorageUnit\n",
+       "battery storage                -0.0\n",
+       "hydrogen storage underground   -0.0\n",
+       "Name: p_nom_opt, dtype: float64"
+      ]
+     },
+     "execution_count": 44,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
    "source": [
     "n.storage_units.p_nom_opt  # MW"
    ]
@@ -942,7 +1431,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 45,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -964,13 +1453,75 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 46,
    "metadata": {
     "tags": [
      "hide-output"
     ]
    },
-   "outputs": [],
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "INFO:linopy.model: Solve linear problem using Highs solver\n",
+      "INFO:linopy.io:Writing objective.\n",
+      "Writing constraints.: 100%|\u001b[38;2;128;191;255m██████████\u001b[0m| 15/15 [00:00<00:00, 64.67it/s]\n",
+      "Writing continuous variables.: 100%|\u001b[38;2;128;191;255m██████████\u001b[0m| 7/7 [00:00<00:00, 199.03it/s]\n",
+      "INFO:linopy.io: Writing time: 0.29s\n",
+      "INFO:linopy.solvers:Log file at /tmp/highs.log.\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Running HiGHS 1.5.3 [date: 2023-05-16, git hash: 594fa5a9d-dirty]\n",
+      "Copyright (c) 2023 HiGHS under MIT licence terms\n",
+      "Presolving model\n",
+      "25230 rows, 18665 cols, 69120 nonzeros\n",
+      "25230 rows, 18665 cols, 69120 nonzeros\n",
+      "Presolve : Reductions: rows 25230(-25147); columns 18665(-3241); elements 69120(-32766)\n",
+      "Solving the presolved LP\n",
+      "Using EKK dual simplex solver - serial\n",
+      "  Iteration        Objective     Infeasibilities num(sum)\n",
+      "          0     0.0000000000e+00 Pr: 2190(1.32502e+09) 0s\n",
+      "      12614     1.7259174995e+10 Pr: 5117(8.18071e+12); Du: 0(4.93933e-09) 5s\n",
+      "      23432     6.5542941965e+10 Pr: 0(0); Du: 0(1.42457e-07) 10s\n",
+      "      23432     6.5542206026e+10 Pr: 0(0) 10s\n",
+      "Solving the original LP from the solution after postsolve\n",
+      "Model   status      : Optimal\n",
+      "Simplex   iterations: 23432\n",
+      "Objective value     :  6.5542206026e+10\n",
+      "HiGHS run time      :         10.51\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "INFO:linopy.constants: Optimization successful: \n",
+      "Status: ok\n",
+      "Termination condition: optimal\n",
+      "Solution: 21906 primals, 50377 duals\n",
+      "Objective: 6.55e+10\n",
+      "Solver model: available\n",
+      "Solver message: optimal\n",
+      "\n",
+      "INFO:pypsa.optimization.optimize:The shadow-prices of the constraints Generator-ext-p-lower, Generator-ext-p-upper, StorageUnit-ext-p_dispatch-lower, StorageUnit-ext-p_dispatch-upper, StorageUnit-ext-p_store-lower, StorageUnit-ext-p_store-upper, StorageUnit-ext-state_of_charge-lower, StorageUnit-ext-state_of_charge-upper, StorageUnit-energy_balance were not assigned to the network.\n"
+     ]
+    },
+    {
+     "data": {
+      "text/plain": [
+       "('ok', 'optimal')"
+      ]
+     },
+     "execution_count": 46,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
    "source": [
     "n.optimize(solver_name=\"highs\")"
    ]
@@ -984,27 +1535,71 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
+   "execution_count": 47,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "Generator\n",
+       "OCGT           -0.000000\n",
+       "onwind     220958.961317\n",
+       "offwind     75825.717685\n",
+       "solar      251269.009694\n",
+       "Name: p_nom_opt, dtype: float64"
+      ]
+     },
+     "execution_count": 47,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
    "source": [
     "n.generators.p_nom_opt  # MW"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
+   "execution_count": 48,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "StorageUnit\n",
+       "battery storage                 35544.217482\n",
+       "hydrogen storage underground    61986.162254\n",
+       "Name: p_nom_opt, dtype: float64"
+      ]
+     },
+     "execution_count": 48,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
    "source": [
     "n.storage_units.p_nom_opt  # MW"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
+   "execution_count": 49,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "StorageUnit\n",
+       "battery storage                   213.265305\n",
+       "hydrogen storage underground    10413.675259\n",
+       "dtype: float64"
+      ]
+     },
+     "execution_count": 49,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
    "source": [
     "n.storage_units.p_nom_opt.div(1e3) * n.storage_units.max_hours  # GWh"
    ]
@@ -1018,9 +1613,30 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
+   "execution_count": 50,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/home/fneum/miniconda3/envs/esm-2023/lib/python3.11/site-packages/pandas/plotting/_matplotlib/core.py:1600: UserWarning:\n",
+      "\n",
+      "Attempting to set identical low and high ylims makes transformation singular; automatically expanding.\n",
+      "\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 600x300 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
    "source": [
     "plot_dispatch(n)"
    ]
@@ -1034,20 +1650,38 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 52,
    "metadata": {},
    "outputs": [],
    "source": [
     "def system_cost(n):\n",
-    "    tsc = n.statistics.capex() + n.statistics.opex(aggregate_time=\"sum\")\n",
+    "    tsc = n.statistics.capex() + n.statistics.opex()\n",
     "    return tsc.droplevel(0).div(1e6)  # million €/a"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
+   "execution_count": 53,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "carrier\n",
+       "OCGT                                0.000000\n",
+       "offwind                         11992.773707\n",
+       "onwind                          21315.499152\n",
+       "solar                           11688.315828\n",
+       "battery storage                  3427.563054\n",
+       "hydrogen storage underground    17118.054285\n",
+       "dtype: float64"
+      ]
+     },
+     "execution_count": 53,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
    "source": [
     "system_cost(n)"
    ]
@@ -1061,9 +1695,30 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
+   "execution_count": 54,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<Axes: >"
+      ]
+     },
+     "execution_count": 54,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 200x200 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
    "source": [
     "system_cost(n).plot.pie(figsize=(2, 2))"
    ]
@@ -1077,7 +1732,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 55,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -1086,9 +1741,20 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
+   "execution_count": 56,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "136.8525442506265"
+      ]
+     },
+     "execution_count": 56,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
    "source": [
     "system_cost(n).sum() * 1e6 / demand.sum()"
    ]
@@ -1124,13 +1790,276 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 57,
    "metadata": {
     "tags": [
      "hide-output"
     ]
    },
-   "outputs": [],
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "INFO:linopy.model: Solve linear problem using Highs solver\n",
+      "INFO:linopy.io:Writing objective.\n",
+      "Writing constraints.: 100%|\u001b[38;2;128;191;255m██████████\u001b[0m| 15/15 [00:00<00:00, 66.28it/s]\n",
+      "Writing continuous variables.: 100%|\u001b[38;2;128;191;255m██████████\u001b[0m| 7/7 [00:00<00:00, 189.51it/s]\n",
+      "INFO:linopy.io: Writing time: 0.28s\n",
+      "INFO:linopy.solvers:Log file at /tmp/highs.log.\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Running HiGHS 1.5.3 [date: 2023-05-16, git hash: 594fa5a9d-dirty]\n",
+      "Copyright (c) 2023 HiGHS under MIT licence terms\n",
+      "Presolving model\n",
+      "27421 rows, 20856 cols, 77880 nonzeros\n",
+      "27421 rows, 20856 cols, 77880 nonzeros\n",
+      "Presolve : Reductions: rows 27421(-22956); columns 20856(-1050); elements 77880(-24006)\n",
+      "Solving the presolved LP\n",
+      "Using EKK dual simplex solver - serial\n",
+      "  Iteration        Objective     Infeasibilities num(sum)\n",
+      "          0     0.0000000000e+00 Pr: 2190(1.43191e+09) 0s\n",
+      "      26541     2.9707818396e+10 Pr: 0(0); Du: 0(4.94637e-12) 3s\n",
+      "Solving the original LP from the solution after postsolve\n",
+      "Model   status      : Optimal\n",
+      "Simplex   iterations: 26541\n",
+      "Objective value     :  2.9707818396e+10\n",
+      "HiGHS run time      :          3.30\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "INFO:linopy.constants: Optimization successful: \n",
+      "Status: ok\n",
+      "Termination condition: optimal\n",
+      "Solution: 21906 primals, 50377 duals\n",
+      "Objective: 2.97e+10\n",
+      "Solver model: available\n",
+      "Solver message: optimal\n",
+      "\n",
+      "INFO:pypsa.optimization.optimize:The shadow-prices of the constraints Generator-ext-p-lower, Generator-ext-p-upper, StorageUnit-ext-p_dispatch-lower, StorageUnit-ext-p_dispatch-upper, StorageUnit-ext-p_store-lower, StorageUnit-ext-p_store-upper, StorageUnit-ext-state_of_charge-lower, StorageUnit-ext-state_of_charge-upper, StorageUnit-energy_balance were not assigned to the network.\n",
+      "INFO:linopy.model: Solve linear problem using Highs solver\n",
+      "INFO:linopy.io:Writing objective.\n",
+      "Writing constraints.: 100%|\u001b[38;2;128;191;255m██████████\u001b[0m| 15/15 [00:00<00:00, 63.91it/s]\n",
+      "Writing continuous variables.: 100%|\u001b[38;2;128;191;255m██████████\u001b[0m| 7/7 [00:00<00:00, 197.08it/s]\n",
+      "INFO:linopy.io: Writing time: 0.29s\n",
+      "INFO:linopy.solvers:Log file at /tmp/highs.log.\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Running HiGHS 1.5.3 [date: 2023-05-16, git hash: 594fa5a9d-dirty]\n",
+      "Copyright (c) 2023 HiGHS under MIT licence terms\n",
+      "Presolving model\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "INFO:linopy.constants: Optimization successful: \n",
+      "Status: ok\n",
+      "Termination condition: optimal\n",
+      "Solution: 21906 primals, 50377 duals\n",
+      "Objective: 2.97e+10\n",
+      "Solver model: available\n",
+      "Solver message: optimal\n",
+      "\n",
+      "INFO:pypsa.optimization.optimize:The shadow-prices of the constraints Generator-ext-p-lower, Generator-ext-p-upper, StorageUnit-ext-p_dispatch-lower, StorageUnit-ext-p_dispatch-upper, StorageUnit-ext-p_store-lower, StorageUnit-ext-p_store-upper, StorageUnit-ext-state_of_charge-lower, StorageUnit-ext-state_of_charge-upper, StorageUnit-energy_balance were not assigned to the network.\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "27421 rows, 20856 cols, 77880 nonzeros\n",
+      "27421 rows, 20856 cols, 77880 nonzeros\n",
+      "Presolve : Reductions: rows 27421(-22956); columns 20856(-1050); elements 77880(-24006)\n",
+      "Solving the presolved LP\n",
+      "Using EKK dual simplex solver - serial\n",
+      "  Iteration        Objective     Infeasibilities num(sum)\n",
+      "          0     0.0000000000e+00 Pr: 2190(1.43191e+09) 0s\n",
+      "      18518     2.4986536222e+10 Pr: 3772(3.48346e+10); Du: 0(6.39834e-07) 5s\n",
+      "      29608     2.9749883211e+10 Pr: 0(0); Du: 0(1.18556e-11) 9s\n",
+      "      29608     2.9749883211e+10 Pr: 0(0); Du: 0(1.18556e-11) 9s\n",
+      "Solving the original LP from the solution after postsolve\n",
+      "Model   status      : Optimal\n",
+      "Simplex   iterations: 29608\n",
+      "Objective value     :  2.9749883211e+10\n",
+      "HiGHS run time      :          9.78\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "INFO:linopy.model: Solve linear problem using Highs solver\n",
+      "INFO:linopy.io:Writing objective.\n",
+      "Writing constraints.: 100%|\u001b[38;2;128;191;255m██████████\u001b[0m| 15/15 [00:00<00:00, 60.01it/s]\n",
+      "Writing continuous variables.: 100%|\u001b[38;2;128;191;255m██████████\u001b[0m| 7/7 [00:00<00:00, 179.04it/s]\n",
+      "INFO:linopy.io: Writing time: 0.31s\n",
+      "INFO:linopy.solvers:Log file at /tmp/highs.log.\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Running HiGHS 1.5.3 [date: 2023-05-16, git hash: 594fa5a9d-dirty]\n",
+      "Copyright (c) 2023 HiGHS under MIT licence terms\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "INFO:linopy.constants: Optimization successful: \n",
+      "Status: ok\n",
+      "Termination condition: optimal\n",
+      "Solution: 21906 primals, 50377 duals\n",
+      "Objective: 3.31e+10\n",
+      "Solver model: available\n",
+      "Solver message: optimal\n",
+      "\n",
+      "INFO:pypsa.optimization.optimize:The shadow-prices of the constraints Generator-ext-p-lower, Generator-ext-p-upper, StorageUnit-ext-p_dispatch-lower, StorageUnit-ext-p_dispatch-upper, StorageUnit-ext-p_store-lower, StorageUnit-ext-p_store-upper, StorageUnit-ext-state_of_charge-lower, StorageUnit-ext-state_of_charge-upper, StorageUnit-energy_balance were not assigned to the network.\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Presolving model\n",
+      "27421 rows, 20856 cols, 77880 nonzeros\n",
+      "27421 rows, 20856 cols, 77880 nonzeros\n",
+      "Presolve : Reductions: rows 27421(-22956); columns 20856(-1050); elements 77880(-24006)\n",
+      "Solving the presolved LP\n",
+      "Using EKK dual simplex solver - serial\n",
+      "  Iteration        Objective     Infeasibilities num(sum)\n",
+      "          0     0.0000000000e+00 Pr: 2190(1.43191e+09) 0s\n",
+      "      15207     2.7001678730e+10 Pr: 9870(1.50894e+12); Du: 0(3.9799e-07) 5s\n",
+      "      25155     3.2274581653e+10 Pr: 11386(5.01194e+11); Du: 0(2.78313e-07) 10s\n",
+      "      29126     3.3060429019e+10 Pr: 0(0); Du: 0(1.59872e-14) 12s\n",
+      "      29126     3.3060429019e+10 Pr: 0(0); Du: 0(1.59872e-14) 12s\n",
+      "Solving the original LP from the solution after postsolve\n",
+      "Model   status      : Optimal\n",
+      "Simplex   iterations: 29126\n",
+      "Objective value     :  3.3060429019e+10\n",
+      "HiGHS run time      :         12.70\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "INFO:linopy.model: Solve linear problem using Highs solver\n",
+      "INFO:linopy.io:Writing objective.\n",
+      "Writing constraints.: 100%|\u001b[38;2;128;191;255m██████████\u001b[0m| 15/15 [00:00<00:00, 61.10it/s]\n",
+      "Writing continuous variables.: 100%|\u001b[38;2;128;191;255m██████████\u001b[0m| 7/7 [00:00<00:00, 182.68it/s]\n",
+      "INFO:linopy.io: Writing time: 0.3s\n",
+      "INFO:linopy.solvers:Log file at /tmp/highs.log.\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Running HiGHS 1.5.3 [date: 2023-05-16, git hash: 594fa5a9d-dirty]\n",
+      "Copyright (c) 2023 HiGHS under MIT licence terms\n",
+      "Presolving model\n",
+      "27421 rows, 20856 cols, 77880 nonzeros\n",
+      "27421 rows, 20856 cols, 77880 nonzeros\n",
+      "Presolve : Reductions: rows 27421(-22956); columns 20856(-1050); elements 77880(-24006)\n",
+      "Solving the presolved LP\n",
+      "Using EKK dual simplex solver - serial\n",
+      "  Iteration        Objective     Infeasibilities num(sum)\n",
+      "          0     0.0000000000e+00 Pr: 2190(1.43191e+09) 0s\n",
+      "      11581     1.7610015451e+10 Pr: 10857(4.57502e+12); Du: 0(1.04598e-07) 5s\n",
+      "      17403     3.4368986057e+10 Pr: 14142(2.91956e+11); Du: 0(8.35077e-09) 10s\n",
+      "      22019     3.7999390616e+10 Pr: 0(0); Du: 0(2.887e-13) 14s\n",
+      "      22019     3.7999390616e+10 Pr: 0(0); Du: 0(2.887e-13) 14s\n",
+      "      22019     3.7999390616e+10 Pr: 0(0); Du: 0(2.887e-13) 14s\n",
+      "Solving the original LP from the solution after postsolve\n",
+      "Model   status      : Optimal\n",
+      "Simplex   iterations: 22019\n",
+      "Objective value     :  3.7999390616e+10\n",
+      "HiGHS run time      :         14.09\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "INFO:linopy.constants: Optimization successful: \n",
+      "Status: ok\n",
+      "Termination condition: optimal\n",
+      "Solution: 21906 primals, 50377 duals\n",
+      "Objective: 3.80e+10\n",
+      "Solver model: available\n",
+      "Solver message: optimal\n",
+      "\n",
+      "INFO:pypsa.optimization.optimize:The shadow-prices of the constraints Generator-ext-p-lower, Generator-ext-p-upper, StorageUnit-ext-p_dispatch-lower, StorageUnit-ext-p_dispatch-upper, StorageUnit-ext-p_store-lower, StorageUnit-ext-p_store-upper, StorageUnit-ext-state_of_charge-lower, StorageUnit-ext-state_of_charge-upper, StorageUnit-energy_balance were not assigned to the network.\n",
+      "INFO:linopy.model: Solve linear problem using Highs solver\n",
+      "INFO:linopy.io:Writing objective.\n",
+      "Writing constraints.: 100%|\u001b[38;2;128;191;255m██████████\u001b[0m| 15/15 [00:00<00:00, 63.65it/s]\n",
+      "Writing continuous variables.: 100%|\u001b[38;2;128;191;255m██████████\u001b[0m| 7/7 [00:00<00:00, 180.07it/s]\n",
+      "INFO:linopy.io: Writing time: 0.29s\n",
+      "INFO:linopy.solvers:Log file at /tmp/highs.log.\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Running HiGHS 1.5.3 [date: 2023-05-16, git hash: 594fa5a9d-dirty]\n",
+      "Copyright (c) 2023 HiGHS under MIT licence terms\n",
+      "Presolving model\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "INFO:linopy.constants: Optimization successful: \n",
+      "Status: ok\n",
+      "Termination condition: optimal\n",
+      "Solution: 21906 primals, 50377 duals\n",
+      "Objective: 6.55e+10\n",
+      "Solver model: available\n",
+      "Solver message: optimal\n",
+      "\n",
+      "INFO:pypsa.optimization.optimize:The shadow-prices of the constraints Generator-ext-p-lower, Generator-ext-p-upper, StorageUnit-ext-p_dispatch-lower, StorageUnit-ext-p_dispatch-upper, StorageUnit-ext-p_store-lower, StorageUnit-ext-p_store-upper, StorageUnit-ext-state_of_charge-lower, StorageUnit-ext-state_of_charge-upper, StorageUnit-energy_balance were not assigned to the network.\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "25230 rows, 18665 cols, 69120 nonzeros\n",
+      "25230 rows, 18665 cols, 69120 nonzeros\n",
+      "Presolve : Reductions: rows 25230(-25147); columns 18665(-3241); elements 69120(-32766)\n",
+      "Solving the presolved LP\n",
+      "Using EKK dual simplex solver - serial\n",
+      "  Iteration        Objective     Infeasibilities num(sum)\n",
+      "          0     0.0000000000e+00 Pr: 2190(1.32502e+09) 0s\n",
+      "      12614     1.7259174995e+10 Pr: 5117(8.18071e+12); Du: 0(4.93933e-09) 5s\n",
+      "      22631     6.5490521488e+10 Pr: 590(1.56337e+09); Du: 0(7.86181e-08) 10s\n",
+      "      23432     6.5542206026e+10 Pr: 0(0) 11s\n",
+      "Solving the original LP from the solution after postsolve\n",
+      "Model   status      : Optimal\n",
+      "Simplex   iterations: 23432\n",
+      "Objective value     :  6.5542206026e+10\n",
+      "HiGHS run time      :         11.23\n"
+     ]
+    }
+   ],
    "source": [
     "sensitivity = {}\n",
     "for co2 in [150, 100, 50, 25, 0]:\n",
@@ -1141,9 +2070,30 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
+   "execution_count": 58,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<matplotlib.legend.Legend at 0x7f96183439d0>"
+      ]
+     },
+     "execution_count": 58,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 400x400 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
    "source": [
     "df = pd.DataFrame(sensitivity).T.div(1e3)  # billion Euro/a\n",
     "df.plot.area(\n",
@@ -1258,9 +2208,9 @@
  ],
  "metadata": {
   "kernelspec": {
-   "display_name": "",
+   "display_name": "esm-2023",
    "language": "python",
-   "name": ""
+   "name": "python3"
   },
   "language_info": {
    "codemirror_mode": {