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Commit 1e3ce703 authored by Fabian Neumann's avatar Fabian Neumann
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minor clarifications and updates in T5

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tutorial-3/notebooks/tutorial-3-task-2-solution.ipynb
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{
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"<matplotlib.axes._subplots.AxesSubplot at 0x7f6ee975a630>"
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},
"execution_count": 10,
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" Number of bounded subproblems: 0\n",
" Number of created subproblems: 0\n",
" Error rc: 0\n",
" Time: 3.998594045639038\n",
" Time: 3.898280382156372\n",
"# ----------------------------------------------------------\n",
"# Solution Information\n",
"# ----------------------------------------------------------\n",
......@@ -638,7 +638,7 @@
{
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"execution_count": 19,
......@@ -774,7 +774,7 @@
" Number of bounded subproblems: 0\n",
" Number of created subproblems: 0\n",
" Error rc: 0\n",
" Time: 8.340548753738403\n",
" Time: 7.731746435165405\n",
"# ----------------------------------------------------------\n",
"# Solution Information\n",
"# ----------------------------------------------------------\n",
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"execution_count": 26,
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},
{
"cell_type": "code",
"execution_count": 29,
"execution_count": 28,
"metadata": {
"slideshow": {
"slide_type": "fragment"
......@@ -1079,7 +1079,7 @@
"2012-01-01 04:00:00 0.0 0.641201"
]
},
"execution_count": 29,
"execution_count": 28,
"metadata": {},
"output_type": "execute_result"
}
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},
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"slide_type": "subslide"
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{
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"execution_count": 31,
"execution_count": 30,
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" dtype='datetime64[ns]', name='name', length=744, freq=None)"
]
},
"execution_count": 31,
"execution_count": 30,
"metadata": {},
"output_type": "execute_result"
}
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},
{
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"execution_count": 31,
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"slideshow": {
"slide_type": "subslide"
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"slide_type": "fragment"
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},
{
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......@@ -1279,7 +1279,7 @@
" Number of bounded subproblems: 0\n",
" Number of created subproblems: 0\n",
" Error rc: 0\n",
" Time: 8.114485740661621\n",
" Time: 8.02032470703125\n",
"# ----------------------------------------------------------\n",
"# Solution Information\n",
"# ----------------------------------------------------------\n",
......@@ -1294,7 +1294,7 @@
"('ok', 'optimal')"
]
},
"execution_count": 35,
"execution_count": 34,
"metadata": {},
"output_type": "execute_result"
}
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},
{
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"execution_count": 36,
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"525.895790860553"
]
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"execution_count": 36,
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{
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"execution_count": 37,
"execution_count": 36,
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"Name: p_nom_opt, dtype: float64"
]
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"execution_count": 37,
"execution_count": 36,
"metadata": {},
"output_type": "execute_result"
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"slideshow": {
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"Name: p_nom_opt, dtype: float64"
]
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"execution_count": 38,
"execution_count": 37,
"metadata": {},
"output_type": "execute_result"
}
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},
{
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"slideshow": {
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......@@ -1421,7 +1421,7 @@
"Name: e_nom_opt, dtype: float64"
]
},
"execution_count": 39,
"execution_count": 38,
"metadata": {},
"output_type": "execute_result"
}
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},
{
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"execution_count": 39,
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"execution_count": 40,
"execution_count": 39,
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"execution_count": 42,
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......@@ -1601,10 +1601,10 @@
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"execution_count": 45,
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{
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"execution_count": 46,
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tutorial-5/notebooks/tutorial-5-task-2-solution.ipynb
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......@@ -28,7 +28,7 @@
},
{
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"execution_count": 4,
"execution_count": 1,
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},
{
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"execution_count": 2,
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{
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{
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"<matplotlib.axes._subplots.AxesSubplot at 0x7f09f5771fd0>"
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"execution_count": 6,
"execution_count": 3,
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},
{
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"execution_count": 7,
"execution_count": 4,
"metadata": {
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......@@ -240,7 +240,7 @@
},
{
"cell_type": "code",
"execution_count": 8,
"execution_count": 5,
"metadata": {
"scrolled": true,
"slideshow": {
......@@ -289,7 +289,7 @@
" Number of bounded subproblems: 0\n",
" Number of created subproblems: 0\n",
" Error rc: 0\n",
" Time: 0.18898773193359375\n",
" Time: 0.1875760555267334\n",
"# ----------------------------------------------------------\n",
"# Solution Information\n",
"# ----------------------------------------------------------\n",
......@@ -304,7 +304,7 @@
"('ok', 'optimal')"
]
},
"execution_count": 8,
"execution_count": 5,
"metadata": {},
"output_type": "execute_result"
}
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},
{
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"execution_count": 9,
"execution_count": 6,
"metadata": {
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"14706.193806194"
]
},
"execution_count": 9,
"execution_count": 6,
"metadata": {},
"output_type": "execute_result"
}
......@@ -361,7 +361,7 @@
},
{
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"execution_count": 7,
"metadata": {
"slideshow": {
"slide_type": "fragment"
......@@ -377,7 +377,7 @@
"Name: p_nom_opt, dtype: float64"
]
},
"execution_count": 10,
"execution_count": 7,
"metadata": {},
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}
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},
{
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"execution_count": 11,
"execution_count": 8,
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"execution_count": 12,
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"execution_count": 13,
"execution_count": 10,
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"dtype: float64"
]
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"execution_count": 20,
"execution_count": 11,
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}
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},
{
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"dtype: int64"
]
},
"execution_count": 23,
"execution_count": 13,
"metadata": {},
"output_type": "execute_result"
}
......
tutorial-5/notebooks/tutorial-5-task-3-solution.ipynb
View file @ 1e3ce703
......@@ -75,8 +75,6 @@
"\n",
"* The marginal costs are illustrative, not accurate.\n",
"\n",
"* Only the first day of 2011 is in the github dataset, which is not representative. The full year of 2011 can be downloaded [here](http://www.pypsa.org/examples/scigrid-with-load-gen-trafos-2011.zip).\n",
"\n",
"* The ENTSO-E total load for Germany may not be scaled correctly; it is scaled up uniformly by factor 1.12 (a simplification of the methodology in Schumacher, Hirth (2015), which suggests monthly factors).\n",
"\n",
"* Biomass from the EEG Stammdaten are not read in at the moment.\n",
......@@ -98,7 +96,7 @@
},
{
"cell_type": "code",
"execution_count": 105,
"execution_count": 52,
"metadata": {
"slideshow": {
"slide_type": "skip"
......@@ -138,12 +136,12 @@
}
},
"source": [
"Some general settings (You may have to adjust this path to where you downloaded the network data!):"
"Some general settings:"
]
},
{
"cell_type": "code",
"execution_count": 106,
"execution_count": 53,
"metadata": {
"slideshow": {
"slide_type": "fragment"
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},
{
"cell_type": "code",
"execution_count": 107,
"execution_count": 54,
"metadata": {
"slideshow": {
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},
{
"cell_type": "code",
"execution_count": 108,
"execution_count": 55,
"metadata": {},
"outputs": [],
"source": [
......@@ -220,7 +218,7 @@
},
{
"cell_type": "code",
"execution_count": 137,
"execution_count": 56,
"metadata": {
"slideshow": {
"slide_type": "fragment"
......@@ -257,7 +255,7 @@
},
{
"cell_type": "code",
"execution_count": 110,
"execution_count": 57,
"metadata": {
"slideshow": {
"slide_type": "fragment"
......@@ -267,6 +265,7 @@
"source": [
"network.lines[\"s_nom_original\"] = network.lines.s_nom\n",
"\n",
"# extendable, but no reduction of line capacities\n",
"network.lines.s_nom_extendable = True\n",
"network.lines.s_nom_min = network.lines.s_nom\n",
"\n",
......@@ -286,7 +285,7 @@
},
{
"cell_type": "code",
"execution_count": 136,
"execution_count": 58,
"metadata": {
"slideshow": {
"slide_type": "fragment"
......@@ -306,7 +305,7 @@
},
"source": [
"***\n",
"## (a) Describe the nework as well as its regio