"Show the first 5 lines (header) of the German data:"
]
...
...
@@ -363,7 +454,11 @@
{
"cell_type": "code",
"execution_count": 20,
"metadata": {},
"metadata": {
"slideshow": {
"slide_type": "fragment"
}
},
"outputs": [
{
"data": {
...
...
@@ -453,7 +548,11 @@
},
{
"cell_type": "markdown",
"metadata": {},
"metadata": {
"slideshow": {
"slide_type": "fragment"
}
},
"source": [
"The wind, solar and load files are just differently organized datasets, its the same data:"
]
...
...
@@ -461,7 +560,11 @@
{
"cell_type": "code",
"execution_count": 21,
"metadata": {},
"metadata": {
"slideshow": {
"slide_type": "fragment"
}
},
"outputs": [
{
"data": {
...
...
@@ -480,7 +583,11 @@
},
{
"cell_type": "markdown",
"metadata": {},
"metadata": {
"slideshow": {
"slide_type": "slide"
}
},
"source": [
"***\n",
"**(a) Check that the wind and solar time series are normalized to ’per-unit of installed capacity’,\n",
...
...
@@ -491,7 +598,11 @@
{
"cell_type": "code",
"execution_count": 22,
"metadata": {},
"metadata": {
"slideshow": {
"slide_type": "fragment"
}
},
"outputs": [
{
"data": {
...
...
@@ -521,7 +632,11 @@
},
{
"cell_type": "markdown",
"metadata": {},
"metadata": {
"slideshow": {
"slide_type": "fragment"
}
},
"source": [
"Data set includes four years ranging from `2011-01-01` until `2014-12-31`."
]
...
...
@@ -529,7 +644,11 @@
{
"cell_type": "code",
"execution_count": 46,
"metadata": {},
"metadata": {
"slideshow": {
"slide_type": "subslide"
}
},
"outputs": [
{
"data": {
...
...
@@ -635,7 +754,10 @@
"cell_type": "code",
"execution_count": 47,
"metadata": {
"scrolled": true
"scrolled": true,
"slideshow": {
"slide_type": "subslide"
}
},
"outputs": [
{
...
...
@@ -658,7 +780,11 @@
},
{
"cell_type": "markdown",
"metadata": {},
"metadata": {
"slideshow": {
"slide_type": "fragment"
}
},
"source": [
"There are 35064 time slots: 8760h*4 + 24 (2012 was a leap year!)\n",
"\n",
...
...
@@ -671,7 +797,11 @@
},
{
"cell_type": "markdown",
"metadata": {},
"metadata": {
"slideshow": {
"slide_type": "slide"
}
},
"source": [
"***\n",
"** (c) For all three regions, plot the time series $W (t)$, $S(t)$, $L(t)$ for a winter month (January) and a summer month (July). **"
...
...
@@ -680,7 +810,11 @@
{
"cell_type": "code",
"execution_count": 27,
"metadata": {},
"metadata": {
"slideshow": {
"slide_type": "subslide"
}
},
"outputs": [
{
"data": {
...
...
@@ -707,7 +841,11 @@
{
"cell_type": "code",
"execution_count": 28,
"metadata": {},
"metadata": {
"slideshow": {
"slide_type": "subslide"
}
},
"outputs": [
{
"data": {
...
...
@@ -733,7 +871,11 @@
},
{
"cell_type": "markdown",
"metadata": {},
"metadata": {
"slideshow": {
"slide_type": "subslide"
}
},
"source": [
"Let's also compare the wind between the different regions"
]
...
...
@@ -741,7 +883,11 @@
{
"cell_type": "code",
"execution_count": 59,
"metadata": {},
"metadata": {
"slideshow": {
"slide_type": "fragment"
}
},
"outputs": [
{
"data": {
...
...
@@ -767,7 +913,11 @@
},
{
"cell_type": "markdown",
"metadata": {},
"metadata": {
"slideshow": {
"slide_type": "slide"
}
},
"source": [
"***\n",
"**(d) For all three regions, plot the duration curve for $W(t)$, $S(t)$, $L(t)$.** "
...
...
@@ -776,7 +926,11 @@
{
"cell_type": "code",
"execution_count": 63,
"metadata": {},
"metadata": {
"slideshow": {
"slide_type": "subslide"
}
},
"outputs": [
{
"data": {
...
...
@@ -810,14 +964,22 @@
},
{
"cell_type": "markdown",
"metadata": {},
"metadata": {
"slideshow": {
"slide_type": "skip"
}
},
"source": [
"> **Tip:** Go through the line `de['wind'].sort_values(ascending=False).reset_index(drop=True).plot()` dot by dot and note what happens to the output."
]
},
{
"cell_type": "markdown",
"metadata": {},
"metadata": {
"slideshow": {
"slide_type": "slide"
}
},
"source": [
"***\n",
"**(e) For all three regions, plot the probability density function of $W(t)$, $S(t)$, $L(t)$.**"
...
...
@@ -825,7 +987,11 @@
},
{
"cell_type": "markdown",
"metadata": {},
"metadata": {
"slideshow": {
"slide_type": "fragment"
}
},
"source": [
"There are two different methods:\n",
"1. [Histograms](https://en.wikipedia.org/wiki/Histogram) and \n",
...
...
@@ -836,7 +1002,11 @@
},
{
"cell_type": "markdown",
"metadata": {},
"metadata": {
"slideshow": {
"slide_type": "subslide"
}
},
"source": [
"First, let's look at the wind data:"
]
...
...
@@ -845,7 +1015,10 @@
"cell_type": "code",
"execution_count": 66,
"metadata": {
"scrolled": true
"scrolled": true,
"slideshow": {
"slide_type": "fragment"
}
},
"outputs": [
{
...
...
@@ -880,7 +1053,10 @@
{
"cell_type": "markdown",
"metadata": {
"scrolled": true
"scrolled": true,
"slideshow": {
"slide_type": "subslide"
}
},
"source": [
"Now, let's look at the solar data:"
...
...
@@ -890,7 +1066,10 @@
"cell_type": "code",
"execution_count": 70,
"metadata": {
"scrolled": true
"scrolled": true,
"slideshow": {
"slide_type": "fragment"
}
},
"outputs": [
{
...
...
@@ -924,7 +1103,11 @@
},
{
"cell_type": "markdown",
"metadata": {},
"metadata": {
"slideshow": {
"slide_type": "subslide"
}
},
"source": [
"Somewhat hard to see. Let's look at this in detail by limiting the y-axis shown to (0,2):"