{ "cells": [ { "cell_type": "markdown", "metadata": {}, "source": [ "# Problem 14.4" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "**Fundamentals of Solar Cells and Photovoltaic Systems Engineering**\n", "\n", "**Solutions Manual**\n", "\n", "**Problem 14.4**\n" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "**Determine the dominant frequencies for solar PV and wind power fluctuations by calculating the Fast Fourier Transform (FFT) of the solar PV and wind power time series corresponding to the country in Problem 14.3 and plotting the power spectra.**" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "We downloaded solar PV and wind time series for Spain from https://model.energy/ and saved it in the data folder." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "We will use the packages [pandas](https://pandas.org/), [numpy](https://numpy.org/), and [matplotlib.pyplot](https://matplotlib.org/stable/index.html) to plot the results" ] }, { "cell_type": "code", "execution_count": 1, "metadata": {}, "outputs": [], "source": [ "import pandas as pd\n", "import numpy as np\n", "import matplotlib.pyplot as plt\n", "import matplotlib.gridspec as gridspec" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "First, we retrieve the time series. " ] }, { "cell_type": "code", "execution_count": 2, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
\n", " | onwind | \n", "solar | \n", "
---|---|---|
2011-01-01 00:00:00 | \n", "0.021 | \n", "0.0 | \n", "
2011-01-01 01:00:00 | \n", "0.021 | \n", "0.0 | \n", "
2011-01-01 02:00:00 | \n", "0.020 | \n", "0.0 | \n", "
2011-01-01 03:00:00 | \n", "0.018 | \n", "0.0 | \n", "
2011-01-01 04:00:00 | \n", "0.016 | \n", "0.0 | \n", "