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Collecting Data from Oklahoma Wind Sites Ifa wind energy planti going to be built in Oklahoma, the most important factor to consideris obvious: location The purpose of this assignment is tocollectdata on the wind conditions at the Mesonet sites across Oklahoma and project whichsite has the reatest potentia for wind farm To ensure the quality of our choices for possible wind farmsites eacl must collect the accuratedata for which they are responsible To project wh ich site will be optimal for constructing wind farm, we will analyze average wind speeds over the course of one year for particular site By doing so, we will gain information on which sites seem to have more wind and therefore more energy. Ontop of this we will also begi to analyze correlations data and how we can know that two variables arelinked. To do this we will look the relationship between solar radiation and temperature, anduse linear regression to see how closely related they truly are. To collect data go to Mesonet website and download station monhtly summaries Here you can select the month year, and location anda corresponding table will appear Data Collection: Create table in Excel that contains the following (information that looks similar to the image below. Copy and paste this table three times to fill in data for each of the three sites that you've been assigned. Mesonet Site # Day Month w/Data Ave Wind Speed (mph) Days Ave Wind Speed January February March April May June July August September October November December Total Days with Data Sum Days Ave. Wind Average Monthly Air Average Daily Wind Speed When you select month, year, and site table similar to the following will appear: - Neacest NN Homman Courty Cleveland - MES AMC DEWT? NTM NSI - su - MAX HIN 20.19 Neetuly Inerages -> Terpezature 74* Degtee Daya 7378 Bainfall sech: Rainfall: Nonthly Total: 1.00* Dandity lighess; 100* Wind Speed ER: c.se 26 nand To determine the of days with data, count the number of NAs in the SPEED AVG column (highlighted and subtract it from the number of days in the month. Next record the average wind speed for the month (highlighted in purple) The two other boxed numbers will be important in thelater questions, but for now, ignore them. For the last column in the table, multiply the average wind speed for the month by the number of days that data was collected Toget rough estimate of how windy the site is sum up the last column and divide by the total days that data was present. Report your calculations in the table similar to the example figure on the first page. This assignment will require the examination of 36 files! The work must be completed in careful and diligent manner. want to spread data collection over couple of days to prevent making errors from being tired 2 Questions and Exercises: Submit both Word Document and an Excel Spreadsheet for this lab that answers the following 1 Set up single Excel Spreadsheet with formatted table for each of the assigned Mesonet sites. Collect the data and perform the calculations as described above. 2 Which if any, of your sites have months that lack more than three days? List the site number of missing days and month for each. How does missing data affect this lab? 3 Give an example of extra data that you could collect that would help in determining how windy a site is (For example you could collect dew temperature data but that won't have an affect on wind speeds... 4 Itis important to look for correlations, or trends in data. To determineit two variables influence one another we can construct linear plot comparing these two variables. The two variables we are interested here are the Average Temperature and the Average Solar Radiation (the teal and the green box on the monthly summaries, respectively). Pick one of your sites and for each month record these two numbers After you have made chart in excel with this data we are going to plot the two on a scatter plot Arrange your chart so that the independent variable the left column and the dependent variable the right Highlight both columns and click Insert Chart Scatter Right-click the data points and click Add Trend line Choose linear trend and display the R² 5. In the question above, do your R2values make sense? In two or three sentences explain why or why not. 3

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