How much pollution reduction do we get from a MWh electricity produced by wind or solar power? In principle, this corresponds to the avoided pollution of a fossil fuel plant that reduces its output due to the higher production of renewable electricity. Which fossil fuel plant reduces its output and to which degree is not straightforward, however. It depends on the flexibility of the power plants, the predictability of the wind supply and possible network congestion.
Kevin Novan studies the pollution reduction of wind energy in his very interesting article “Valuing the Wind: Renewable Energy Policies and Air Pollution Avoided” (AEJ, Economic Policy 2015) using detailed time series data from Texas.
As part of her Master Thesis at Ulm University, Anna Sophie Barann has generated a nice RTutor problem set that allows you to replicate the main insights of the article in an interactive fashion. You learn about R, econometrics and the electricity sector at the same time.
Here is screenshoot:
Like in previous RTutor problem sets, you can enter free R code in a web based shiny app. The code will be automatically checked and you can get hints how to procceed. In addition you are challenged by many multiple choice quizzes.
To install the problem set the problem set locally, first install RTutor as explained here:
and then install the problem set package:
There is also an online version hosted by shinyapps.io that allows you explore the problem set without any local installation. (The online version is capped at 25 hours total usage time per month. So it may be greyed out when you click at it.)
If you want to learn more about RTutor, to try out other problem sets, or to create a problem set yourself, take a look at the RTutor Github page
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