Sun is not always shining and wind is not always blowing. Thus, with increasing shares of renewable energy, its volatility becomes a concern. What is the best way to buffer this volatility? Is there an upper limit for renewables ?
In his paper "Buffering volatility: A study on the limits of Germany's energy revolution (2017)", Hans-Werner Sinn explores this questions, based on his own claculations, and draws some rather pessimistic conclusions.
His view was challenged soon after by research of A. Zerrahn et al: "On the economics of electrical storage for variable renewable energy sources (2018)", where Sinns calculations are reproduced, extended and finally an optimistic view is (re-)established.
This package provides interactive visualisations of some of A. Zerrahns findings. You can explore it online here: https://patchexplorer.shinyapps.io/revola_deploy/
The original paper is based on 2 spreadsheet tools and a numerical optimization model, all of which are open source and available online. To facilitate our visualisations, we provide a very fast R implementation of both spreadsheet tools based on Rcpp. The interacitve visualisation is done with the "shiny" package.