In a paper published in Nature Climate Change, we used a combination of a meteorological understanding of weather regimes and our Renewables.ninja wind and PV generation time series to show that by smart spatial deployment of future wind farms, based on our knowledge of weather regimes, it is possible to keep the European wind fleet’s multi-day variability to levels the power system is already dealing with today.

Together with Iain Staffell, I published two papers, available today, using reanalysis and satellite data to simulate PV and wind power plants across Europe (references at the bottom of this post). Alongside these two publications, we built a large database of measured power output data to validate the simulations and perform bias corrections. This now allows us to accurately model hypothetical European wind and PV power output over several decades, investigating issues like the impact of increasing PV deployment on net power demand:

Energy system models are used by analysts in academia, government and industry. They allow researchers to build internally coherent simulations and scenarios of the extraction, conversion, transportation and use of energy, either today or in the future, at scales ranging from cities to entire countries or continents. These models are particularly important because they can help with understanding and planning the transition from a fossil-fuel dominated energy system to one primarily consisting of clean and renewable energy.

Update 26 October 2015: The ipython-extensions repository has been updated with instructions for Jupyter/IPython 4.0, but for now, the CodeMirror customizations do not seem to work.

Update 4 March 2015: As of IPython 3.0, it seems that code in custom.js (such as the examples below) should be attached to the app_initialized.NotebookApp event (the ipython-extensions repository is updated accordingly):

$([IPython.events]).on("app_initialized.NotebookApp", function () {
    // your code here
});

Since I use the IPython notebook for a lot of explorative data analysis, I wanted some extra functionality to make day-to-day notebook work just a little bit more pleasant. I use several of Min RK’s excellent notebook extensions, particularly the floating table of contents and the Gist button.

We just published a paper in Nature Climate Change where we examine whether concentrating solar power (CSP) can provide the reliability we’re used to from conventional (fossil or nuclear) power plants. In other words, under what conditions can CSP plants provide baseload power, i.e. an essentially stable output of power over time similar to nuclear plants, and dispatchable power, i.e. power output that can be quickly called upon if needed to balance demand?