In previous post, I described the particular dynamics in which electricity production from intermittent energy sources, when growing in capacity, will not increase much at the production valleys, but will steeply increase at the production peaks. This means that, when capacity increases, the needed backup capacity will stay high, even at multiples of the current capacity, but at the same time measures have to be taken to suppress the ever growing peaks.
I illustrated this with a (celebrated) record high of wind production on June 8, followed by a (neglected) low production (June 9). In less than 12 hours, the production fell from almost 3,000 MWh (capacity factor of 81%) to almost 20 MWh (capacity factor of 0.5%). This illustration was only for electricity production by wind energy. There is a complicating factor: solar is also an intermittent energy source and can intensify as well as dampen the effect of wind.
That made me wonder how this interaction would look like when capacity of solar and wind increases over time. In real-life, this is not witnessed yet, this is still to come. It is however possible to study the dynamics of such a system by modeling it.
A storm headed over our country at the end of last week. That inevitably means advocates of wind energy praising how wonderful wind energy is doing and how much electricity was produced by wind. That is exactly what happened and apparently we even have a new record…
It was Chris Derde (manager of energy provider Wase wind) who broke the news. He tweeted that wind energy had a “new record production of 3 GW” and that nuclear power plants lowered “their production by 0.5 GW”. This was one of the two images that accompanied the tweet, illustrating the record:
This is the wrap-up of the vehicle-to-grid series. In this post, I will go back to the article bringing the news that vehicle-to-grid networks increase longevity of electric car batteries. Now that I read the paper and have shed some light on several aspects, I re-read the article to find out whether the author was correctly representing that paper.
Unfortunately, this is not the case. It already starts with the title (translated from Dutch, my emphasis):
‘Energy storage in electric car extends the lifespan of the battery’
In the series of posts on the battery-life saving algorithm of the University of Warwick, I made (twice) the remark that the managers of vehicle-to-grid programs would not be very keen in implementing such an algorithm. This because this algorithm, although it is hailed as a break-though, will have a negative impact on the primary purpose of these schemes, therefor tolerating (some) battery damage might be the preferred option.
That made me wonder whether I could check this. The Warwick paper was published two years ago and the Smart Solar Charging program was presented as having developed its own bidirectional charging stations, so if there is some ability to make improvements based on this supposed break-through, then this project should be the one that will show it.
There are two findings in the battery-saving algorithm paper from the University of Warwick that I want to write about in this post. Both were mentioned only in passing in the paper. Although these findings are crucial information for those who want to implement such a system in the real world, these were not mentioned in the conclusion nor in the discussion nor in the list of things they want to improve upon.
These are the two findings:
The paper on the 10% increase of lithium-ion battery life as a result of operating in a vehicle-to-grid (see previous post) is an interesting read. I was initially fascinated by the validation of their battery degradation model, but the actual result came from the integration of that model in a smart grid algorithm. This algorithm was then used in a simulation of load balancing of a building by means of electric cars and resulted in the 10% increase of battery-life figure.
That number is therefor not obtained by measuring the battery degradation in reality, it is the outcome of a mathematical model. Personally, I don’t have a problem with models and this particular model seems to have potential (the battery degradation part is validated). Models are useful for sure, but that doesn’t mean they are necessarily right. It depends for example on the data that goes in the model and the assumptions that are made. It seems that this is where it went wrong in this simulation.
The data that was fed to the algorithm came among other things from an actual building (the International Digital Laboratory). This is the description of that building:
The International Digital Laboratory (IDL) is four story office building located on the University of Warwick campus near Coventry. The University is situated in the centre of England, adjacent to the city of Coventry and on the border with Warwickshire. The building compromises of a 100-seater auditorium, two electrical laboratories, a boardroom, 3 teaching laboratories, eight meeting rooms and houses approximately 360 researchers and administration staff.
That is not a small building and it draws quite some electricity (my emphasis):
In the previous post, I wrote about a report calculating the expected electricity price in a vehicle-to-grid system and the assumptions that went into it. One of the difficulties that was detailed in the report was the aging of the battery used in a vehicle-to-grid system. In the meanwhile, I read this 2017 article from the Dutch sustainability website wattisduurzaam.nl contradicting this. The author of the article writes that it is contra-intuitive, but that research from the University of Warwick revealed that a vehicle-to-grid system can even extend the lifetime of lithium-ion batteries…
I could somehow understand “minimize”, but a vehicle-to-grid system that extends battery life is a very strong claim.
Although the article was written in a cheering mode, it also acknowledges that battery degradation is a problem in current vehicle-to-grid systems, but that this research achieved an extended battery life. Not just a tiny extension, a whopping 10 percent extension of battery life by operating in the vehicle-to-grid system.