In previous posts, I threw around a bunch of numbers and sometimes mentioned that these are insanely high, but never gave an idea how high. I now will try to put them in perspective in this post. I found a sweet spot where solar and wind both could deliver enough power to meet demand. This happened at 8.57 times the current capacity of solar and wind, supported by seasonal storage of 2,421 GWh. I called that an insane amount of storage. How would this compare to actual demand over the year?
When comparing seasonal characteristics of solar and wind in previous post, there was one graph that got my attention:
It shows wind got shortages (visible orange lines) during the summer months, while solar had its best production at the same time. Solar got shortages in the beginning and end of the year, while wind had a decent production at the same time. Then it is tempting to assume that solar and wind are complementary. I understand that solar and wind are only complementary on average. When it comes to individual timeslots, they are certainly not complementary. That is an disadvantage when production and demand need to be in balance at all times.
What if we throw in storage? Is there an optimal mix of solar and wind that can deliver as much as possible direct power from solar and wind, therefor minimizing storage requirements? Separately, both solar and wind have dizzying storage requirements. Yet they could be balanced by means of 2,421 GWh storage in my first post on storage. This tells me that quite some gain is possible combining them both. Can we go even lower by varying both capacities? Maybe even in a storage range that is feasible? However, at a higher multiplier both drifted apart and solar was left far behind, so it might not be as simple as it looks.
Recently, I learned that that demand response (a change in energy consumption in order to deal with intermittency) would be more problematic for increasing solar capacities and easier for increasing wind capacities. Initially, that seemed a bit contra-intuitive to me. Solar is doing best during the day when most power is needed, so until then I assumed that it would be easier for demand to follow solar power (coinciding with the demand pattern) than wind power (which is more erratic).
However, there are some things that might interfere with that reasoning. For example, sunny weekends or holidays could spell trouble (high production, yet low demand). More, at our latitude, solar produces most power in summer when least power is needed and least in winter when most power is needed. This however allows for building backup during the summer months to be used later when there is a shortage.
The dynamics of wind power is different. At our latitude, there is more wind in winter when we need most power and less in summer when we need least power. It is however not guaranteed to blow when demand is high and then it also requires some kind of backup/storage.
Looking at it over a longer time frame, demand should follow wind better, potentially decreasing the need for demand response. Time to adapt my simple energy model to find out.
In my series on the impact of intermittent power sources, I got to the point where I was working with a unlimited battery capacity to find out how big that storage needs to be to fill in the gaps of less production with stored power from earlier excess production. I came to the (surprising) conclusion that almost 2,500 GWh was needed to fill in all the gaps. To recap, this is how the stored power looked like over the year:
Which I found an awful high number for storage. Therefor my question back then was: is it really necessary to store all that power? What would happen when storage is limited to a value below the optimal capacity?
This post is a follow-up to the previous post, where I looked into the scenario of an unlimited storage device topping off the excess electricity at peaks and filling in the gaps when there is a shortage. I found that a storage capacity of about 2,500 GWh was needed to fill in all the gaps. That number seemed very high to me, so I wanted to check whether other people also found such large numbers.
I quickly found a back-of-the-envelope-calculation by the late David MacKay. He proposes that 33 GW of wind power, delivering on average 10 GW, needs roughly 1,200 GWh backup. This is his calculation:
10 GW × (5 × 24 h) = 1,200 GWh.
He starts from the assumption that it is necessary to bridge five consecutive days of no wind. The difference is that he only considers wind, while I also include another intermittent energy source (solar).
The average delivered power is rather similar in both cases. In my scenario I have ((3,369.05 MW x 0.12) + (3,157.185 MW x 0.24)) x 8.57 = 9,957.95 MW.
Which is a tad below the 10 GW of MacKay is working with. Yet, my result is almost twice as high. Is this the influence of another intermittent power source in the mix? Or just a coincidence? Or did I do something wrong?
A bit later than I anticipated, a follow-up on previous post where I presented a simple model that gave the opportunity to learn about the mechanisms that determine an increase of intermittent energy sources (solar and wind). It confirmed that, when increasing in capacity, the production lows don’t grow much, but the production highs will steeply increase. Which is, mathematical speaking, rather logical. In practice this means that the need for backup will not decrease much with increasing capacity, but that at the same time measures need to be taken to top off those ever growing peaks.
That led to the next question: is it possible, at least theoretically, to save the surplus electricity from production highs and use it later when there is not enough electricity at production lows? I adapted the model to a scenario that when more solar and wind energy is produced than consumed, then the excess energy will be stored and when less solar and wind energy is produced than consumed, the system would try to retrieve this from storage.
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.
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.
A small interruption from my 6-years-of-blogging series. This blog documented several meaningless (or even wrong) remarks from our (now former) Flemish Minister of Energy. I was a bit sad when I heard that he chose to be mayor of Ostend in stead of Minister of Energy, but apparently he doesn’t have to be Minister to utter such remarks. On a congress organized by his party (OpenVLD) he made following claim (translated from Dutch):
Today, offshore wind turbines provide 1.2 GW of energy production.
That is not even remotely true. Belgian offshore wind provides much less than that. The 1.2 GW is the capacity. The real production will vary, but will be on average a fraction of that number.
He obviously is confusing capacity with production. Why am I not surprised? Strange however is that the error is still not corrected yet at the time I published this post (now more than a week later). Didn’t they notice it? Or do all the energy experts of that political party stand behind this number?
Then comes the interesting part that leads to the subject of this post (translated from Dutch, my emphasis):
“By 2026 we will increase this to 4GW without subsidies. From then on, the offshore wind farms will provide 20% of the total electricity requirement. This is just as much as the total electricity consumption of all Belgian families, “says Bart Tommelein.
This claim reminded me of the new energy pact made by the Flemish Green party, published a few days before the congress. It has a similar claim (translated from Dutch, my emphasis):
Is renewable energy cheap? I often heard this claim in the past, mostly from politicians who want to justify their policies, but also from scientists. I then assumed that not all costs were counted, but had no clue what their specific arguments were.
The claim was also made in the current events lecture “A Sustainable Energy Supply for Belgium” (see previous post), specifically in the second lecture. The claim was that renewables are so cheap that they push fossil-fuel fired power plants out of the market. Odd, because subsidies for for example wind energy still exist in Belgium. If wind energy is really cheaper than fossil-fuel energy, then those subsidies don’t make much sense. Luckily, the speaker (Johan Driesen) took some time to explain his arguments in support of his claim and that made it very clear what he exactly meant by being “cheap”.
This is the part where he explains his reasoning (Dunglish not mine):