Wind Power Generation Intermittency – It’s Worse Than You Think It Is – Introduction

Posted on Mon 11/30/2020 by

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By Anton Lang ~

Introduction

We have all heard that wind power generation is intermittent, that it goes up and down on a daily basis. However, is that really all that much of a problem, and if so, how big a problem is it? We have also heard that constructing more wind plants will go towards alleviating this problem. Is that correct? Or will that only make the problem worse?

Well, it is in fact quite a large problem, and constructing more of those wind plants is making the problem worse.

Macarthur Wind Plant In Victoria Australia

For many years now, I have been looking at wind power generation here in Australia, and in fact recording and keeping wind generation data on a daily basis now for more than four years. After looking at this data on a daily basis for so long, I could see that it went up and down on that irregular basis, but what I was not seeing was long term trends of the scale of that intermittency, how big it was, how suddenly it would fall, how sustained it could be, and the quite large sizes of the falls, both sudden and long term.

So, six Months back now, in a task which took three Months, I went back over that daily data, back for a little more than two years, and collated all the falls for wind generation to see if it was just a matter of general ups and downs, or if those falls were large in scale. After the first session of this task, the problem started to show itself. There were a lot of sudden falls, and there were a lot of sustained falls over longer time frames. So here, what I needed to do was to set some parameters, based on the sizes of the loss of power generation, and the time basis for those falls in power generation. Even then, the problem was so large that I needed to have a basis of more than one time frame for sudden falls, and more than one for the long term falls.

The first thing I had to do was to set a base size for these power losses. Here, I selected 500MW, and you may think of that as an arbitrary amount, but I selected that for two distinct purposes. 500MW is around the average for a SINGLE large scale coal fired Unit. Here in Australia, we have 16 coal fired power plants, and there are 48 separate Units at all of those plants. The total Nameplate is 23000MW, so the average size of those Units is 480MW, so here I just rounded it up to that total of 500MW. So, the loss of 500MW of power in a short space of time is the equivalent of one of those large scale coal fired Units going off line, something that renewable power supporters tell us is proof somehow that coal fired power is unreliable. Secondly, and of far more importance, is that figure of 500MW equates to around four or more wind plants, not just the towers, but whole wind plants with many towers. The total Nameplate for wind power is currently 7728MW and there are 64 wind plants, so here, the average is 120MW, so the 500MW I have selected equates to around four wind plants, so those power losses are not just a few towers here and there, or just one wind plant going off line, as this 500MW is around 250 to 270 of those individual wind towers, so that is in fact a significant amount of wind generation failures across those time frames.

So I ended up with three time frames for sudden losses and two time frames for sustained losses of power generation, and I have listed those below, and after each time frame I have added the number of times this happened and also the range of the power losses. This is taken across the last two Years and two Months, so around 800 days.

1. Power loss in less than one hour – 53 times, between 500MW and 1340MW

2. Power loss in One Hour -54 times, between 500MW and 980MW

3. Power loss between one and three hours – 52 times between 630MW and 1570MW

4. Power loss between three and eight and a half hours – 42 times between 1240MW and 2490MW

5. Power loss over sustained long period of time – 64 times between 1500MW and 3670MW. (with 10 times over 3000MW)

As each of the time frames increased, then I also increased that starting base for power loss, because as many as I have included over that 500MW start base for those three lower time frames, there were many more in the power loss range of 250MW to 400MW, and in those two higher time frame ranges, there were also as many lower power loss totals as the ones I have included.

Now, as to the scale of this ‘problem’, and if it is even a problem at all, keep in mind here that this is just over the last two Years and two Months, so this is data covering just 800 days, and here we have 265 occasions where the power loss exceeds 500MW.

Again, I have looked at this data over the last four years, and now collected this data for the last 800 days, and, as often as I look at all this data, something that I did not see earlier has became more obvious now that I am doing this specific task, the fact that nearly all of those losses in the short time frames were when power generation was already quite high, and again, this is a further reason I have split all of this into those two areas, the three short time frame ones, and the two long time frame ones.

With all the images on this page, if you click on the image, it will open on a new page and at a much larger size, so you can better see the detail.

Wind Generation Sustained Power Loss

The thing which I was already aware of was that over the last two years, that when it comes to those long time frame power losses, it was apparent it was related to the weather. Every time one of those large High pressure weather systems came into an area in the South of the Country, then wind generation would fall away by a large amount. An example of that is shown in the image at the right, and here, you can see that power generation fell away from the high of 4500MW just after Midnight to that indicated low around 850MW, a loss of 3650MW across that time frame of 20 hours. So, what we have here is that the greatest percentage of all the data that I was recording was coming from that same area where those High pressure systems would pass over. This was the South Eastern area of South Australia, and the Central West area of Victoria. Now, that particular area is where the largest number of those wind plants are located. Australia has (now) got a total Nameplate for wind power of 7728MW. However, in that area I have mentioned here there is now a total Nameplate of 4916MW, and that is 64% of ALL the total wind plant Nameplate in the Country, two thirds of it all, just in those two States alone.

Now, here’s the thing I found recently with those short time frame power losses, and that was that this is also related to the weather as well.

We have been told often enough that these wind towers only operate between specific wind ranges. When the wind gets too high, then the wind towers automatically turn off, and the same happens when the wind is too low, they also turn off automatically.

Wind Generation Short Term Large Power Loss

So, what is happening here for those short time frame power losses is that between the occurrence of those large High pressure weather systems over that area, moving as they do from West to East, the isobars are closer together, and because of that, the wind is high, and so, there is high wind power generation. However if the wind gets too high, then the turbines turn off, and we have that loss of power when they turn off. An example of this is shown in the image at right, where power was already relatively high at the indicated high of 3558MW, and it quite suddenly fell 1340MW in 45 minutes. On that same image, you can also see that this happened earlier in the day twice, just after 2AM, and again just before 6AM, where, both times, it fell by more than 400MW, and then fell around 1500MW in a sustained period of more than seven hours. Now, selecting the base of 500MW as I did, it shows that a large number of towers turn off in high wind situations, and they do that in a short space of time as well, as will be shown in the tables for those short time frame losses. Now, yet again, that problem we have with the intermittency being supposedly resolved by constructing more of them, has in this case, also been made worse, as now there are more wind towers in that area, as more plants are constructed in that area, and now they are more susceptible to large scale losses in shorter time frames when the wind gets too high.

I mentioned that I used a start date of May in 2018, hence the 800 days ago I mentioned, and at that time, the total Nameplate for Wind Power was below 5000MW. So, in those 26 Months since the start of this task, the Nameplate for wind power has increased by almost 3000MW, probably around 20 or more new wind plants, and most of that increase in the number of those wind plants has been in that direct area I have mentioned, those two States of South Australia and Victoria.

This data I have collected here shows that the intermittency problem is getting worse, as there are more occurrences of power losses, and those losses in power generation are becoming larger.

In effect what has happened here is that by constructing MORE wind plants in that area, it has not been part of the solution of this perceived problem of intermittency. They have in fact made the problem WORSE.

Having now set the scene, in the next two Posts I will detail those losses, show you the tables of the scale of those losses, and explain them with respect to using three images for each time frame period across the 800 days of this data gathering task.

Link to Part Two – Wind Power Generation Intermittency – It’s Worse Than You Think It Is – Part Two

Link to Part Three – Wind Power Generation Intermittency – It’s Worse Than You Think It Is – Part Three

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Anton Lang uses the screen name of TonyfromOz, and he writes at this site, PA Pundits International on topics related to electrical power generation, from all sources, concentrating mainly on Renewable Power, and how the two most favoured methods of renewable power generation, Wind Power and all versions of Solar Power, fail comprehensively to deliver levels of power required to replace traditional power generation. His Bio is at this link.

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