Another year is over, and I wanted to write a ‘year in review’ series about the electricy system in 2023! First up is a look at how different TSOs adjust the Flowbased Domain for grid security reasons, the Individual Validations or IVA for short.

But first, a quick shout out to the sponsor of my database server: Code Yellow! Code Yellow has provided the server that supports my flowbased domain database. Without them the analysis in this post would be a lot more work. Many thanks!

Please note that this post is quite technical and about a specific capacity calculation topic. I tried to explain it to non experts as well, but you do need a basic idea of the flowbased domain.
This post is also specifically about the validation results of Flowbased CORE. The Nordic Flowbased has yet to implement a validation step.

What are virtual capacities and individual validations⌗

Let’s start with an introduction to the topic. Virtual capacity is the capacity that TSOs release on top of the capacity calculated in the normal grid calculation. This is done to reach the regulatory minimum capacity requirement. This requirement is also informally called the “70% rule”.

Ever since the introduction of these virtual capacities, the challenge arose on how to ensure grid security for this virtual part. To tackle this, the validation step was implemented into the Flowbased Capacity Calculation methodology.

Validation allows TSOs to reduce capacity on elements (CNECs) in the domain if and only if TSO’s demonstrate that the capacity calculated cannot be secured even when all available remedial actions (RA) are activated. RA’s are usually forms of redispatch.

The adjustment of a CNEC is called Individual Validation Adjustment (IVA). The idea behind this adjustment is that the non-virtual part you get for free. However, if the market uses the virtual part, it incurs a TSO (and thus societal) cost. This then spurs grid investments to make sure you can reach the target capacity with as little virtual capacity as possible.

Process wise, the validation step is one of the last steps in Flowbased. The last being the addition of LTnom flows. The validation is called individual and thus is in principle run by local tooling of individual TSOs. The exception to this will be explained later.
Stepwise the process to the final capacity then becomes as follows:

1. Calculate real capacity ($RAM_{init}$)
2. Add virtual capacity until regulatory target ($AMR$)
3. Execute validation and subtract IVAs if needed ($IVA$)

So, the final capacity then becomes: $RAM_{final}=RAM_{init}+AMR-IVA$
Please note that this is a simplified picture of the whole flowbased process to explain the IVA flow.

With the rising of regulatory targets, this validation of virtual capacities is becoming increasingly important. For more information about these rising targets, you can read for example the Dutch action plan about this here.

Remarks on the data⌗

Dataset used includes the entire of 2023, with a total of 8760 hours. On two days in 2023, Elia had an exceptional unintended fallback causing a very distorted picture on IVAs. For this reason, Elia IVAs for the full day of 2023-04-19, as well as, for hour 11, 12 and 13 of 2023-08-21 have been filtered out. More information about the first day can be found in my post here.

Now that the topic and data remarks are introduced, let’s get into the analysis.

IVAs in 2023⌗

To start, figure 1 below shows how many hours were impacted by IVAs in 2023.

Here we can see that in only 36% of the hours, no IVA was applied on presolved or active constraints. This percentage of hours seems high. However, there are big differences between how much IVA and on how many constraints they were applied in those hours. Furthermore, not every TSO applies the same methodology, since its a local responsibility. Let us have a look at differences between TSOs.

Differences between TSOs: methodologies⌗

There are some important differences in methodologies applied. First off the most confusing part of this story: not all Individual Validations are actually done Individual. The TSOs of Germany, Austria and the Netherlands decided to work together, using one tool to calculate IVAs for all three countries, this tool is called DAVinCy. This pooling allows the application of cross border IVAs. For example, an IVA on German CNECs to solve an overload in NL. From a social welfare perspective this is more efficient.
In fact pooling the whole region would be more efficient and this is also forseen in the methodology, the so called Common Validation Adjustment or CVA. This is not implemented yet however, but is actively being worked on.

As mentioned before, each TSO is responsible for their own validation process. Except for the common DAVinCy group, all CORE TSOs have developed their own methodologies. Explaining each of them is outside the scope of this post, instead, we focus here on the trend differences among TSOs.
Detailed explanations of these methodologies per TSO (including the DAVinCy group) can be found in the appendix of CORE Consultative Group slides of 2023-03-28, starting from slide 41 here.

IVA trends between TSOs: number of occurrences⌗

First, we determine the number of hours in which a TSO had at least one active IVA in the presolved domain. Figure 2 below shows both the number of hours and the percentage of those hours in 2023.

Here we can see that there is a clear trend difference between the top 3 TSOs, namely RTE, SEPS and Transelectrica, and the other TSOs. These three TSOs applied IVAs in many more hours during 2023, with RTE applying in almost 1/3 of all hours.

In addition, a second trend is noticeable when IVAs per hours are split by months (figure 3 below).

Here we can see that Transelectrica applies more IVAs at the first half of the year, while RTE applied more in the second half of the year. All the other TSOs have fewer clear trends, with variations throughout the year.

IVA trends between TSOs: sizes⌗

The same analysis can be made with sizes of IVAs. To make the comparison between CNECs fair, results are expressed as a % of the maximum thermal flow on an element (Fmax). Please note that due to negative reference flows it is possible to have an IVA which is > 100% of Fmax. This is a fairly uncommon case. In 2023 only the DAVinCy group applied such IVAs.
All presolved domain IVAs are shown in a boxplot in figure 4 below. Each dot next to the boxplot is a datapoint in the set.

Results show a clear differences on percentage of IVAs applied. CEPS, Mavir, DAVinCy and RTE apply fairly large IVA’s. CEPS has a median of almost 40% of Fmax. However, interpretation requires caution since the median is based on very few applications. Mavir, DAVinCy and RTE have a median of around 20%, with DAVinCy showing large spread outside of their box. Elia shows this spread too. However, their median is low. We see again that there is a group of TSOs which are scoring higher than the rest on this indicator.

This indicator too can be split out per month, as shown in figure 5 below.

Here no clear trend can be seen. The only thing that stands out, is that the high spread of Elia is apparently caused by IVA spikes in February and August.

Conclusion of trends⌗

Is there an overall trend to be concluded?
Results clearly showed that there are major differences on when and how much IVAs are applied across TSOs. Their statistics are summarized in table 1 below. This is the table form of figure 2 and 4.

TSO	#CNECs	mean IVA (%Fmax)	min IVA (%Fmax)	median IVA (%Fmax)	max IVA (%Fmax)	#hours	% hours of year
CEPS	10.0	40.23	27.09	38.92	51.66	10	0.11
DAVinCy	1733.0	28.45	0.05	19.96	142.62	218	2.49
ELES	198.0	5.18	0.09	4.46	20.56	155	1.77
ELIA	397.0	17.10	0.60	6.17	99.06	277	3.16
HOPS	194.0	4.95	0.08	3.65	30.21	181	2.07
MAVIR	408.0	16.75	0.29	16.46	55.16	249	2.84
PSE	700.0	10.30	0.07	6.21	36.19	339	3.87
RTE	2949.0	22.24	0.03	21.72	55.38	2450	27.97
SEPS	3330.0	6.43	0.07	5.28	30.01	2232	25.48
TRANSELECTRICA	3602.0	10.51	0.08	8.75	73.40	1804	20.59

From table 1, the TSOs can be categorized along the axis of number hours and the median IVA (expressed as % of Fmax). This is plotted in figure 6 below. CEPS is excluded from this graph due to its outlier character, showing few hours and a high median IVA %.

From figure 6 four catagories of trends can be concluded:

1. RTE has a high number of hours with also a high median IVA value
2. Transelectrica and SEPS have a high number of hours but low median IVA value
3. ELES, HOPS, Elia and PSE have lower number of hours and low median IVA value
4. DAVinCy group, MAVIR and CEPS (last one not shown) have low number of hours but high median IVA

There are a couple of important things to note from this trend conclusion:

• there is no right or wrong here. Individual validation is a tailored process to each grid. There are multiple ways to handle the validation and it is the individual responsibility of each TSO to apply those.
• there may a bias on the dataset that benefits larger TSOs. Larger TSOs have more CNECs and have thus a larger chance of being presolved and needing to apply IVAs.

This concludes the first post on the “year in review” series. More to follow later!

If you have any questions or suggestions feel free to reach out to me on linkedin, twitter (on either search with my real name) or via email at frank@fboerman.nl.

Disclaimer: all information described in this post is meant for informational purpose and written by an expert working on the topic. No information neither any conclusion written in this post can be taken as an official opinion or position of my employer TenneT in any way, shape or form.