What results should flexibility needs assessments in the power sector produce? : output indicators that meet the objectives of the electricity market design reform.
Date: 2024-10-07
Institutions: Joint Research Centre
Subjects: EU Member State, electrical energy, energy market, reduction of gas emissions, renewable energy, research report, security of supply

What results should Flexibility  
Needs Assessments in 
the power sector produce?  

Output indicators that meet the objectives  
of the Electricity Market Design reform 

By Thomaßen, G. and Landeka, J. 

2024 

ISSN 1831-9424 

EUR 40070 

 
 
 
 
 
 
 
 
This document is a publication by the Joint Research Centre (JRC), the European Commission’s science and knowledge 
service. It aims to provide evidence-based scientific support to the European policymaking process. The contents of this 
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concerning the delimitation of its frontiers or boundaries. 

Contact information  
Name: Georg Thomaßen 
Email: georg.thomassen@ec.europa.eu 

EU Science Hub 
https://joint-research-centre.ec.europa.eu 

JRC139027 

EUR 40070 

PDF 

ISBN 978-92-68-20978-3   ISSN 1831-9424   doi:10.2760/9174552 

KJ-01-24-074-EN-N 

Luxembourg: Publications Office of the European Union, 2024 

© European Union, 2024 

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How to cite this report: European Commission, Joint Research Centre, Thomassen, G. and Landeka, J., What results should Flexibility Needs 
Assessments in the power sector produce, Publications Office of the European Union, Luxembourg, 2024, https://data.europa.eu/
doi/10.2760/9174552, JRC139027. 

 EUR 40070 

 
 
 
 
 
 
 
 
 
 
 
 
 
Contents 

Abstract ...................................................................................................................................................................................................... 2 

Acknowledgements .............................................................................................................................................................................. 3 

Executive summary .............................................................................................................................................................................. 4 

1  Introduction ....................................................................................................................................................................................... 6 

2  Flexibility indicators in the literature .................................................................................................................................. 8 

2.1  Renewable integration ................................................................................................................................................... 10 

2.2  Ramping flexibility............................................................................................................................................................ 10 

2.3  Reserve requirements .................................................................................................................................................... 11 

2.4  Descriptive market indicators .................................................................................................................................... 11 

3  FNA output indicators in line with the EMD ................................................................................................................. 12 

3.1  Renewable integration needs .................................................................................................................................... 12 

3.1.1  Renewable integration target ...................................................................................................................... 13 

3.1.2  Calculation from model outputs ................................................................................................................ 13 

3.2  Ramping needs................................................................................................................................................................... 15 

3.2.1  Calculation from model outputs ................................................................................................................ 16 

3.3  Reserve needs .................................................................................................................................................................... 16 

3.3.1  Calculation from model outputs ................................................................................................................ 16 

3.4  Deriving the overall needs ........................................................................................................................................... 17 

4  Concluding remarks ................................................................................................................................................................... 18 

References ............................................................................................................................................................................................. 19 

List of abbreviations and definitions ...................................................................................................................................... 20 

List of figures ....................................................................................................................................................................................... 21 

1 

 
 
 
 
 
 
 
 
 
 
 
Abstract  

The recently adopted Electricity Market Design (EMD) reform includes provisions for the creation of 
Flexibility Needs Assessments (FNAs) on the national and European level. The reform sets a focus on 
advancing decarbonization while maintaining a high level of supply security. The FNAs should further 
enable Member States to set up mechanisms to procure additional flexibility to meet any identified 
inefficiencies  that  are  due  to  an  insufficiently  inflexible  system.  Against  this  background,  the  JRC 
reviewed existing flexibility assessments in the literature and the outcomes they produce. Based on 
this review, we propose that FNAs in Europe should assess three key areas: renewable integration, 
ramping  needs  and  reserve  requirements.  We  further  propose  concrete  indicators,  which  allow  to 
derive net flexibility needs – taking into consideration the capabilities already present in the system 
– and enable Member States to procure any missing volumes of flexibility.  

2 

 
 
 
 
 
 
Acknowledgements  

We would like to thank our colleagues at ACER for the fruitful discussions and exchanges.  

Authors 

Georg Thomaßen and Josipa Landeka 

3 

 
 
 
Executive summary  

Policy context 

The European Electricity Market Design (EMD) reform was adopted in July 2024. The reform includes 
provisions for the creation of Flexibility Needs Assessments on a national and European level. These 
assessments shall evaluate whether sufficient amounts of flexible resources are present in the power 
system to meet decarbonisation goals, by effectively integrating electricity from renewable sources, 
and maintaining a high level of supply security. Where sufficient flexibility is lacking to meet these 
goals, Member States can then procure the missing volumes. 

As a next step, ENTSO-E and the EU DSO entity are charged with developing a methodology, based 
on which the national assessments shall be conducted. After the proposal is finalized, ACER will have 
the option to amend and/or accept the methodology. 

Key conclusions 

—  Flexibility Needs Assessments (FNAs) shall identify concrete needs in the system to 
enable Member States to swiftly procure any missing volumes of flexibility. To do 
so, FNAs must identify concrete shortfalls in the system and quantify the amount of flexibility 
needed to counter these. The EMD mandates that flexibility needs shall be quantified so that 
goals with respect to decarbonization and supply security can be met.  

—  To assess the flexibility needed for decarbonization, two steps are necessary to 
quantify the amount of flexibility required for sufficient renewable integration. 
First, a benchmark needs to be set or derived that defines how much renewable generation 
should be integrated into the system, or how much renewable curtailment remains 
acceptable. FNAs can then quantify the necessary volumes of flexibility to achieve this 
benchmark by a better matching of electricity demand and renewable supply – directly 
through demand response or through storage as an intermediary.  

—  Whether sufficient amounts of flexibility are present in the system to maintain a 

high level of supply security can be evaluated by assessing the system’s capability 
to deal with ramps on the generation and the demand side, and by its ability to 
provide the necessary volumes of reserves. The relevance of these aspects will grow 
over the next decades with the decommissioning of large parts of the conventional power 
plant fleet in Europe and the advent of variable renewable generation. 

Main findings 

This report proposes a set of outputs that FNAs in Europe should produce to fulfil the criteria set out 
by the EMD. To this aim, we examined several flexibility assessments in the literature based on the 
aspects they investigated and the indicators they produced. These assessments typically present two 
types of indicators: (1) diagnostic indicators which indicate whether a concrete shortfall in the system 
occurred.  And  (2)  descriptive  indicators,  which  depict  characteristics  of  the  system,  which  do  not 
directly indicate a malfunction in the system, but rather add to the description of the system (and 
how  it  changes).  These  must  be  seen  as  part  of  the  bigger  picture  and  in  the  context  with  other 
indicators. 

4 

 
 
 
Across the investigated works, we further identified four key areas that present diagnostic indicators: 
Renewable  integration,  ramping  flexibility,  reserve  requirements  and  resource  adequacy.  The 
European  Resource  Adequacy  Assessment  (ERAA)  and  National  Resource  Adequacy  Assessments 
(NRAAs) already assess resource adequacy on a European and on the national levels. The EMD further 
calls for FNAs to be aligned with ERAA and the NRAAs. We therefore propose that FNAs should focus 
on the three other areas to be complementary to the RAAs.  

To meet the requirements from the EMD, indicators should tackle both, decarbonization and security 
of supply issues. For the first aspect, FNAs should evaluate the level of renewable integration. This 
requires a target against which the performance of the system can be assessed. Such a target can 
be set with regard to the total amount of renewables to be integrated, or with regard to the maximum 
amount of curtailment that is still deemed acceptable. Where sufficient national targets are lacking 
to calibrate such a renewable integration target, least-cost optimization could be used to determine 
the most economic level of curtailment.  

A desired level of renewable integration can then be achieved by increasing the correlation between 
electricity demand and renewable supply – either directly through demand response or with the help 
of  storage  as  an  intermediary.  The  additional  amount  of  flexibility  needed  can  be  determined  by 
adding energy shifting capability to the system, with energy shifting capability being a placeholder 
technology for either demand shifting or storage operation.  

The  supply  security  aspect  of  FNAs  can  further  be  covered  by  evaluating  ramping  needs  and 
operational reserve requirements. Both can be determined based on unit commitment model runs. If 
a load shedding event occurred due to insufficient ramping capability in the system (in contrast to 
insufficient generation capacity), it would signify a need in this area. Similarly, a unit commitment run 
could  produce  time  periods  in  which  the  model  could  not  provide  reserve  levels  in  line  with  the 
European  grid  codes.  Both  cases  are  expected  to  grow  in  relevance  with  large  volumes  of 
decommissioning foreseen, for example, with regard to coal power plants.   

To avoid overprocurement, it is essential to avoid double counting when combining the needs from 
the three areas. It should therefore be evaluated whether filling the need, for example, for renewable 
integration would take care of (some of) the needs identified in the two other areas.  

Related and future JRC work 

The JRC is consulting ACER on the implementation of national and the European FNAs in line with the 
EMD reform. The JRC has further consulted ACER on the implementation of ERAA since the start of 
the assessment, and is continuing to do so in the context of the new requirements set out by the EMD.   

Quick guide 

Section 1 introduces the issue, by discussing the requirements that the EMD reform sets out for FNAs, 
and the overall relevance of flexibility in the current context of the European power system. Section 
2 features a review of flexibility assessments in the literature, distinguishing key focus areas and 
evaluating the indicators presented in these works. Section 3 then features a set of suitable indicators, 
which would allow national and European FNAs to meet the requirements of the EMD, while section 
4 concludes.  

—   

5 

 
 
 
 
1 

Introduction  

The flexibility of the European power system has become a topic front and centre in the energy policy 
debate in recent years. This development started during the European gas crisis, where an obligation 
to reduce electricity demand during peak hours contributed to maintaining a secure supply (European 
Commission, 2022).  Accordingly, the European Electricity Market Design (EMD) reform – drafted in 
the wake of the crisis – sets a strong focus on improving the flexibility of the power system to increase 
security of supply and advance its decarbonization. 

Recent market outcomes in the EU demonstrate the need for this. Here, the number of hours with 
zero  or  negative  prices  has  been  increasing  massively  in  recent  years,  as  shown  in  Figure  1  for 
several key markets. The year 2024 appears to mark a new chapter in this context, as the number of 
hours in July is already matching or exceeding the number of hours that occurred during the entire 
year in previous years.  

Figure 1: Evolution of the cumulative number of hours with zero or negative prices in Germany and 
Luxembourg, Spain, France and Poland for the years 2020 to 2024. 

Source: JRC analysis based on ENTSO-E Transparency Platform. 

Zero and negative prices indicate a lack of flexibility in the system. They occur when generators are 
willing to produce without compensation, or even pay for producing electricity. These situations arise 
if: 

6 

 
 
 
 
(1)  Generation from sources with zero marginal costs supply the entire demand (usually variable 

renewables); 

(2)  Generation  capacity  is  insufficiently  flexible  to  shut  down  in  times  when  high  volumes  of 

renewable electricity is being produced.  

(3)  Capacity has to stay on-line to provide system services. 

(4)  Or  if  generation  is  remunerated  on  secondary  markets  –  for  example  through  renewable 

remuneration schemes.  

Accordingly, negative prices indicate an insufficient ability to accommodate renewables in the system. 
Either due to slow ramping capabilities, the inability to provide system services without conventional 
generators,  or  due  to  an  inability  to  bring  forward  sufficient  demand  to  store  or  consume  the 
electricity when it is being produced. 

The primary instruments for  fostering  flexibility in the power system featured in the EMD  are  the 
removal of market barriers and the introduction of support mechanisms for carbon-neutral flexibility. 
Member  States  are  supposed  to  design  support  mechanisms  based  on  the  need  for  additional 
flexibility, which shall be determined based on Flexibility Needs Assessments (FNAs) on the national 
level. In addition, ACER will conduct a European-wide FNA in order to assess flexibility needs at the 
EU level.  

These assessments are highly relevant, as they determine the volumes of additional flexibility that 
Member States can then procure. This report discusses the way FNAs on the national and European 
level  can  determine  a  need  for  additional  flexibility  in  the  power  system.  To  enable  addressing 
inflexibility  swiftly,  the  results  should  directly  enable  Member  States  to  dimension  support 
mechanisms that fill any identified gaps. In this way, FNAs distinguish themselves from more general 
flexibility assessments, as they quantify the need, instead of just identifying shortfalls. 

The  EMD  foresees  that  ENTSO-E  and  the  EU  DSO entity  draft the methodology  for  national  FNAs 
within 9 months after the EMD went into force (July of 2024). The proposal is then submitted to ACER, 
who can amend or accept the methodology, based on which the national FNAs will be performed. This 
report has to be seen in the context of this currently ongoing process. We aim to contribute to the 
discussion by outlining suitable indicators that meet the requirements arising from the EMD.  

7 

 
 
 
 
2  Flexibility indicators in the literature 

There exist different works in the literature that assess whether there is sufficient flexibility available 
in a power system. Some works feature as many as 20 indicators (Parker, 2017). Not all of these 
indicators directly describe a technical issue, such as a shortfall, but rather convey descriptively how 
the system changes. We can thus differentiate further between diagnostic indicators, which identify 
a concrete lack of a certain capability inside the system, and descriptive indicators, which describe 
characteristics of the system that do not directly identify a malfunction. As an example, lost load 
would  describe  a  diagnostic  parameter,  while  the  number  of  zero  or  negative  prices  would  be 
descriptive, as their occurrence does not directly pose an issue to the operation of the system – even 
though they might pose challenges to market participants and might signal that renewable electricity 
is wasted during the respective time periods. 

To align FNAs, both on a national and a European level, with the purposes set out by the EMD, the 
focus should  lie  on diagnostic indicators, as these assessments have the purpose of identifying a 
concrete  need  for  flexible capacity.  Descriptive indicators  can  help  to  complement the picture,  for 
example  by  presenting  market  indicators,  yet  should  be  considered  as  a  secondary  priority.  To 
differentiate  between  diagnostic  and  descriptive  indicators,  we  can  have  a  look  at  three  system 
services:  The  provision  of  clean  electricity,  the  provision  of  electricity  in  general,  as  well  as  the 
provision of sufficient reserves to safeguard the operation of the system. Malfunctions identified in 
these three areas describe a direct need for more flexibility. Descriptive indicators, like the occurrence 
of  negative  prices,  indicate  a  need  for  flexibility  yet  do  not  in  itself  prove  it.  If  we  assume,  as  a 
hypothetical, that the addition of flexibility would decrease the number of hours with negative prices, 
but lead to higher system costs and emissions, this addition would not be rectified. Indicators such 
as negative prices can therefore be an important indication of a lack of flexibility, yet they do not 
suffice on their own to determine a need. 

To  identify  suitable  indicators  that  describe  concrete  shortcomings  in  the  system  associated  with 
insufficient  amounts  of  flexibility,  the  JRC  analysed  several  related  works  (AESO,  2022; 
Chondrogiannis  et  al.,  2021;  Edmunds  et  al.,  2017;  Elia,  2023;  Parker,  2017),  and  screened  for 
diagnostic indicators.  

In this context, we identified four key areas: 

1.  Renewable integration  

2.  Ramping flexibility   

3.  Reserve requirements 

4.  Resource adequacy 

The fact that resource adequacy is included in this list reflects that it is often – and ideally – evaluated 
together  with  flexibility1.  It  reflects  that  supply  shortfalls  can  occur  due  to  insufficient  production 
capacity (i.e. total amount of capacity) in the system, or because the flexibility of said capacity was 

1 As a working definition, we assume that adequacy events occur if demand exceeds the available generation capacities. 
Flexibility-related load shedding events, on the other hand, can occur if there is capacity available in the system that 
could produce, but it is not possible to make it available in time meet demand, for example due to too long start-up 
times or low ramp rates.    

8 

 
 
 
                                                 
 
insufficient to make it available in time. In addition, improving resource adequacy can simultaneously 
improve the system’s flexibility and vice versa.  

In  the  European  legislation,  there is,  however,  a  clear  separation  of  roles:  The  European  Resource 
Adequacy Assessment (ERAA) is evaluating the level of resource adequacy in the European system, 
while National Resource Adequacy Assessments (NRAAs) have the same function on a national level. 
FNAs should further be in line with the ERAA and NRAAs according to the EMD. This can be achieved 
by taking power plant capacities from ERAA as a starting point, as a best guess of how the system 
will look like, and excluding resource adequacy from the scope of FNAs. The remaining three areas in 
conjunction  can  deliver  a  comprehensive  picture  of  whether  sufficient  flexibility  is  available.  An 
overview on their presence in the assessed works is given in Table 1. The assessments evaluated in 
this work focus on identifying malfunctions in the system. While this is a necessary precondition to 
determine  the  system’s  needs,  FNAs  should  extend  beyond  this  point  to  quantify  the  capabilities 
Member States need to procure to meet the identified shortfalls.  

Table 1: Overview of featured indicators in the assessed literature. Coloured cell implies presence of indicator 
type. 

(AESO, 
2022) 

(Chondro
giannis et 
al., 2021) 

(Edmunds 
et al., 
2017) 

(Parker, 
2017) 

(Elia, 
2023) 

(As part of 
resource 
adequacy) 

(As part of 
resource 
adequacy 

Renewable 
integration 

Ramping 
flexibility 

Reserve 
requirements 

Diagnostic 

Descriptive 

Diagnostic 

Descriptive 

Diagnostic 

Descriptive 

Markets 

Descriptive 

Source: JRC analysis 

In addition to the areas presented above, one could further assess the contribution of flexibility to 
resolving congestion. Besides the fact that this aspect was not considered in any of the assessments 

9 

 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
reviewed for this work, including congestion in FNAs is rather tricky, due to different reasons. From a 
feasibility point of view, it would take large grid modelling exercises – down to the distribution level 
– to capture the role of flexibility in managing congestion. More importantly, however, the provisions 
in the EMD are not necessarily suitable to resolve congestion by procuring additional flexibility through 
the Member States: Let us assume that a FNA found a need for more flexible resources in the system 
to manage congestion better. If these resources were to be procured through a general mechanism 
by the Member State in question, there would be no guarantee that they would be operated in a way 
that relieves congestion. If they were to be placed on the wrong side of a bottleneck, they could well 
increase congestion further.  

2.1  Renewable integration  

A lack of flexibility in the system can lead to lower levels of renewable integration, as the system is 
insufficiently capable to either store renewable generation with the purpose of making it available at 
a  later  point  in  time,  or  to  shift  demand  to  timeframes  when  unused  renewable  energy  is  still 
available. Accordingly, several assessments evaluate the level of renewable curtailment (AESO, 2022; 
Chondrogiannis et al., 2021; Edmunds et al., 2017; Parker, 2017). In addition, assessments feature 
other descriptive indicators, such as the penetration level of renewable generation (Chondrogiannis 
et al., 2021), the increase in forecast errors (AESO, 2022) or the volatility of renewable infeed (Parker, 
2017).  

There  are,  however,  two  issues  with  taking  renewable  curtailment  as  the  final  output  indicator 
measuring  renewable  integration.  Firstly,  one  would  need  to  define  how  much  curtailment  is  still 
acceptable as otherwise no shortfall can be identified. Some curtailment will always be part of the 
most  economical  solution  –  instead  of  investing  in  flexibility  until  the  last  MWh  of  renewable 
generation was integrated. Similar to a LOLE target for resource adequacy assessments, a renewable 
integration target would  therefore  need to be defined. The  FNA would then identify a need if this 
target was not met.  

The second issue is that an unmet renewable integration target does not contain information on how 
much flexibility is needed to meet the target. To allow for a fast procurement process, FNAs would 
therefore need to identify how much flexibility is needed to reduce curtailment below a pre-defined 
level.  

2.2  Ramping flexibility   

Insufficiently flexible power systems can further produce situations in which the system operator has 
to order load shedding – even though generation capacity is available in the system and generally 
functional. In these cases, free capacity is not able to ramp up in time to meet demand due to ramping 
limitations. Ramping flexibility includes as well limitations when power plants cannot be ramped up 
in time after a period of downtime. 

These situations can occur when extreme ramps on the demand side occur, for example due to the 
electrification of heating, which can produce high winter peaks (Thomaßen et al., 2021). Renewable 
ramps would likely be less of a concern: The market algorithm would curtail renewable generation to 
maintain enough dispatchable capacity in the system to safeguard operation, as this solution would 
produce  lower  costs  than  shedding  load.  Exits  of  conventional  generator  can  further  increase  the 
relevance of assessing whether sufficient ramping capacity will be present in the system.  

10 

 
 
 
Accordingly, ramping needs are at the core of the assessed works, being considered as an element of  
security of supply (Chondrogiannis et al., 2021; Edmunds et al., 2017; Elia, 2023; Parker, 2017), while 
(AESO, 2022) features a descriptive depiction of the magnitude of ramps that occur in the system.  

(Edmunds et al., 2017; Parker, 2017) further identified those periods where demand was not met due 
to insufficient ramping resources, distinguishing them from general adequacy events. We recommend 
to  follow  these  two  examples  to  allow  for  sufficient  distinction  between  adequacy  and  flexibility 
related events, and thereby sufficient distinction between ERAA/NRAAs and FNAs.  

2.3  Reserve requirements  

Lastly, insufficient flexibility in the system can trigger events when the system operator is not capable 
of  procuring  sufficient  amounts  of  operating  reserves  to  meet  reserve  targets.  This  concerns  the 
ability of TSOs to procure and maintain a sufficiently sized reserve before imbalances are settled in 
the balancing market. 

Similar indicators have been reported by (Chondrogiannis et al., 2021; Edmunds et al., 2017; Parker, 
2017). Providing reserves does not only require free, non-producing capacity, but as well the capability 
to make this capacity available within a certain time window. If capacity is insufficiently flexible, time 
periods can occur, during which the market cannot offer sufficient reserve volumes to fulfil the target 
set by the system operator, resulting in a shortage of reserves.  

Flexibility assessments can further assess whether the demand for balancing services will increase, 
and therefore, whether said reserve would need to increase in size. In this way, (Elia, 2023) assesses 
the expected imbalances, such as forecast errors, and whether this would create a need to procure 
larger volumes of reserves in the future.  

2.4  Descriptive market indicators 

In addition to the three areas above, several assessments feature descriptive market indicators, such 
as the number of hours with negative prices or positive price spikes that are expected (Edmunds et 
al., 2017; Parker, 2017), as well as the general level of volatility (Chondrogiannis et al., 2021; Parker, 
2017). These indicators can be helpful for market participants, as they give an outlook on how prices 
might change in the future. As argued above, they should be seen as an important but secondary 
output of FNAs, as the system’s needs cannot be directly derived from these. 

11 

 
 
 
3  FNA output indicators in line with the EMD 

In this section, we propose a set of output indicators, which consider best practices in the literature 
(summarized in the previous section), as well as the needs that result from the EMD reform. 

The EMD mandates that the focus of FNAs shall be the need for flexible resources to achieve both, 
security of supply and decarbonization, as outlined in Article 19 c): 

[…]  the  regulatory  authority,  or  another authority  or entity designated by a Member  State, 
shall adopt a report on the estimated needs for flexibility for a period of at least the next 
5 to 10 years at national level, in view of the need to cost effectively achieve security and 
reliability of supply and decarbonise the electricity system […] 

(Emphasis added by the authors.) 

It  is  therefore  the  primary  purpose  of  the  FNA  Methodology  to  identify  in  which  situations 
inefficiencies can occur, which are related  to a lack of flexibility in the system, and estimate  how 
much additional flexibility is needed. The focus shall furthermore lie on inefficiencies that undermine 
the security of supply, or decarbonization efforts, which aligns well with the three areas identified in 
section 2: renewable integration, ramping needs and reserve requirements.  

In the following, we present three indicators that describe these areas of priority. In conjunction, they 
deliver a consistent and holistic picture of the inefficiencies present in a given power system that 
arise due to insufficient flexibility, and which have an impact on decarbonization and the security of 
supply. They should be determined with the help of a unit commitment model, respecting start-up 
and  shut-down  times,  ramp  rates,  among  others,  as  to  deliver  an  accurate  picture  of  the 
(in)flexibilities  present  in  the  power  system.  In  distinction  to  gross  flexibility  needs  derived  with 
residual load curve analyses (see for example (Artelys, 2023)), all indicators presented here describe 
net flexibility needs, i.e. take into consideration the capabilities already present in the system.  

3.1  Renewable integration needs 

Instead  of  simply  reporting  renewable  curtailment,  we  propose  to  identify  the  flexibility  needs 
associated with a reduction in curtailment below a certain target. The need for such an indicator can 
be directly derived from Article 19 c), mandating that the report shall 

[…] evaluate  the different types  of  needs for flexibility, at least on a seasonal,  daily and 
hourly  basis,  to  integrate  electricity  generated  from  renewable  sources  in  the 
electricity system.[…]  

(Emphasis by the authors.) 

Broadly, there are two ways of integrating more renewable electricity into the system: By increasing 
transmission  and  by  improving  the correlation  of  renewable  supply  and  demand.  A  full-scale  grid 
modelling exercise is likely out of scope of the assessment. Transmission planning is further subject 
to the Ten Year Network Development Plan (TYNDP) and the national Network Development Plans 
(NDPs). If FNAs were to assess transmission needs as well, there is a risk that they would interfere 
with  these  processes,  adding  unnecessary  complexity  to  transmission  planning  while  blurring 
responsibilities and competencies.  

The way to increase the share of renewable electricity in the grid within the jurisdiction of FNAs is 
therefore  to  increase  the  correlation  between  supply  and  demand.  With  renewable  production 

12 

 
 
 
potential being driven by weather conditions, there broadly exist two options: To move consumption 
to times when renewable electricity is available, or to store renewable electricity with the purpose of 
making it available when sufficient demand for it is present. Leaving aside transmission expansion, 
additional  renewable  integration  can  therefore  only  be  achieved  by  additional  energy  shifting  – 
demand or supply.  

The respective section in the EMD  further mandates that the needs shall  be  split up into  at least 
hourly, daily and seasonal flexibility needs. While those indicators related to the security of supply 
produce primarily hourly and sub-hourly flexibility needs, renewable integration needs arise along all 
time scales, up to seasonal or even inter-annual horizons2.  

3.1.1  Renewable integration target 

A precondition for determining the energy shifting need of a system is that there exists a target with 
regard to how much renewable electricity shall be integrated into the system. This target can, for 
example,  be  formulated  as  a  renewable  share  with  regard  to  consumption,  or  as  a  curtailment 
standard, mandating how much renewable curtailment should occur at maximum. Here, it has to be 
noted that it is likely not reasonable to set a common curtailment standard, as the system-optimal 
level of curtailment will differ between a country with high shares of variable renewables and one 
which has just started deploying these technologies. It will further differ in time, as higher curtailment 
rates will be system optimal with larger deployed volumes of variable renewable generation. Each 
Member  State  therefore  has  to  define  what  level  of  renewable  curtailment  is acceptable  at  what 
point in time. 

One option to derive such a target would be to interpret national targets, where these are defined in 
sufficient detail. A renewable integration target could be derived, for example, if these describe the 
deployed  renewable  capacity  and  the  share  of  renewable  electricity  in  the  electricity  mix.  The 
renewable integration target would be achieved if sufficient flexibility were present in the system to 
integrate the renewable energy volumes foreseen by the national targets.  

A second option, for example where similar information is lacking, would be that Member States rely 
on modelling approaches to identify how much renewable integration is system optimal.  

3.1.2  Calculation from model outputs 

The starting point to determine a renewable integration  need would be a unit-commitment model 
run, which resulted in insufficient amounts of renewable electricity being integrated into the system. 
As  outlined  above,  a  renewable  integration  need  would  be  equivalent  to  a  need  for  more  energy 
shifting to increase utilization. 

To  determine  the  energy shifting  needs,  an  energy-shifting  technology  (EST)  can  be  added  to  the 
system until the renewable integration target was met (see Box 1). The correct capacity of this EST 
could be determined with the help of an investment model, either iterative or in one run. Alternatively, 

2 Inter-annual fluctuations in renewable energy supply can be relevant with regard to hydro production, or – potentially at 

higher levels of decarbonization – with regard to the production of hydrogen.  

13 

 
 
 
                                                 
 
even capacity additions by hand would be a feasible, yet cumbersome solution, similar to ENTSO-E’s 
approach for the Capacity Market scenario in ERAA 2021 (ENTSO-E, 2021). 

Box 1: Energy shifting technology 

An energy shifting technology (EST) can act as a placeholder for flexibility with energy shifting capabilities 
– such as demand response and storage – and should be modelled as a dummy storage technology. It is 
suitable as well to depict demand shifting, as the shifting process is often modelled through the use of 
some kind of storage (virtual or actual3). This allows depicting the impact of additional capabilities to 
transfer electricity in time, which is a precondition for increasing the utilization of renewable generation 
(compare section 3.1). Adding EST capacity (measured in MWh) until a renewable integration target is met 
therefore describes the need, without any assumption to how this need is ultimately satisfied.  

To remain technology agnostic, the EST should therefore be parametrized as a storage technology without 
losses, which is primarily defined through its energy content. Restrictions with regard to charging and 
discharging capacity should not apply, to enforce that shifting energy is the only purpose of capacity 
additions by the model. These limitations, together with loss rates, should rather be taken into 
consideration during the procurement process4 – as they are technology specific – instead of being 
considered within the procurement volume, which should be technology agnostic.  

Splitting up the renewable integration needs into the different time horizons (hourly/daily/seasonal) 
would then require an analysis of the time series, which describes the EST energy content. To this 
aim, a similar methodology to the one presented by (Artelys, 2023) could be used5. Instead, however, 
of deriving flexibility  needs from the residual  demand curve – which would yield gross needs  – it 
could be used to split up the energy shifting needs determined by the model, representing necessary 
additions to the existing capabilities (net needs).  

This can be achieved by taking the energy content curve of the EST and splitting it up by subtracting 
the mean over the corresponding time interval. For daily energy shifting needs, it would be the daily 
mean, while the weekly mean would be the relevant value for weekly energy shifting and so forth. As 
an example, the daily flexibility needs produced by each hour could be calculated as: 

𝐸(ℎ, 𝑑) − 𝐸𝑚𝑒𝑎𝑛(𝑑) 

With 𝐸(ℎ, 𝑑) being the energy content stored inside the EST during a given hour of the day ℎ on a 
given day 𝑑, and 𝐸𝑚𝑒𝑎𝑛(𝑑) being the mean energy content of the same day. 

The  difference  between  the  maximum  and  the  minimum  value  over  the  full  study  horizon  then 
corresponds to the renewable integration need, expressed as an energy shifting capacity (in MWh), 
which  could  be  satisfied  by  storage  and  demand  shifting  with the  corresponding  capabilities  (see 
Figure 2).  

3 For example in the case of heat pumps (thermal storage) or electric vehicles (considering charging strategies).  
4 For example through derating factors, similar to capacity credits in a capacity market.  
5 As an alternative, Fourier transformation could be used to disaggregate into different time horizons.  

14 

 
 
 
                                                 
 
Figure 2: Determination of daily (left) and seasonal (right) energy shifting needs based on an evaluation of 
the EST’s energy content curve (exemplary representation) 

Source: JRC analysis 

3.2  Ramping needs 

This indicator describes flexibility needs that are related to ramping, i.e. the inability to supply load 
due to insufficient ramping capacity inside the power system. Ramping needs distinguish themselves 
from  adequacy  indicators,  as  derived  in  ERAA,  as  they  describe  occurrences  in  which  sufficient 
generation capacity was in principle still available, yet it could not be committed or ramped up in time 
to meet demand. These needs are therefore a result of (1) limited capability to ramp up a committed 
generator from one production level during one hour to a higher (or lower) one in the next, or (2) of 
ramping  up  a  generator  that  was  previously  not  committed.  Start-up  and  minimum  down  time 
requirements being the limiting factor in the second case.  

The need to consider ramping needs can be derived from the EMD’s requirement to consider security 
of supply when assessing the flexibility needs within a power system, as load shedding events that 
are unrelated to adequacy are usually related to insufficient ramping capabilities. 

Ramps that describe the transitions from one market time interval to another fall under the category 
of hourly flexibility  needs, or even sub-hourly, if the model resolution is increased to 15 minutes. 
These correspond to the short-term flexibility definition used by (Elia, 2023). Limitations with regard 
to commitment decisions – activating a generator that was previously down – can further relate to 
longer time horizons.  

Capturing limitations with regard to commitment decisions would require the modelling of at least 
two separate market sessions  – one real time or several intraday sessions in addition to one day 
ahead. If forecasts for load or renewables deviate from the real-time outcome, it can  require the 
commitment of additional capacity. If this capacity cannot be committed, due to long start up times, 
it can force the system operator to order load shedding. These inefficiencies only reveal themselves 
if a market session after the day ahead is modelled – when some final commitment decisions were 
already made.  

15 

 
 
 
 
 
3.2.1  Calculation from model outputs 

The calculation of ramping needs is rather straightforward. As a first step, the hours during which 
load shedding occurred are identified. In a second step, a check is performed whether all available 
capacity  inside  the  respective  zone  was  operating,  i.e.  generating  power  or  providing  balancing 
services.  

If  all  capacity  was  operating,  but  it  was  still  not  possible  to  meet  demand,  the  event  has  to  be 
classified as an adequacy event, and therefore should not be reported in the flexibility indicators. If, 
however, there was sufficient capacity available in the respective zone, the load shedding event has 
to be seen in the context of insufficiently flexible power plants, as it was not possible to ramp up the 
free capacity in time. 

The needed amount of fast-ramping capacity can be determined by considering the maximum load 
shedding capacity  that  occurred  due to  ramping  constraints.  The  additional  flexibility  need due to 
ramping could therefore be described as a ramping capacity (in MW/MTU). This flexibility could be 
provided by very different means, such as storage, demand response, but also the flexibilization of 
existing generators and the addition of quick-start units. The final need further needs to take into 
consideration the  reliability  standard  set  by  the  Member  State  in question.  In  an  otherwise  highly 
adequate system, the occurrence of some load shedding events due to ramping limitations might still 
remain within acceptable limits. 

3.3  Reserve needs 

Similar  to  the  ramping  needs,  a  reserve  shortage  indicator  describes  insufficient  power  system 
flexibility to safeguard the security of supply. In addition to shortfalls in making generation capacity 
available to the market – which are subject to section 3.2 – insufficient flexibility can show itself in 
the model’s inability  to  meet  the  level  of  reserves which  should  be  withheld during  every trading 
interval. As described in section 2.3, this describes the TSO’s ability to withhold sufficient reserves 
before balancing markets are settled close to real time. Reduced reserve levels, in turn, can lead to 
load shedding events, as the risk increases that the balancing demand exceeds the available supply. 

Reserve shortages require additional flexibility at a sub-hourly timescale, as the delivery periods for 
all reserve products but replacement reserves are usually up to 12.5 minutes.  

3.3.1  Calculation from model outputs 

It is common to add a reserve constraint to unit commitment models to ensure that sufficient reserves 
are withheld during every trading interval. This constraint can be formulated as 

∑ 𝑅𝑒𝑠𝑒𝑟𝑣𝑒𝑢,ℎ
𝑢

+ 𝐿𝑜𝑠𝑡𝑅𝑒𝑠𝑒𝑟𝑣𝑒 = 𝑅𝑒𝑠𝑒𝑟𝑣𝑒𝑇𝑎𝑟𝑔𝑒𝑡 

With 𝑅𝑒𝑠𝑒𝑟𝑣𝑒𝑢,ℎ as the level of reserves provided by each unit 𝑢 during hour ℎ, and 𝑅𝑒𝑠𝑒𝑟𝑣𝑒𝑇𝑎𝑟𝑔𝑒𝑡 
being  the  amount  of  reserves  procured  by  the  TSO  for  the  relevant  reserve  segment.  The 
𝐿𝑜𝑠𝑡𝑅𝑒𝑠𝑒𝑟𝑣𝑒  variable  describes  a  slack  generator,  which  is  only  drawn  in  cases  when  the  model 
cannot fulfil the balance in any  other way.  TSOs would  always aim to preserve the reserve levels 
necessary to safeguard the system’s operation, even ordering load shedding to maintain adequate 
levels of reserves. The 𝐿𝑜𝑠𝑡𝑅𝑒𝑠𝑒𝑟𝑣𝑒 variable would therefore be penalized with a high penalty factor 
in the objective function.  

16 

 
 
 
Lost reserves can therefore be directly extracted from the modelling results. The amount of capacity 
needed to compensate a lost reserve event can be determined by considering the maximum amount 
of  capacity  that  was  missing.  Procuring  the  missing  capacity  in  a  flexibility  auction  then  requires 
taking  into  consideration  the  prequalification  criteria  that  exist  for  the  respective  reserve  product 
where a need was identified.  

3.4  Deriving the overall needs 

To limit the procurement of additional flexibility to what is actually needed, double counting should 
be avoided. To do so, one should start with the area that usually produces flexibility needs with the 
longest time horizon – renewable integration. The reason is that it is possible that additional flexibility 
for renewable integration will decrease the needs for additional flexibility for ramping and reserve 
purposes as well. Similarly, ramping needs, can produce hourly and multi-hourly flexibility needs and 
should therefore be considered before reserve needs.  

17 

 
 
 
4  Concluding remarks 

As  set  out  in  the  EMD  reform,  FNAs  should  address  both  security  of  supply  and  decarbonization 
objectives. They should further enable Member States to dimension support schemes for flexibility 
that procure sufficient volumes to address any existing gaps. To this aim, this work analyses existing 
assessments of power system flexibility in the literature before proposing suitable outcome indicators 
that fulfil these purposes.  

We  find  that  flexibility  assessments  commonly  focus  on  four  key  areas:  renewable  integration, 
ramping flexibility, reserve requirements and resource adequacy. As resource adequacy is subject to 
ERAA and NRAAs, we propose to focus on the three remaining areas in the upcoming methodology 
for FNAs.  

While the reviewed assessments provide already suitable indicators on aspects regarding the security 
of supply – ramping needs and reserve shortages – they usually evaluate renewable integration based 
on  curtailment  levels.  This  indicator  can  indeed  be  the  starting  point  to  judge  whether  sufficient 
resources are available to integrate renewables, yet there are two challenges: On the one hand, a 
renewable integration target would need to be defined, in comparison to which it can be determined 
whether renewable curtailment exceeds acceptable levels or not. Further, to meet the requirements 
set out by the EMD, it needs to be derived how much flexibility needs to be procured at the different 
time scales to meet a renewable integration target that would otherwise not be met.  

We thus propose three output indicators that align with the three identified areas of key interest: (1) 
renewable integration needs, (2) ramping needs, as well as reserve needs (3).  

With regard to (1), it appears necessary that Member States define a renewable integration target. 
Wherever sufficient information is available, this target could be derived from national renewable 
targets.  Alternatively,  modelling  exercises  could  be  used  determine  system-optimal  levels  of 
curtailment.  

In those cases where the target has not been met, renewable integration needs could be determined 
by adding  energy-shifting capacity  to the model until  sufficient amounts of renewable generation 
were  integrated.  We  further  outlined  how  these  needs  for  additional  energy  shifting  could  be 
separated into the different time horizons.  

Ramping needs (2) can furthermore be derived directly from unit-commitment model runs. To this 
aim, load shedding events can be evaluated. Events with insufficient ramping capacity need further 
to be distinguished from adequacy events, to avoid overlaps with ERAA/NRAAs. This can be achieved 
by considering the utilization rate of the available capacity.  

Lastly, it should be evaluated whether reserve shortages occur during the model runs. In these cases, 
we can quantify reserve needs (3), which describe the need for additional flexibility at a sub-hourly 
time horizon. These needs arise when there is insufficient capacity available for system operators to 
procure the targeted volumes for each reserve segment.  

To  avoid  over  procurement,  synergies  between  the  three  areas  of  interest  need  to  be  taken  into 
consideration.  It  needs  therefore  careful  assessment  whether  capacity  procured  for  one  purpose 
might  as  well  resolve  flexibility  shortages  in  other  areas.  Generally,  needs  with  the  largest  time 
horizon should therefore be determined first, as filling these can already supply some of the needs 
at shorter time horizons. 

18 

 
 
 
 
References  

AESO, 2022. System-Flexibility-Assessment. 

Artelys, 2023. Power System Flexibility in the Penta-region - Current State and Challenges for a 

Future Decarbonised Energy System. 

Chondrogiannis, S., Poncela-Blanco, M., Marinopoulos, A., Marneris, I., Ntomaris, A., Biskas, P., 

Bakirtzis, A., 2021. Power system flexibility: A methodological analytical framework based 
on unit commitment and economic dispatch modelling, in: Mathematical Modelling of 
Contemporary Electricity Markets. Elsevier, pp. 127–156. https://doi.org/10.1016/B978-0-
12-821838-9.00008-6 

Edmunds, T., Alzaabi, O., Mills, A., 2017. Flexibility Metrics to Support Grid Planning and Operations. 

Elia, 2023. Adequacy & Flexibility Study for Belgium (2024-2034). 

ENTSO-E, 2021. ERAA 2021: Annex 3 Methodology. 

European Commission, 2022. State of the Union 2022. 

https://ec.europa.eu/commission/presscorner/detail/en/ip_22_5489 

Parker, M.J., 2017. Grid Modernization: Metrics Analysis (GMLC1.1). 

Thomaßen, G., Kavvadias, K., Jiménez Navarro, J.P., 2021. The decarbonisation of the EU heating 
sector through electrification: A parametric analysis. Energy Policy 148, 111929. 
https://doi.org/10.1016/j.enpol.2020.111929 

19 

 
 
 
 
List of abbreviations and definitions  

Abbreviations 

Definitions 

ACER 

EMD 

ENTSO-E 

ERAA 

EU DSO  

FNA 

MWh 

MTU 

NDP 

NRAA 

RAA 

TSO 

Agency for the Cooperation of Energy Regulators 

Electricity Market Design  

European Network of Transmission System Operators for 
Electricity 

European Resource Adequacy Assessment 

European Distribution System Operators 

Flexibility Needs Assessment 

Megawatthour 

Market time unit 

Network Development Plan 

National Resource Adequacy Assessment 

Resource Adequacy Assessment 

Transmission System Operator 

TYNDP 

Ten Year Network Development Plan 

20 

 
 
 
 
 
List of figures  

Figure 1: Number of hours with zero or negative prices in Germany and Luxembourg, Spain, France 
and Poland for the years 2020 to 2024. ................................................................................................................................. 6 

Figure 2: Determination of daily (left) and seasonal (right) storage needs based on an evaluation of 
a dummy storage curve (exemplary representation) ..................................................................................................... 15 

21 

 
 
 
List of tables 

Table 1: Overview of featured indicators in the assessed literature. Coloured cell implies presence 
of indicator type. .................................................................................................................................................................................... 9 

22 

 
 
 
 
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