Market Integration & SoS

Updated proposals for SJWS #6

ENTSOG offices – Brussels Stakeholder Joint Working Session – 26 April 2012

SJWS process on SoS & Market Integration

Feb. 15th Mar.

20th April 26th May ?

June TYNDP 2013-2022 Public WS

February session – Come-back to TYNDP 2011-2020

> Establishment of a shared understanding of current report and associated feedback

March session – ENTSOG initial proposals

> > Proposals focus on selection of relevant cases for SoS & Mkt Int. assessment Feedback on proposals and first considerations on indicators to be used

April session – ENTSOG updated proposals

> Fine-tuned scenarios/cases and first set of indicators

May session – Fine-tuning of assessment methodology

> Presentation of an integrated method (cases & indicators) fitting with other SJWSs 2

Security of Supply & UGS low deliverability

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Security of Supply – potential events

List of extreme but still realistic events will be slightly updated

> Considered list could be complemented at GRIP level for specific focus

Source Technical Transit Supply

Algeria Caspia 100% MEG & 100% Transmed separately 100% (dealt within the FID case) Libya 100% Green stream LNG Norway Russia Expecting for update GLE study 100% Langeled & 100% other connection (worst case to be tested) or process plant (see GASSCO) ?

100% Ukraine & 100% Belarus separately 4

LNG management

Definition of the import and storage share

> Supply part could be based on the historical curve not considering the highest values (using a pipe profile instead of) > The difference between the historical profile and the curve defined above could represent the storage part to be split between countries according the average autonomy-days (tank volume / send-out capacity) of their LNG terminals

LNG as storage

LNG tank management

>

LNG as import

Required parameters to be used in the model: • • stock level to be considered prior to any event the minimum level to be kept in stock > Such data will be provided by the update GLE study 5

Security of Supply – Event management

Management of disruption or low UGS deliverability cases

> Supply priority is: 1.

2.

3.

4.

Disrupted supply through alternative routes Alternative imports (including LNG until maximum potential supply as import) LNG (using remaining capacity up to send-out capacity) and UGS Disruption > Order does not influence the identification of gaps but provide transparency on the method and influence the resulting supply mix

Load factor of import routes

> Model will be able to use different load factor for routes between a given supply source and Europe > Nevertheless a minimum load factor will be defined for every route based on historical data 6

Security of Supply – Low UGS

Minimum UGS deliverability at European level

> UGS withdrawal rate at European level is defined by putting all imports at their Potential Supply level (disregarding LNG storage component) > Same UGS (and LNG storage component) load factor will be then used in every system (except for gas islands) 75% 75% 75% 75% 75% 75% 75%

Resulting information

> > > Comparison of the minimum deliverability with the one observed in February last years Identification of potential flow constraints preventing this even withdrawal rate Such identification highlights the relative influence of UGS by countries

but cannot be used to define investment gaps themselves

as a higher withdraw rate is sufficient 7

Security of Supply – 2-week case

120 100 80 60 40 20 0

Definition of demand level on a 2-week period

> For the 2-week period under Simultaneous Case, imports will be set at their potential supply value > An additional modelling will be made with every disruption

Way to model

Modeled day

1 2 3 4 5 6 7 Supply from Import & Nat.

Production Supply from UGS Demand UGS deliverability 1.

Supply/Demand balance on the last day defines the need of UGS deliverability 2.

Modeling check potential gaps 3.

Ex-post calculation defines the minimum UGS deliverability then level for the 6 previous days 8

Market Integration & Supply diversification

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Predominant supply

Which benchmark ?

> In comparison with Reference Case supply share (full color), potential benchmarks are: • X% of import capacity (TYNDP 2011-2020 with 95% for pipe and 80% LNG) • • Potential supply of the source +Y% increase in comparison with Ref. Case 12 000 10 000 8 000 6 000 4 000 2 000 -

Guidelines

> Cases/scenarios have to ensure that TYNDP cover extreme but still realistic scenarios in order to provide a meaningful information to decision-maker > Level of stress on infrastructures also depends on: • How are combined increased sources • the way other sources are decreased 12 000 10 000 8 000 6 000 4 000 2 000 6 000 5 000 4 000 3 000 2 000 1 000 -

Russia

2011 FID

Norway

2015 FID 2015 Others 2011 FID

LNG

2015 FID 2015 Others 2011 FID 2015 FID 2015 Others 2020 FID 2020 Others 2020 FID 2020 Others FID 10 2020 Others

Alternative supplies

Influence of each supply source will be considered separately

NO +14% RU, AL, LY, CA, LNG -5% NO - 14% > Supply spread will differ depending on how each import point of alternative supplies will be decreased: • By the same percentage for every source and route • By the same percentage for every source but giving some flexibility by route • By the same percentage for every source and complete flexibility by route (down to 0 – case of previous TYNDP) RU, AL, LY, CA, LNG + 5% > Under the supply minimization case, benchmark could be a decrease of the same extent that the increase, the alternative supplies being increased according above options (down to 0 being replaced by up to Potential Supply of the Source) 11

TYNDP 2011-2020 figures

Supply range proposal

2011 FID Russia Norway Algeria Libya LNG

Reference Case Potential yearly supply 95% Import capacity Lower benchmark Reference Case Potential yearly supply 95% Import capacity Lower benchmark Reference Case Potential yearly supply 95% Import capacity Lower benchmark Reference Case Potential yearly supply 95% Import capacity Lower benchmark Reference Case Potential yearly supply 80% Import capacity Lower benchmark 3,800 4,808 6,355 2,792 3,000 3,432 4,171 2,568 1,100 1,203 1,624 997 300 300 306 300 1,800 3,140 4,420 460 27% 67% -27% 14% 39% -14% 9% 48% -9% 0% 2% 0% 74% 146% -74%

2015 FID

4,230 3,339 3,607 1,224 1,237 1,624 310 310 2,003 3,723 5,322 7,915 3,108 4,425 3,071 1,211 5,297 332 310 284 27% 67% -27% 8% 33% -8% 1% 33% -1% 0% 7% 0% 86% 164% -86% Max source Max route Min sources Min route

Maximization

Potential supply

Minimization

Symmetric decrease Some flexibility to be defined or not Same % at source level Up to Potential supply Some flexibility to be defined or not

2020 FID

5,263 3,750 3,750 1,297 1,297 1,624 327 327 2,493 4,600 5,859 7,915 4,667 4,423 3,750 1,297 5,430 332 327 386 11% 50% -11% 0% 18% 0% 0% 25% 0% 0% 1% 0% 85% 118% -85% 12

Physical supply spread

Uniform spread

> Spread shape aims at reaching simultaneously a given supply share threshold (X%) in a maximum number of systems > It models a common reaction to a given stimulus and the ability to physically secure a sell agreement NO +14%

Maximum reach

> Spread shape aims at reaching alternatively a given supply share threshold (X%) in a maximum number of systems NO +14% > It requires several runs to capture maximum ranges (could be based on the ability to replace alternative source one by-one) > It models the ability to physically secure a sell agreement for more remote countries than in the uniform spread (e.g. selling NO gas arriving in UK to the RO market) Both types of spread will use the same source and route range as proposed in previous slide 13

Identification of physical limits

No gap identification

> It would require both: • A consensus on market integration definition and target • To balance cost and benefit of improvement > Some contractual solution may mitigate the lack of supply diversification under business-as-usual conditions (not in case of crisis which are covered within the SoS section of TYNDP)

Identification of physical limits

> Identification should rather derive from a lack of diversification of a given system rather than from a limit to a source spread (e.g. what prevents HU to have a physical access to 20 % of NO gas, rather than what limit the ability to send more NO gas into Europe) 14

Indicators & Gap identification

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Remaining flexibility & investment gaps

Remaining flexibility indicator

> It is defined at 2 levels: • Infrastructure: • System level: > Results are provided as ranges: <1% / 1-5% / 5-20% / >20%

Gap identification criteria

> Under Reference Case (no disruption), gaps are identified when a system has a R. Flex below 5% > In case of disruption, the criteria is decreased to 1% as part of the R. Flex will have been used to face the event > Then congested infrastructure (or supply) are identified based on their R. Flex > Potential remedies will be identified using the non-FID projects provided by project promoters (without priority)

Dependence to flow pattern

High Medium 16

Supply diversification

Impacting supply share

> > > > The share of a given supply source able to induce a significant impact on prices Should it be calculated in comparison with the total supply or the total imports ?

TYNDP 2011-2020 used mostly 5% (identifying also systems with more than 20%) On map, supply shares should be represented with figures or ranges?

Supply diversification from a market perspective

> Could be based on the uniform or maximum spreads > Which is the minimum share of a given source to be considered?

> How to deal with LNG embedded diversification (e.g. highlighting the presence of LNG)?

> Is a benchmark (e.g. 3 sources required)?

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Range of infrastructure use in the cases

Synthetic indicator can be derived from all simulations

> Indicator can be defined for every system: • • • At cross-border level UGS aggregate LNG aggregate > Range would be defined base on the highest and lowest load factor of the 165+ simulations > > Actual use may be outside these ranges Robustness could be improved with a sensitivity study around each simulation modifying slightly the supply shares 100% 80% 60% 40% 20% 0% -20% -40% X-border C1/C2 X-border C1/C3 UGS C1 UGS C2 LNG C1 18

Route diversification

ENtry Capacity Concentration index

> As evolution of market shares is beyond the scope of TYNDP, analysis should focus on how infrastructure can support market integration and SoS >

100%

Then based on the same logic than HHI but calculated on the share of an entry capacity in the total entry (same can be done using the flows but index will then depend on flow pattern)

30%

ENCC= 100²= 10 000

40% 20%

ENCC= 40²+30²+20²+ 10²= 3000

10%

EXit Capacity Concentration index

> Similar indicators may defined based on exit capacity in order to measure how a system may support supply/route diversification > Result should be compared to the idealistic situation taking into account the number of cross-borders As for all indicators, analysis is more robust when comparing situation of one country between 2 cases 19

Security of Supply & Market Integration proposed Cases

List of parameters for modelling

Year Infra. Cluster Demand Case Duration Occurence Disrupti on UGS deliverability Supply source mix

2013 FID 1 day Design Case None No use Reference 2017 Non-FID 2022 2 weeks Year Simultaneous Case AL Average day LY BY UA NO LNG Not limited -x% / Ref Case Crisis Min/max AL Min/max LY Min/max BY Min/max UA Min/max NO Min/max LNG > Current proposal accounts for 165 cases (against 67 for TYNDP 2011-2020), one additional disruption would add 15 cases 20

Thank You for Your Attention

Olivier Lebois, Adviser, System Development ENTSOG -- European Network of Transmission System Operators for Gas Avenue de Cortenbergh 100, B-1000 Brussels EML: T: WWW: [email protected]

+ 32 2 894 5105 www.entsog.eu

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