Market Integration & SoS Updated proposals for SJWS #6 ENTSOG offices – Brussels Stakeholder Joint Working Session – 26 April 2012

SJWS process on SoS & Market Integration 2 February session – Come-back to TYNDP > 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 June TYNDP Public WS Feb. 15th Mar. 20th April 26th May ?

Security of Supply & UGS low deliverability 3

Security of Supply – potential events 4 List of extreme but still realistic events will be slightly updated > Considered list could be complemented at GRIP level for specific focus SourceTechnicalTransitSupply Algeria 100% MEG & 100% Transmed separately Caspia100% (dealt within the FID case) Libya100% Green stream LNGExpecting for update GLE study Norway 100% Langeled & 100% other connection (worst case to be tested) or process plant (see GASSCO) ? Russia 100% Ukraine & 100% Belarus separately

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 tank management > 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 LNG as import LNG as storage

Security of Supply – Event management 6 Management of disruption or low UGS deliverability cases > Supply priority is: 1. Disrupted supply through alternative routes 2. Alternative imports (including LNG until maximum potential supply as import) 3. LNG (using remaining capacity up to send-out capacity) and UGS 4. 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

Security of Supply – Low UGS 7 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% 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

Security of Supply – 2-week case 8 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 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 Modeled day

Market Integration & Supply diversification 9

Predominant supply 10 Which benchmark ? > In comparison with Reference Case supply share (full color), potential benchmarks are: X% of import capacity (TYNDP with 95% for pipe and 80% LNG) Potential supply of the source +Y% increase in comparison with Ref. Case 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 Russia Norway LNG

Alternative supplies 11 Influence of each supply source will be considered separately 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) > 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) RU, AL, LY, CA, LNG + 5% NO - 14%

Supply range proposal 12 MaximizationMinimization Max sourcePotential supplySymmetric decrease Max routeSome flexibility to be defined or not Min sourcesSame % at source levelUp to Potential supply Min routeSome flexibility to be defined or not TYNDP figures

Physical supply spread 13 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 Maximum reach > Spread shape aims at reaching alternatively a given supply share threshold (X%) in a maximum number of systems > 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 NO +14%

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 15

Remaining flexibility & investment gaps Remaining flexibility indicator > It is defined at 2 levels: Infrastructure: System level: > Results are provided as ranges: 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) 16 Dependence to flow pattern High Medium

Supply diversification 17 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 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)?

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 18 > Actual use may be outside these ranges > Robustness could be improved with a sensitivity study around each simulation modifying slightly the supply shares

Route diversification 19 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 > 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) 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 100% 40% 30% 20% 10% ENCC= 100²= ENCC= 40²+30²+20²+ 10²= 3000 As for all indicators, analysis is more robust when comparing situation of one country between 2 cases

Security of Supply & Market Integration proposed Cases 20 List of parameters for modelling > Current proposal accounts for 165 cases (against 67 for TYNDP ), one additional disruption would add 15 cases YearInfra. Cluster Demand Case Duration Occurence Disrupti on UGS deliverability Supply source mix 2013FID1 dayDesign CaseNoneNo useReference 2017Non-FID2 weeksSimultaneous CaseALNot limitedCrisis 2022YearAverage dayLY-x% / Ref CaseMin/max AL BYMin/max LY UAMin/max BY NOMin/max UA LNGMin/max NO Min/max LNG

21 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 T: WWW: