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The price of energy security in depressed electricity markets; the case of Belgium

The price of energy security in depressed electricity markets; the case of Belgium. Prof.Dr . Johan Albrecht Faculteit Economie & Bedrijfskunde Second Summer School Economics of Electricity Markets 28/08/2014. Structure. The Belgian context

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The price of energy security in depressed electricity markets; the case of Belgium

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  1. The price of energy security in depressed electricity markets; the case of Belgium Prof.Dr. Johan Albrecht Faculteit Economie & Bedrijfskunde Second Summer School Economics of Electricity Markets 28/08/2014

  2. Structure • The Belgian context • ‘Security of supply’ has twodimensions: follow peak demand & avoidexcessiveoverproduction (intermittent RES) • ‘No Policy’ scenario; notsustainable • ‘Security of supply’ scenarios ; new assets, oldthermalassets, DSM & combinations • Surplus risk assessment • Conclusions

  3. The Belgian Context • Firmcapacity of 15 700 MW (13 000 MW today) • Nuclearphase-out: 5 900 MW

  4. Changing Load Factors (LF)

  5. RES <-> Gas

  6. Wholesale prices in CWE

  7. Peak Load; decreasing?

  8. Plan Wathelet • Extension Tihange 1, 800 MW CCGT, 400 MW DSM

  9. Reserve Margin (RM) 2012/2013

  10. RM in ‘No Policy’ scenario

  11. Supply scenariosfor Belgium • Policy options; incentives forflexiblegeneration(new andoldtermal), DSM, CFD for RES (with/without Market Participation (MP)) • Investment and system cost of policy options? (with8% discount rate, LCOE-approach) • Assumptions on context; peak demand + 0,5%/yr, carbon price up to € 40 per ton CO2 in 2030, endogenousprice model (more RES -> lowerwholesaleprices), networkcostsincreasewith RES share

  12. LCOE assumptions

  13. Endogenousprice model

  14. Prices in NEA for DE

  15. Network costs as f(RES)

  16. Security of supply; RM > 5% at alltimes • IF (‘No Policy’ RM < 5%) THEN model triggers CCGT, OCGT & Biomassinvestments • Context: oldthermal, DSM, BAU RES and High RES

  17. New capacity; split up

  18. Incentive schemes • Capacitypaymentsfor CCGT (€ 900/kW), OCGT (€ 700/kW) andBiomass (€ 1050/kW) • RES support per MWh (incl. Biomass) ; CFD = LCOE minusprice • CFD-MP includescurtailment (max 5% PV, max 14% wind) • CFD-MP; lower LF, higher LCOE, higher CFD

  19. Old Thermal & DSM • end of 1 300 MW OT scheduledfor 2014-2024; in reserve capacity, 5% LF @ € 95/MWh (€ 50 to 60 mill) • DSM clearing prices of € 150/MW/day (based on UBS)

  20. Firmcapacity in 2030; 18 GW / RM 9% Peak demand of 14,7 GW in 2030 Gas dominates / oldthermal; end of life in 2024 Biomass; 3 000 – 3 500 MW in BAU RES / 4 000 – 4 500 MW in High RES

  21. Total capacity in 2030; 25 – 30 GW

  22. Electricity production in 2030 CFD-MP; Biomassused in flexible way -> higher LF for CCGT Share of RES in 2030: from 28% in BAU RES CFD-MP to 60% in High RES CFD

  23. Generation portfolio LF

  24. WP Bureau Fédéral du Plan, 2013

  25. Annualsubsidycost: cap pay + CFD • Allresults: additionaltosubsidycost of 2014 • One-off capacitypayments in year of investment

  26. Cumulativecost up to 2030; € 21 and € 41 bill-> MP of RES matters!

  27. Optimalframeworksand RES share? • Trade-off between RES share andcosts is notlinear

  28. LCOE generation mix, 2012-2030

  29. Total annual system costs (gen+netw)

  30. Total costsand RES share

  31. Cumulative System Costs 2014-2030

  32. Cumulative System Costs & RES-share (2030)

  33. CumulativeSubsidyCosts & Cumulative System Costs (2014-2030)

  34. Surplus risks? • Onlywith ‘New Capacity’ scenarios • Random PV & wind generation in Matlab (10 000 patterns), based on Elia • ‘Must-run’; biomass (MP), CHP & nuclear • Comparedtodemandvariation in 15 min intervals • Demand (15 min) <-> (RES + Must Run) • Export capacity of 3 500 MW; surplus of 3 000 is problematic • DSM (toincreasedemand); herenotincluded

  35. Illustration of PV+wind output for 29 days

  36. 2014 Surplus Risk

  37. 2017 Surplus Risk

  38. 2023 Surplus Risk

  39. 2027 Surplus Risk

  40. Overview Surplus Analysis

  41. Nuclearprolongation; 3 GW NUC in 2030

  42. Conclusions 1

  43. Conclusions 2 • To secure 5% RM, cumulativesubsidycosts up to 2030 varybetween € 21 and € 41 billion • Smart policy choiceswilllowercostsfor society, even at relatively high RES shares • Market participationby RES is essentialtofacilitatefurtherexpansion of RES • DSM lowerscosts / Old thermal; limitedrelevance • limitations of this analysis; capacitypayments as institutionalchallenge (end of EOM?), recovery of demand, delocalisationenergy-intensiveindustries, evolution of interconnection, arrival of smart grid, share of electricvehiclesby 2030, EC climatepolicies,…

  44. Thankyouforyour attention • Johan.albrecht@ugent.be • Second Summer School ‘Economics of Electricity Markets’ @ Ghent University, August 25-29, 2014 • http://www.ceem.ugent.be/SummerSchools/2014/index.htm

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