1. 34th IAEE International Conference, Stockholm, June 19-23, 2011Juan Rosellon, CIDE and DIW Berlin Regulated Expansion of Electricity Transmission Networks: the effects of Fluctuating Demand and Wind Generation Schill, Rosellón, Egerer

2. 16 June 20112 Outline Motivation The model Model application Results Conclusions and challenges

3. 16 June 20113 Motivation Starting point: Hogan, Rosellón and Vogelsang (2010) - “HRV“ –Rosellón and Weigt (2011), and Rosellón, Myslikóvá and Zenón (2011): “Seminal, but simplified” Challenges: –Demand and prices vary considerably over a day / over a year –Increasing importance of fluctuating wind power –Comparison to other regulatory regimes Our approach: –Include hourly time resolution and appropriate data –Implement additional regulatory regimes  How will the HRV model perform?

4. 16 June 20114 The model MPEC approach (Rosellón and Weigt, 2011) Dispatch problem (lower level):

5. 16 June 20115 Maximization Transco Problem (upper level)

6. 16 June 20116 Additional equations HRV cap on fix part:

7. 16 June 2011 7 Model application Implementation in GAMS Elmod framework for load flows Stylized central European network TechnologyVariable generation costs in €/MWh Overall available capacity Nuclear964,858 Lignite2915,120 Hard coal3535,064 CCGT4316,358 Gas turbine6516,286 Oil7212,584 Hydro09,841 Wind029,790 Table 1: Variable generation costs and available capacity

8. 16 June 20118 Different cases CaseRepresentation of demandWind generation StaticYearly average DRes144 hours, representing six characteristic days of the yearYearly average WindRes144 hours, representing six characteristic days of the yearFluctuating pattern Hourly reference demand at different nodes Figure 2: Hourly nodal reference demand in DRes and WindRes

9. 6 October 20109 Hourly overall demand and wind pattern Hourly reference prices Figure 3: Hourly nodal reference prices in DRes and WindRes Figure 4: Wind generation and overall reference demand in WindRes

10. 16 June 2011 10 Results: Static  Network extension: HRV closest to WF-max

11. 16 June 201111 Line expansion (Static) Extension: Germany-Netherlands and France-Belgium Figure 6: Time path of overall extension in the Static case

12. 16 June 201112 Results: Static vs. DRes  Demand fluctuations increase extension in wf-max and HRV  Opposite effect in noreg and costreg cases! Social welfare Producer rent Consumer rent Congestion rent Extension costs Transco profit Fixed part WFMax +1.94+19.04-15.57-1.50+0.03-1.50- NoReg +0.13-1.42+1.36+0.19+0.00+0.19- CostReg +0.11-1.43+1.37+0.19+0.01+0.19+0.02 HRV +1.81+13.08-11.13-0.12+0.02+1.68+1.82 Social welfare Producer rent Consumer rent Congestion rent Extension costs Transco profit Fixed part WFMax +2.80+11.13-5.97-2.27+0.08-2.27- NoReg +1.10+1.82-1.13+0.42+0.01+0.41- CostReg +1.06+1.77-1.08+0.41+0.04+0.42+0.04 HRV +2.25+6.59-3.62-0.68+0.04+1.79+2.51

13. 16 June 201113 Price convergence in DRes Figure 18: Convergence of hourly nodal prices under different regulatory approaches in DRes

14. 16 June 201114 WindRes  HRV again closer to wf-max than noreg and costreg Social welfare Producer rent Consumer rent Congestion rent Extension costs Transco profit Fixed part WFMax +2.80+11.13-5.97-2.27+0.08-2.27- NoReg +1.10+1.82-1.13+0.42+0.01+0.41- CostReg +1.06+1.77-1.08+0.41+0.04+0.42+0.04 HRV +2.25+6.59-3.62-0.68+0.04+1.79+2.51 Table 5: Welfare results DRes: Differences to baseline without extension in bn € Social welfare Producer rent Consumer rent Congestion rent Extension costs Transco profit Fixed part WFMax +2.82+11.46-6.31-2.25+0.08-2.33- NoReg +1.09+1.81-1.15+0.44+0.01+0.43- CostReg +1.09+1.99-1.30+0.44+0.05+0.44+0.05 HRV +2.30+6.80-3.69-0.76+0.04+1.79+2.59 Table 6: Welfare results WindRes: Differences to baseline without extension in bn €

15. 16 June 2011 15 Comparison of welfare and extension results  HRV much closer to wf-optimum in all cases  robust!  Fluctuating demand and wind power both increase the gap between wf-max and the regulatory cases Figure 17: Social welfare gain of extension compared to WFMax for different model runs

16. 16 June 201116 Conclusions Details matter in electricity market modelling: –Demand: simplified, static approach systematically underestimates the need for transmission upgrades –Fluctuating wind: further increases expansion requirements HRV is robust against demand and wind fluctuations –WF: HRV closest to wf-max –Extension: HRV also leads to second-highest outcomes –Performance of HRV relative to alternatives increases with more realistic setting! HRV has favourable characteristics for future large-scale wind integration (high extension)  further research necessary

17. 16 June 201117 Challenges Computationally very intensive Data: –Better reference demands and prices –More realistic wind power fluctuations Strong assumptions: –Perfect competition in generation –A single Transco