The future of nuclear power in France: an analysis of the costs of phasing-out

Energy

Volumn 116, Issue , 2016, Pages 908-921

  Malischek, Raimund ^a   Trüby, Johannes ^a  

^a UNIVERSITY OF COLOGNE   (Germany)

Author keywords

Electricity market modeling; France; Investment; Nuclear policy; Uncertainty

Indexed keywords

COSTS; INVESTMENTS; NUCLEAR ENERGY; NUCLEAR POWER PLANTS; OPTIMIZATION; STOCHASTIC MODELS; UNCERTAINTY ANALYSIS;

ADDITIONAL COSTS; ELECTRICITY GENERATION; ELECTRICITY MARKET MODEL; ELECTRICITY SYSTEM; FRANCE; NUCLEAR POLICY; STOCHASTIC OPTIMIZATION MODEL; UNCERTAINTY;

COST BENEFIT ANALYSIS;

COST ANALYSIS; ELECTRICITY GENERATION; ENERGY MARKET; ENERGY POLICY; INVESTMENT; NUCLEAR POWER; NUCLEAR POWER PLANT; UNCERTAINTY ANALYSIS;

FRANCE;

EID: 84992490688     PISSN: 03605442     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.energy.2016.10.008     Document Type: Article

References (30)

1. [1] Bartels, M., Cost efficient expansion of district heat networks in Germany. 2009, Oldenbourg Industrieverlag, Munich.
2. [2] Bertsch, J., Growitsch, C., Lorenczik, S., Nagl, S., Flexibility in Europe's power sector - an additional requirement or an automatic complement?. Energy Econ 53 (2016), 118–131.
3. [3] Cany, C., Mansilla, C., da Costa, P., Mathonnière, G., Duquesnoy, T., Baschwitz, A., Nuclear and intermittent renewables: two compatible supply options? The case of the French power mix. Energy Policy 95 (2016), 135–146.
4. [4] CAS, English version - note de synthèse 263-Énergies 2050. 2012, CAS Tech. rep.
5. [5] CDC, Le coût de production de l’électricité nucléaire. Actualisation 2014 (Rapport public thématique). 2014, CDC Tech. rep.
6. [6] Fürsch, M., Lindenberger, D., Malischek, R., Nagl, S., Panke, T., Trüby, J., German nuclear policy reconsidered: implications for the electricity market. Econ Energy & Environ Policy 1:3 (2012), 39–58.
7. [7] Fürsch, M., Nagl, S., Lindenberger, D., Optimization of power plant investments under uncertain renewable energy deployment paths: a multistage stochastic programming approach. Energy Syst 5:1 (2012), 85–121.
8. [8] Gardner, D.T., Rogers, J., Planning electric power systems under demand uncertainty with different technology lead times. Manag Sci 45:10 (1999), 1289–1306.
9. [9] Gardner, D.T., Flexibility in electric power planning: coping with demand uncertainty. Energy 21:12 (1996), 1207–1218.
10. [10] Gröwe-Kuska, N., Heitsch, H., Römisch, W., 2003. Scenario Reduction and Scenario Tree Construction for Power Management Problems. Paper accepted for presentation at 2003 IEEE Bologna Power Tech Conference.
11. [11] Höffler, F., Wambach, A., Investment coordination in network industries: the case of electricity grid and electricity. J Regul Econ 44:3 (2013), 287–307.
12. [12] Hong, S., Bradshaw, C.J.A., Brook, B.W., Evaluating options for the future energy mix of Japan after the Fukushima nuclear crisis. Energy Policy 56 (2013), 418–424.
13. [13] IEA, World energy outlook - weo model investment costs. 2015 http://www.worldenergyoutlook.org/weomodel/investmentcosts last accessed 24 June 2016.
14. [14] IEA, World energy outlook 2015. 2015, IEA Publications Paris.
15. [15] Jägemann, C., Fürsch, M., Hagspiel, S., Nagl, S., Decarbonizing Europe's power sector by 2050-Analyzing the economic implications of alternative decarbonization pathways. Energy Econ 40 (2013), 622–636.
16. [16] Laleman, R., Albrecht, J., Nuclear and old fossil phase out scenarios: assessment of shortages, surpluses and the load factor of flexible assets with high renewable generation targets – a Belgian case study. Int J Electr Power & Energy Syst 74 (2016), 338–347.
17. [17] Lundgren, K., Patel, T., EDF advances most in 2 months on nuclear extension report: Paris mover., 2012 http://www.bloomberg.com/news/2012-02-13/edf-rises-most-in-2-1-2-months-on-nuclear-report-paris-mover.html last accessed 24 June 2016.
18. [18] Morales, J.M., Pineda, S., Conejo, A.J., Carrión, M., Scenario reduction for futures market trading in electricity markets. IEEE Trans Power Syst, 24(2), 2009.
19. [19] Nagl, S., Fürsch, M., Lindenberger, D., The costs of electricity systems with a high share of fluctuating renewables: a stochastic investment and dispatch optimization model for Europe. Energy J 34:4 (2012), 151–179.
20. [20] Park, N., Yun, S.-J., Jeon, E.-C., An analysis of long- term scenarios for the transition to renewable energy in the Korean electricity sector. Energy Policy 52 (2013), 288–296.
21. [21] Patino-Echeverri, D., Fischebeck, P., Kriegler, E., Economic and environmental costs of regulatory uncertainty for coal-fired power plants. Environ Sci Technol 43:3 (2009), 578–584.
22. [22] Prognos, Energieszenarien für ein Energiekonzept der Bundesregierung. 2010, Prognos AG, EWI and GWS Tech. rep.
23. [23] Richter, J., DIMENSION - a dispatch and investment model for European electricity markets. 2011 EWI Working Paper Series 11/03.
24. [24] Roques, F., Nuttall, W.J., Newberry, D.M., de Neufville, R., Connors, S., Nuclear power: a hedge against uncertain gas and carbon prices?. Energy J 27:4 (2006), 1–24.
25. [25] RTE, Generation adequacy report 2011., 2011, RTE Tech. rep.
26. [26] Shapiro, A., Dentcheva, D., Ruszczynski, A., Lectures on stochastic programming: modeling and theory. 2009.
27. [27] Sun, N., Ellersdorfer, I., Swider, D.J., Model-based long-term electricity generation system planning under uncertainty. Int. Conference on electric utility deregulation and Re-structuring and power technologies (DRPT 2008), 2008.
28. [28] Swider, D.J., Weber, C., The costs of wind's intermittency in Germany. Eur Trans Electr Power 17 (2006), 151–172.
29. [29] UFE, Electricity 2030: the choices for France. 2011, UFE Tech. rep.
30. [30] WNA, World nuclear power reactors & uranium requirements. 2016 http://www.world-nuclear.org/information-library/facts-and-figures/world-nuclear-power-reactors-and-uranium-requireme.aspx last accessed 24 June 2016.