The costs of electricity systems with a high share of fluctuating renewables: A stochastic investment and dispatch optimization model for europe

Energy Journal

Volumn 34, Issue 4, 2013, Pages 151-179

  Nagl, Stephan ^a   Fürsch, Michaela ^a   Lindenberger, Dietmar ^a  

^a UNIVERSITY OF COLOGNE   (Germany)

Author keywords

Electricity; Renewable energy; Stochastic programming

Indexed keywords

EID: 84886041911     PISSN: 01956574     EISSN: None     Source Type: Trade Journal    
DOI: 10.5547/01956574.34.4.8     Document Type: Article

References (34)

1. Beenstock, M. (1995). "The stochastic economics of windpower." Energy Economics 17, 22-37. http://dx.doi.org/10.1016/0140-9883(95)98904-I
2. Benders, J. (1962). "Partitioning procedures for solving mixed-variables programming problems." Numerische Mathematik 4, 238-252. http://dx.doi.org/10.1007/BF01386316.
3. Birge, J. and Louveaux, F. (1997). Introduction to Stochastic Programming. New York: Springer.
4. Buijs, P., Bekaert, D., Cole, S., Hertem, D. V. and Belmans, R. (2011). "Transmission investment problems in Europe: Going beyond standard solutions." Energy Policy 39, 1794-1801.
5. Conejo, A., Carrion, M. and Morales, J. (2010). Decision Making Under Uncertainty in Electricity Markets. New York: Springer
6. Dantzig, B. (1955). "Linear programming under uncertainty." Management Science 1, 197-206
7. DeCarolis, J. and Keith, D. (2006). "The economics of large scale wind power in a carbon constrained world." Energy Policy 34, 395-410 (Pubitemid 41600330)
8. EEA (2009). "Europe's onshore and offshore wind energy potential-an assessment of environmental and economic constraints." Tech. rep., Coppens, C., Gordijn, H., Piek, M., Ruyssenaars, P., Schrander, J., de Smet, P., Swart, R., Hoogwijk, M., Papalexandrou, M., Visser, E., Horalek, J., Kurfürst, P., Jensen, F., Petersen, B., Harfoot, M., Milego, R., Clausen, N., and Giebel, G. (prepared by the European Environmental Agency
9. Efron, B. (1979). "Bootstrap methods: Another look at the jackknife." The Annals of Statistics 7, 1-26
10. ENTSO-E (2011a). "Yearly electricity consumption data for Europe." Available at https://entsoe.eu/ index.php?id = 92 (accessed 31 October 2012).
11. EuroWind (2011). Database for hourly wind speeds and solar radiation from 2006-2010 (not public).
12. EWI (2010). "European RES-E policy analysis-a model based analysis of RES-E deployment and its impact on the conventional power market." Tech. rep., Fürsch, M., Golling, C., Nicolosi, M., Wissen, R. and Lindenberger, D. (Institute of Energy Economics at the University of Cologne).
13. EWI (2011). Roadmap 2050-a closer look. Cost-effcient RES-E penetration and the role of grid extensions. Tech. rep., Fürsch, M., Hagspiel, S., Jägemann, C., Nagl, S., and Lindenberger, D. (Institute of Energy Economics at the University of Cologne) Glotzbach, L., Tröster, E., and Ackermann, T. (energynautics
14. Fleten, S., Stein, W. and Ziemba, W. (2002). Hedging electricity portfolios via stochastic programming. IMA Volumes on Mathematics and its Applications 128, 71-93. http://dx.doi.org/10.1007/ 978-1-4684-9256-9-4
15. Fripp, M. (2008). Optimal investment in wind and solar power in California. Ph.D. thesis, Energy and Resource Group at the University of California, Berkeley
16. Heide, D., Bremen, L., Greiner, M., Hoffmann, C., Speckmann, M. and Bofinger, S. (2010). Seasonal optimal mix of wind and solar power in a future, highly renewable Europe. Renewable Energy 35, 2483-2489. http://dx.doi.org/10. 1016/j.renene.2010.03.012
17. Hobbs, B. and Maheshwari, P. (1990). A decision analysis of the effect of uncertainty upon electric utility planning. Energy 15, 785-801. http://dx.doi.org/10.1016/0360-5442(90)90118-L.
18. Joskow, P. (2011). Comparing the costs of intermittent and dispatchable electricity generating technologies. The American Economic Review 101, 238-241. http://dx.doi.org/10.1257/aer.101.3.238
19. Modiano, E. (1987). Derived demand and capacity planning under uncertainty. Operation Research 35, 185-197. http://dx.doi.org/10.1287/opre.35. 2.185. (Pubitemid 17652595)
20. Mount, T., Maneevitjit, S., Lamadrid, A., Zimmerman, R. and Thomas, R. (2011). The hidden system costs of wind generation in a deregulated electricity market. The Energy Journal 33, 161-186
21. Möst, D. and Keles, D. (2010). A survey of stochastic modelling approaches for liberalised electricity markets. European Journal of Operational Research 207, 543-556. http://dx.doi.org/10.1016/ j.ejor.2009.11.007
22. Murphy, F., Sen, S. and Soyster, A. (1982). Electric utility capacity expansion planning with uncertain load factors. IIE Transactions 14, 52-59. http://dx.doi.org/10.1080/05695558208974582. (Pubitemid 13541856)
23. Nagl, S., Fürsch, M. and Lindenberger, D. (2012). The costs of electricity systems with a high share of fluctutating renewables-a stochastic investment and dispatch optimization model for Europe (Working Paper No. 12/01) Institute of Energy Economics at the University of Cologne. URL http://www.ewi.uni-koeln.de/publikationen/working-papers/
24. Neuhoff, K., Ehrenmann, A., Butler, L., Curst, J., Hoexter, H., Keats, K., Kreczko, A. and Sinden, G. (2008). Space and time: Wind in an investment planning model. Energy Economics 30, 1990-2008. http://dx.doi.org/10.1016/j. eneco.2007.07.009. (Pubitemid 351673985)
25. Papaefthymiou, G., Schavemaker, P., van der Sluis, L., Kling, W., Kurowicka, D. and Cooke, R. (2006). Integration of stochastic generation in power systems. Electrical Power and Energy Systems 28, 655-667. http://dx.doi.org/10.1016/j.ijepes.2006.03.004. (Pubitemid 44416455)
26. Paulus, M. and Borggrefe, F. (2011). The potential of demand-side management in energy-intensive industries for electricity markets in Germany. Applied Energy 88, 432-441. http://dx.doi.org/ 10.1016/j.apenergy.2010.03.017.
27. Prognos/EWI/GWS (2010). Energieszenarien für ein Energiekonzept der Bundesregierung. Tech. rep., Schlesinger, M., Hofer, P., Kemmler, A., Kirchner, A. and Strassburg, S. (all Prognos AG); Lindenberger, D., Fürsch, M., Nagl, S., Paulus, M., Richter, J. and Trüby, J. (all EWI); Lutz, C., Khorushun, O., Lehr, U., and Thobe, I (GWS mbH
28. Richter, J. (2011). DIMENSION-A dispatch and investment model for European electricity markets (Working Paper No. 11/03) Institute of Energy Economics at the University of Cologne.
29. Rosen, J., Tietze-Stöckinger, I. and Rentz, O. (2007). Model-based analysis of effects from largescale wind power production. Energy 32, 575-583. http://dx.doi.org/10.1016/j.energy.2006.06.022 (Pubitemid 44959524)
30. Sen, S. and Higle, J. (1999). An introductory tutorial on stochastic linear programming models. Interfaces 29, 33-61. http://dx.doi.org/10.1287/inte. 29.2.33
31. Short, W., Blair, N. and Heimiller, D. (2003). Wind deployment system (WinDS) model. Tech. rep., National Renewable Energy Laboratory. URL http://www.nrel.gov/analysis/
32. Sun, N., Ellersdorfer, I. and Swider, D. (2008). Model-based long-term electricity generation system planning under uncertainty. In: Int. Conference on Electric Utility Deregualtion and Re-structuring and Power Technologies (DRPT 2008). pp. 1298-1304
33. Swider, D. and Weber, C. (2006). The costs of wind's intermittency in Germany: Application of a stochastic electricity market model. European Transactions on Electrical Power 17, 151-172. http:// dx.doi.org/10.1002/etep. 125
34. Weber, C. (2005). Uncertainty in the Electric Power Industry. New York: Springer.