TH`ESE Docteur de l'Université Paris-Dauphine Morgan HERVÉ ...

List of Tables
1.1 Key operating data on top 10 European utilities . . . . . . . 31
1.2 Sample abatement costs . . . . . . . . . . . . . . . . . . . . . 33
2.1 Capital expenditures for RWE and E.ON - in EUR million . . 57
2.2 Generation operating investment classified by group . . . . . 61
2.3 Financial operations classified by year . . . . . . . . . . . . . 67
2.4 Financial operations classified by group . . . . . . . . . . . . 68
3.1 Net cash flows sample calculation . . . . . . . . . . . . . . . . 97
3.2 Net present value calculation . . . . . . . . . . . . . . . . . . 98
3.3 Expected NPV calculation . . . . . . . . . . . . . . . . . . . . 100
3.4 Pros and cons of scenarios . . . . . . . . . . . . . . . . . . . . 101
3.5 Sensitivity analysis sample calculation: sale price (P) and
quantity sold (Q) . . . . . . . . . . . . . . . . . . . . . . . . . 101
3.6 Pros and cons of sensitivity analysis . . . . . . . . . . . . . . 102
3.7 Pros and cons of simulations . . . . . . . . . . . . . . . . . . 103
3.8 Pros and cons of decision tree analysis . . . . . . . . . . . . . 106
3.9 Payback calculation . . . . . . . . . . . . . . . . . . . . . . . 107
3.10 Discounted payback calculation . . . . . . . . . . . . . . . . . 107
3.11 Financial vs. real options terminology . . . . . . . . . . . . . 121
3.12 Parameters for the carbon price process . . . . . . . . . . . . 136
3.13 Parameters for the power price processes . . . . . . . . . . . . 140
3.14 Correlation among stochastic price processes . . . . . . . . . 141
3.15 Power plant assumptions . . . . . . . . . . . . . . . . . . . . . 146
16 Survey of carbon price stochastic modelling . . . . . . . . . . 190
17 Illustrative case - Price paths for baseload power . . . . . . . 194
18 Illustrative case - Implied NPV paths for technology B . . . . 195
19 Illustrative case - Decision nodes at t=2 and optimal decision
for untapped budget . . . . . . . . . . . . . . . . . . . . . . . 196
20 Illustrative case - Value function vs. budget level at t=2 . . 196
21 Illustrative case - Optimal decision vs. budget level at t=2 . 196
22 Illustrative case - Sample OLS regression data . . . . . . . . . 198
23 Illustrative case - Decision nodes at t=1 and optimal decision
for untapped budget . . . . . . . . . . . . . . . . . . . . . . . 199
24 Illustrative case - Value function vs. budget level at t=1 . . . 199
25 Illustrative case - Optimal decision vs. budget level at t=1 . . 199
26 Illustrative case - Decision nodes at t=0 and optimal decision
for initial budget . . . . . . . . . . . . . . . . . . . . . . . . . 200
27 Appendix - MRt -Immediaterewardcomponentofthevalue
function in t . . . . . . . . . . . . . . . . . . . . . . . . . . . . 203
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