Analysis of Transmission Investments using Real Options

Optimal investment strategies for distributed generation in distribution networks with real option analysis

“…Real option valuation methods can be broadly classified into three categories: analytic methods like the Black–Scholes model [31], binomial or trinomial trees [26, 27, 29, 33], and the Monte Carlo simulation (MCS) method [22, 23, 30, 32, 34]. Real option models often exhibit high complexity as a mixed‐integer linear/non‐linear problem.…”

Buying real options – Valuing uncertainty in infrastructure planning

“…Security of supply and development of price differentials in particular are drivers for investing in multi-fuel electricity generation facilities. In general, electricity generation companies have been rather quick in realising the added value of real option valuation in asset and risk management, in contrast with companies in the network business [27]. An application example in the US is related to the sale of CHP units (also known as cogeneration): ''Competitors outbid utilities often for the purchase of cogeneration plants.…”

Flexibility Value of Distributed Generation in Transmission Expansion Planning

“…the investment option is exercised, not only the deferment choice disappears but also all the other investment choices (Kirschen & Strbac, 2004). The value of the lost option, analogous to a financial call option, is an opportunity cost, which depends on the project's irreversibility as well as on the existing risk and flexible embedded options at the decision time (Dixit & Pindyck, 1994;Ramanathan & Varadan, 2006). However, classical project appraisal methods overlook this interaction even though, in practice, it evidently affects the planner's decisions.…”

“…Since flexibility can only be assessed by comparison (Ku et al, 2003;Gorenstin et al, 1993), the value of a flexible option is assessed by comparing its coefficient of variation with the coefficient of variation of a feasible inflexible reference strategy (flexibility = 0) belonging to the set of feasible expansion plans S k . This basic procedure can be systematically extended into a multi period strategies comparison problem and solved by using the dynamic programming formulation expressed in (9) and (10) (Dixit & Pindyck, 1994;Ramanathan & Varadan, 2006 Going backward in dynamic programming allows decomposing a whole sequence of decisions into just two components: the immediate decision and a valuation function which encapsulates the consequences of all the subsequent future decisions. As shown in Fig.…”