Evaluation of investments in new power generation using dynamic and stochastic analyses

This paper investigates how dynamic and stochastic optimisation, which is the mathematical foundations of real options theory, can be used to improve power generation investment decisions in restructured and competitive power systems. A stochastic simulator is developed, in order to compare the economic performance of investment decisions based on dynamic vs. static, and stochastic vs. deterministic analyses. The simulator takes into account the value of gradually unfolding information, which is present regardless of investment strategy. Monte Carlo simulations are used to estimate the value of the dynamic and stochastic solutions of the investment problem. Results from a case study of a potential new power plant investment in Norway are presented. In the case study the use of a dynamic investment analysis significantly increases the investor´s expected profit, while the value of a stochastic solution appears to be much lower.