Pricing asset scheduling flexibility using optimal switching

We study the financial engineering aspects of operational flexibility of energy assets. The current practice relies on a representation that uses strips of European spark-spread options, ignoring the operational constraints. Instead, we propose a new approach based on a stochastic impulse control framework. The model reduces to a cascade of optimal stopping problems and directly demonstrates that the optimal dispatch policies can be described with the aid of 'switching boundaries', similar to the free boundaries of standard American options. Our main contribution is a new method of numerical solution relying on Monte Carlo regressions. The scheme uses dynamic programming to efficiently approximate the optimal dispatch policy along the simulated paths. Convergence analysis is carried out and results are illustrated with a variety of concrete computational examples. We benchmark and compare our scheme with alternative numerical methods.