Gas storage valuation applying numerically constructed recombining trees

The liberalization of European natural gas markets forces market participants to base their decisions on market prices. For owners and operators of natural gas storage facilities it is therefore necessary to take market prices into account for their decisions. In this framework this paper provides a new approach for the valuation of natural gas storage facilities. Using stochastic dynamic programming on multinomial recombining trees, the optimal storage strategy and value are determined. For this we (i) estimate the deterministic and random impacts on natural gas prices, (ii) simulate gas prices considering the results of the first step, (iii) construct numerically the recombining tree using the simulation results, (iv) determine the optimal storage strategy and value. Besides the determination of the optimal storage value and operation schedule the value quantiles are calculated. Via the quantiles relevant risk measures like value at risk and conditional value at risk are determined.

► We valuate natural gas storages applying numerical constructed recombining trees. ► We prove the convergence of the proposed approach. ► We calculate the value distribution and the Conditional Value at Risk (CVAR). ► Adding the CVAR to the objective function decreases the value disproportionate to the risk. ► The performance of our approach is compared to methods like Least-Squares-Monte-Carlo.