Stochastic modeling of the energy supply system with uncertain fuel price – A case of emerging technologies for distributed power generation

A deterministic energy supply model with bottom-up structure has limited capability in handling the uncertainties. To enhance the applicability of such a model in an uncertain environment two main issues have been investigated in the present paper. First, a binomial lattice is generated based on the stochastic nature of the source of uncertainty. Second, an energy system model (ESM) has been reformulated as a multistage stochastic problem. The result of the application of the modified energy model encompasses all uncertain outcomes together and enables optimal timing of capacity expansion. The performance of the model has been demonstrated with the help of a case study. The case study has been formulated on the assumption that a gas fired engine competes with renewable energy technologies in an uncertain environment where the price of natural gas is volatile. The result of stochastic model has then been compared with those of a deterministic model by studying the expected value of perfect information (EVPI) and the value of stochastic solution (VSS). Finally the results of the sensitivity analysis have been discussed where the characteristics of uncertainty of the price of fuel are varied.

► An existing bottom-up deterministic energy system model (ESM) has limited capability in handling the uncertainties.
► Uncertainty has been modeled based on GBM. Probabilistic scenarios are generated based on Cox–Ross method.
► A multistage stochastic model has been developed where scenarios are integrated in the energy system model.
► A distributed generation system has been introduced as a case study where fuel price is considered as an uncertain parameter.