Stochastic optimization considering the uncertainties in the electricity demand, natural gas infrastructures, photovoltaic units, and wind generation

Abstract

The integration of modern generation technologies along with traditional ones awakens interest at the global level. However, the main difficulties to operate these systems are the uncertainties in the predictions of electricity and gas demands, along with the wind and photovoltaic generation. Regarding mathematical programming, the main drawback is the computational effort needed to solve the models that represent the aforementioned items. In this regard, this paper proposes a stochastic model of two-stage that integrates electric power, hydraulic, and natural gas systems. Several effects are considered, not properly addressed in the literature. Besides, to reduce the computational requirement, a Mixed Integer Linear Programming model and a reduction algorithm for scenarios are implemented. To prove the effectiveness of this proposal, an IEEE 31-bus system integrated into a hydraulic and natural gas system is studied. Results demonstrate that the stochastic approach offers cost reductions up to 4% and provides flexibility for contingencies.