A Stochastic Two-Stage Model for the Integrated Scheduling of the Electric and Natural Gas Systems

Abstract

The inherent coupling of the electric and natural gas systems due to the operation of gas generating units and power-to-gas facilities, along with the uncertainties faced in both systems due to the variability in electricity and gas demand and the vastly increasing volatile renewable injections, create an imperative need to schedule and operate the two systems in a coordinated manner. In this paper a new model for the fully integrated stochastic day-ahead scheduling of electric and gas systems is presented, coping with the uncertainties of both systems. The stochastic parameters comprise the electricity demand and the renewable injections, which collectively create several net electricity load scenarios, and the gas residential/industrial demand. The integrated scheduling problem concerns a unit commitment for the electricity problem, amended with additional constraints imposed by the underlying natural gas transmission system considering steady-state flow. A two-stage stochastic programming model is devised, having as second stage the possible realizations of net electricity load and gas demand in real-time. The model is tested in medium-size real-world test systems - the Greek electricity and gas systems - deriving useful insights on the advantages of the integrated stochastic scheduling versus the deterministic scheduling of the electricity and gas systems.

Keywords

• Electricity system
• natural gas system
• integrated scheduling
• mixed integer linear programming
• two-stage stochastic programming