Robust scheduling of integrated electricity and gas systems: A cost and flexibility assessment

Gas-fired generators and power-to-gas units support the deployment of variable renewable energy in integrated electricity and gas systems (IEGS) by absorbing the fluctuations in electricity generation and demand. The economical and secure operation of IEGSs with high variable renewable energy penetration requires coordinated uncertainty-aware decision support. This paper proposes an adaptive robust optimization for IEGS scheduling, which minimizes the base-case costs, while ensuring security against generation and demand uncertainties with full-recourse rescheduling. The AC power flow and dynamic gas flow equations are convexified using second- order cone relaxations and treated by sequential convex programming to recover feasible solutions. We assess the flexibility of the solutions in response to the realized uncertainties. Computational experiments on the modified IEEE 39-bus system and the Swiss natural gas system show that sequential convex programming reduces demand shedding by 79%-100% and variable renewable energy curtailment by 1%-68%. Robust scheduling prevents demand shedding at 1%-7% additional cost due to the need for additional generation from conventional generators. Power-to-gas enhances variable renewable energy utilization by synthesizing methane from excess renewable energy, especially when the system lacks other flexible resources.