Distributed robust operation of integrated energy system considering gas inertia and biogas-wind renewables

Multiple uncertainties caused by renewable energy and loads bring challenges to the secure operation of integrated energy system (IES). Concurrently, the centralized control methods based on global information of IES cannot preserve the data privacy of each individual subsystem. To deal with these issues, this paper proposes a distributed two-stage robust optimization (TRO) scheduling strategy for IES considering gas inertia and biogas-wind renewables. To address the uncertainties of wind turbines output and electricity loads in IES, a TRO model is first established, and the column and constraint generation (C&CG) algorithm is employed to handle the min-max-min problem of TRO model. On this basis, a distributed cooperative scheduling framework based on the consensus-based alternating direction method of multipliers (C-ADMM) for IES is developed, which requires no overall system information but only local information. Additionally, natural gas pipelines that consider gas inertia are used as gas storage facilities, which provides IES with additional scheduling resources and flexibility. Furthermore, an adaptive step-size strategy is proposed to adjust the step-size of ADMM in real time, which reduces the dependence of ADMM performance on the initial parameters selection and improves its convergence performance. The simulation results in a three-subsystem joint IES are presented to demonstrate the effectiveness of the proposed distributed TRO scheduling strategy.

Automated summary

This paper proposes a distributed two-stage robust optimization (TRO) scheduling strategy for integrated energy systems (IES) to address uncertainties caused by renewable energy and loads. The strategy ensures data privacy of individual subsystems and utilizes gas inertia and biogas-wind renewables. The simulation results of a three-subsystem joint IES demonstrate the effectiveness of the proposed strategy.