Data-driven multi-objective optimization design of eco-efficient gas circuit breaker

C₄F₇N is considered the most promising SF₆ alternative in high-voltage gas circuit breaker (GCB) due to its low greenhouse effect and high dielectric strength. However, the arc interruption performance of C₄F₇N falls short of SF₆, posing challenges to developing eco-efficient GCB. The present circuit breaker design, dependent on extensive interruption tests or computational fluid dynamics (CFD) simulations, is costly and inefficient, failing to harness the full interruption potential of C₄F₇N. This paper proposes a generic data-driven design framework for multi-objective optimization of GCB. Firstly, a parametric GCB model was established, and several surrogate models were constructed using real CFD simulation data at sampling points. Herein, the global sensitivity analysis methods were employed for design variables screening and interpreting the model behavior. Identified highly sensitive variables encompass the upstream and downstream nozzle inclination as well as chamber height. Subsequently, multi-objective optimization was performed using NSGA-II, with electric field strength/gas flow density (E/ρ) and pressure as optimization objectives. Finally, CFD evaluation of the optimized structures was undertaken to further confirm the validity of the design framework. The results demonstrate the optimization framework effectively improves interruption performance, providing technical guidance to expedite the development of eco-efficient GCB toward achieving a net-zero energy system.