KO algorithm-based bi-level optimal scheduling of electricity-carbon-hydrogen coupling systems with flexible resources for renewable energy integration

• Electricity-carbon-hydrogen coupling system with multiple flexible resource is presented. • Bi-level optimal scheduling model with dynamic load balance is proposed. • Kepler optimization algorithm is adopted and shows superior performance. • Better economic/environmental benefits and less load shedding are obtained. As renewable energy penetration keeps growing, its intermittent nature poses huge challenges on the reliable and flexible operation of power systems. The uncertainty and reverse peak shaving characteristics of renewable energy further exacerbate issues of load shedding and renewable energy curtailment. Additionally, both carbon trading and hydrogen energy which play important roles in reducing carbon emissions have attracted great attention. A novel bi-level optimal scheduling model of the electricity-carbon-hydrogen coupling system is proposed considering carbon trading, load flexibility and deep peak shaving. The model simultaneously minimizes load shedding, renewable energy curtailment and the operation cost. Moreover, the Kepler optimization (KO) algorithm is applied and benchmarked against flower pollination (FP) algorithm and particle swarm optimization (PSO) algorithm. Finally, comparative studies confirm that incorporating flexible resources (flexible load and deep peak shaving) significantly reduce renewable curtailment, eliminate load shedding, and lower operation cost. Furthermore, the newly introduced KO algorithm demonstrates superior performance over both FP and PSO algorithms across all evaluated metrics.