A Coordinative Stochastic Optimization Dispatch Strategy for Multi-type- hydrogen Production Systems Oriented to Wind-solar Power Accommodation

To enhance the accommodation capacity of wind and solar power, this study proposes a stochastic optimal scheduling strategy characterized by the coordinated operation of alkaline electrolyzer (ALK) and proton exchange membrane electrolyzer (PEM) units. Methodologically, by leveraging the different operating characteristics of the two types of hydrogen production units, a dual-scenario scheduling framework considering both wind and solar power surplus and deficiency is constructed. To address the uncertainty of wind and solar power output, an improved K-means clustering algorithm based on Mahalanobis depth and weighted similarity is introduced to generate typical operational scenarios, thereby improving the representativeness of the generated scenarios. Furthermore, a mixed integer linear programming model that minimizes system operating costs is established, comprehensively considering economic factors such as hydrogen production revenue, operation and maintenance costs, and curtailed power costs. Simulation results demonstrate that the proposed coordinated scheduling strategy for multi-type hydrogen production units can fully utilize the differentiated operational characteristics of the two types of electrolyzers. In comparison with the single-type scheme, it can further improve the accommodation capacity of wind-solar power.