Temporally Coordinated Operation of Green Multi-Energy Airport Microgrids With Climatic Correlations and Flexible Loads via Decomposed Stochastic Programming

To cater to the advancement of electric and hydrogen-powered aircraft, airports are increasingly motivated to transition to green multi-energy airport microgrids (MEAM) for efficient operation and integration of stochastic renewable energy sources (RES). This paper presents a temporally coordinated (two-stage) stochastic programming (SP) model to minimize the energy supply cost of MEAMs while enabling efficient operations with electricity, green hydrogen and thermal energy. From the MEAM perspective, first, the multi-energy loads of MEAMs are considered flexible and modeled in details; second, the electricity-to-hydrogen-and-heat (E2HH) model is applied considering the influence of climatic conditions on the electrolyzers' efficiencies. With regard to the SP model, for one thing, the copula method is employed to capture correlations between climatic parameters related to RES generation and loads to enhance the accuracy and fidelity of the generated scenarios; for another, the Jensen wake model is applied to improve the estimation accuracy of available wind power in the generated scenarios. Furthermore, an adapted-penalty Progressive Hedging (PH) model is proposed to decompose the SP model, reducing the computational burden. Finally, case studies indicate that the proposed approach can effectively coordinate the operation of MEAM to balance system security and cost minimization.