：With the continuous development and refinement of microgrid technology, the uncertainty of sources and loads has increasingly drawn attention to the safe and stable operation of microgrids. In order to address the issues of safety, stability, and optimal economic operation of microgrids, this paper establishes a two-layer microgrid economic optimization model that considers power source-load uncertainty and proposes a hybrid scenario reduction strategy based on Latin Hypercube Sampling and probability distance. In the upper-level model, the impact of various source-load uncertainty scenarios on the economic operation of microgrids is studied. In the lower-level model, the LHS-PD method is used to convert the problem into a stable situation for economic optimization. Finally, a Harris Hawk Algorithm using a hybrid strategy is proposed to solve the two-layer optimization model. Numerical comparisons with test functions have verified that the proposed algorithm has good solution accuracy and convergence speed. Simulation results have confirmed the effectiveness of the two-layer optimization model and the superiority of the algorithm in optimizing the economic operation of microgrids.