To address the scheduling challenges in interconnected multi-microgrid systems

this paper proposes a dimensionality-reduction projection-based scheduling method. Firstly

a centralized operational model of the interconnected multi-microgrid system is constructed and decomposed into sub-problems for individual microgrids. By utilizing the dimensionality reduction projection method

the operational spaces of these sub-problems are mapped into lower-dimensional spaces

allowing for the establishment of reconstructed convex hulls of the sub-problems. Through solving the optimization problem under reconstructed convex hull constraints

the operational costs of sub-microgrids and values of coupling variables under optimal system costs are obtained. The acquired coupling variable values enable the determination of optimal power flow distributions among sub-microgrids at minimum cost. This methodology inherently conceals proprietary information during computation

eliminates iterative processes

thoroughly protects user privacy

and preserves optimality information. Comprehensive tests on both two-area 8-node and two-area 66-node interconnected multi-microgrid systems demonstrate the effectiveness of the proposed method in terms of computational efficiency

privacy preservation

and optimal performance

thereby validating its technical advantages.