Planning of Energy Router Siting and Sizing for Load Supply Assurance Under Typical N-1 Scenarios

Ensuring continuous load supply under N-1 contingencies poses a significant challenge for active distribution networks. Traditional fault recovery relies on mechanical tie switches for network reconfiguration; however, such rigid interconnections often fail due to severe terminal voltage drops during long-distance load transfers, leading to forced load shedding. To address this, this paper proposes an optimal planning framework for Electric Energy Routers (EERs) to secure load supply, aiming to maximize load preservation within investment budget constraints. First, a bi-level robust optimization model is constructed: the upper level determines the optimal EER configuration to minimize load shedding in the worst-case N-1 scenarios, while the lower level evaluates the optimal restoration strategies via mixed-integer second-order cone programming. To handle the inherent complexity of discrete–continuous variable coupling and the computational burden of the bi-level structure, a novel topological manifold evolution algorithm based on Wasserstein geometric flow is developed. By embedding the electrical topology into a sensitivity-driven Riemannian metric field, the algorithm effectively enhances global optimization capabilities. Case studies on the IEEE 33-node system demonstrate that the integration of EERs facilitates a transition from rigid to flexible interconnection, circumventing power transfer bottlenecks caused by low voltage through controllable power flow. Compared with baseline schemes, the optimal EER scheme reduces load shedding in the worst-case scenario by 60.3%, providing a robust and economical solution for high-resilience distribution network planning.