A Bi-Level Operational Optimization Strategy for Distributed Contry-level Smart Grids Based on the Concept of Balancing Zones

As a crucial component of modern energy systems, the country-level power distribution system is facing challenges related to low-carbon and secure operations considering the high-proportion distributed renewable energy injection. Under the carbon peaking and carbon neutrality ("dual carbon" goals) target, the distributed smart grid—a key technology of the next-generation power distribution system—is proposed to solve the problem of rational scheduling of large amounts of flexibility resources. This provides a feasible plan for country-level power distribution system.Based on a cloud-edge-end collaborative control architecture for distributed smart grids, this paper proposes a bi-level operational optimization strategy founded on the concept of balancing zones. The strategy addresses the challenge of optimal scheduling for large-scale flexible resources in distributed smart grids. The upper-level optimization aims to minimize active power loss and suppress voltage deviations, while the lower-level optimization focuses on minimizing the operating costs of distributed units and penalties associated with wind and solar curtailment. Numerical results from a case study using a modified IEEE 37-node power test system with several scenarios demonstrate that the proposed bi-level optimization algorithm effectively suppresses voltage deviations, reduces power losses, and improves the consumption rate of renewable energy. This strategy provides a theoretical reference for the practical application of distributed smart grids.