Two-Stage Resilient Recovery of Unbalanced Distribution System Considering Intelligent Zoning and Merging of Microgrids

Abstract

Increasingly extreme events are threatening the resilience of distribution systems. Conventional research usually ignores the distribution system unbalance and microgrid flexibility. Typical resilient recovery aims to minimize load shedding, but the corresponding strategy may lead to an unacceptable recovery duration. To overcome these problems, a two-stage recovery framework for unbalanced distribution systems is proposed, which can strike a balance between recovery duration and load shedding. In the first stage, the repair crew model considering minimization of repair time is developed to evaluate the recovery duration. Within the duration, an optimal recovery model is then proposed in the second stage to minimize load shedding. Specifically, both static and mobile resources are fully coordinated in the recovery model. In addition, a novel model for intelligent zoning and merging of microgrids (IZMM) is proposed to strategically zone individual islanded microgrids and selectively merge multiple islanded microgrids through network reconfiguration, which can greatly enhance the distribution system resilience. The nonlinear optimization models are converted to mixed integer linear programming (MILP) problems through linearization techniques and solved by commercial solvers. The effectiveness of the proposed methodology is validated on the modified IEEE 33-node and IEEE 123-node test systems.