Resilience improvement of multi-microgrid distribution networks using distributed generation

Abstract Natural disasters such as earthquakes, hurricanes, and other extreme weather events along with human sabotage attacks pose serious risks to critical infrastructures especially electrical energy systems. Hardening and operational actions are the measures to improve the resiliency of the power systems against extreme events. The long-term hardening actions strive to organize the reinforcement of power system infrastructures which accomplished at the pre-events stage. Besides, the short-term operational measures such as network reconfiguration and generation scheduling are applied to form the multiple microgrids aimed at increasing the flexibility of the power system to cope with the severe events. These measures are taken during and after the occurrence of the disasters. In this paper, an integrated framework has been proposed to increase the resiliency of distribution system. In the proposed framework, there are two models so called defender–attacker–defender which are made to find the best possible solution in order to reduce the load-shedding of the system during extreme events. In the first model, the hardening measures are examined at the first level to increase the robustness of the system. The worst scenarios with the highest load-shedding are calculated in the second level and subsequently reconfiguration is performed in the third level to decrease the load-shedding. In the second model, the first and second levels specify the best reinforcement plan and the worst attack scenario respectively, and in the third level, optimal distributed generation placement is accomplished to supply the demand during islanding mode of microgrids. The proposed models are organized as tri-level mixed integer optimization problem and column constraint generation algorithm is utilized to make them computationally obedient. At the end, we have implemented the suggested models on the well-known IEEE 33-bus and 69-bus systems to prove their effectiveness and applicability at improving the resiliency of the distribution systems.