This paper proposes the design of an optimal power management and dispatch strategy among networked microgrids to enhance electrical grid resilience after disconnection. The main contribution of this paper is the design of an optimal strategy to ensure power system stability in the event of generator disconnection. This is achieved through optimal power sharing among multiple microgrids connected at the load bus, combined with smart power dispatch of renewable energy sources. The proposed strategy includes three coordinated stages involving optimal power management of renewable sources in each connected microgrid, optimal sharing of interconnected microgrids, and intelligent load shedding. Each microgrid includes a solar PV generator, concentrating solar power (CSP), and a wind farm. In addition, a multi-energy storage system was installed in each microgrid, comprising Redox Flow Batteries (RFBs), Superconducting Magnetic Energy Storage (SMES) and Fuel Cells (FCs). Moreover, an optimal Load Frequency Control (LFC) loop was applied to cope with system load disturbances or climatic changes. The main objective was to design a decentralized controller using nature-inspired optimization algorithms. For this aim, an optimal Fuzzy-PIDN controller was designed using a recently optimized algorithm called the Crayfish Optimization Algorithm (COA) , which was used to find the best controller parameters to enhance the power management of each green source, the frequency control using multiple storage units, and optimal microgrid power sharing to support the main grid frequency stability and control in case of load disturbances. Several case studies have been conducted to prove the validity of the proposed strategy. It can be concluded from the obtained results that multi-stage optimal power management and control ensure optimal sharing between interconnected multi-microgrids to increase resilience and energy autonomy after grid disconnection, and can also improve dynamic power system stability.