Multi-microgrid power distribution systems are gaining attention in the smart grid era. Distributed energy resources, energy storage, as well as energy sharing and scheduling has a great potential to enhance multi-microgrid systems’ performance. This research develops an algorithm for optimal operation of various distributed energy resources in a flexible boundary multi-microgrid power distribution network, considering internet of things (IoT). The proposed algorithm used in this research can reduce power system operating costs, power, and energy losses and emissions, and ultimately increase the systems’ efficiency. A hybrid Particle Swarm Optimization-Tabu Search algorithm is developed for optimization purposes. This algorithm is then applied to the well-known Pacific Gas and Electric Company 69-bus power distribution network for simulations and case studies to show the impacts of various energy resources, the internet of things, and flexible boundary conditions of multi-microgrid on systems’ performance indices. The probabilistic uncertainty states of photovoltaics and wind turbines are considered to get more accurate results. The simulation results presented in the paper shows great benefits are achievable through operating the system as multi-microgrid and by energy sharing between microgrids, especially with consideration of the flexible boundary conditions and internet of things. The results obtained from the simulations confirm significant increase in the system efficiency and systems’ performance indices, including operational costs, power losses and environmental emissions.