In this paper, a model predictive control (MPC) for the optimal power exchanges in a smart network of power microgrids (MGs) is presented. The main purpose is to present an innovative control strategy for a cluster of interconnected MGs to maximize the global benefits. A MPC-based algorithm is used to determine the scheduling of power exchanges among MGs, and the charge/discharge of each local storage system. The MPC algorithm requires information on power prices, power generation, and load forecasts. The MPC algorithm is tested through case studies with and without prediction errors on loads and renewable power production. The operation of single MGs is simulated to show the advantage of the proposed cooperative framework relative to the control of a single MG. The results demonstrate that the cooperation among MGs has significant advantages and benefits with respect to each single MG operation

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The optimal control of the power flows in a network\ud of microgrids (MGs) is presented. The problem is solved using\ud the mathematical formalization of the optimal control based on\ud the Pontryagin’s minimum principle (PMP). The objective is to\ud deliver an optimal control strategy for the minimization of the\ud power flows among MGs, and to maintain the storage system\ud operating around a given reference value. This study proposes\ud an original formulation based on the PMP that may be viewed as\ud a preliminary continuous time attempt to model and control the\ud exchange of power in a network of MGs. Its main originality\ud is the use and the exchange of information and forecast of\ud energy production and consumption on the whole set of MGs, to\ud improve the overall quality of the power management, and energy\ud storage. A method based on the PMP is developed to solve the\ud corresponding constrained optimal control problem in an almost\ud exclusively analytical way and thus, to calculate the optimal\ud control. To prove the viability of the proposed approach, an\ud example has been solved for the case of four MGs collaborating\ud in a network

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