Özet:

A comprehensive and comparative review of control strategies for power-sharing operation in DC microgrids are presented in the paper. Since a microgrid consists of distributed generation sources and energy storage units, a control layer is required to manage the power-sharing operation between them. For this purpose, the control schemas used in DC microgrids are categorized as centralized, decentralized, distributed and hierarchical. Therefore, a review of these four control structures is presented in the paper firstly. Then, the hierarchical control method is handled in detail because it is widely preferred in DC microgrid control schemas. Among several methods and algorithms used in the hierarchical control layers, methods based on artificial intelligence and metaheuristic algorithms are being gained popularity in up-to-date studies. Hence, a methodological comparison of these methods is presented in order to put forward their advantages and disadvantages. In the last part of the paper, genetic algorithm, particle swarm optimization and the gray wolf algorithm which are the mostly used metaheuristic algorithms are comparatively tested for the optimization of a sample microgrid. Results show that the gray wolf algorithm offers the best performance in terms of the rising time, the overshoot percentage and the settling time.

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