Distributed adaptive droop control for optimal power dispatch in DC microgrid
In this paper, a coordinated adaptive droop control is addressed for DC microgrid to optimize
its power distribution. The optimal solution for economical dispatch problem (EDP) of the
microgrid is found through a fully distributed hierarchical control. The consensus-based
economical regulator calculating the optimal solution for the generator is fully distributed.
Thus, it eliminates the requirement of centralized coordinator. The droop controller receives
the reference from the economical regulator and ensures the output power converging to the …
its power distribution. The optimal solution for economical dispatch problem (EDP) of the
microgrid is found through a fully distributed hierarchical control. The consensus-based
economical regulator calculating the optimal solution for the generator is fully distributed.
Thus, it eliminates the requirement of centralized coordinator. The droop controller receives
the reference from the economical regulator and ensures the output power converging to the …
In this paper, a coordinated adaptive droop control is addressed for DC microgrid to optimize its power distribution. The optimal solution for economical dispatch problem (EDP) of the microgrid is found through a fully distributed hierarchical control. The consensus-based economical regulator calculating the optimal solution for the generator is fully distributed. Thus, it eliminates the requirement of centralized coordinator. The droop controller receives the reference from the economical regulator and ensures the output power converging to the reference while maintaining the power balance of the system. Moreover, the economical regulator can estimate the load information of the system based on the characteristics of droop control. Thus, the information from load or renewable energy source is no longer required to solve the EDP that consequently decreases the number of communication nodes. This will reduce infrastructure cost, enhance the reliability, and fasten the converging speed of algorithm. The dynamic model is established and parameter selection guideline are given in this paper. A low-voltage dc-microgrid prototype platform is utilized to validate the effectiveness of the proposed control.
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