Online Droop Tuning of a Multi-DG Microgrid Using Cuckoo Search Algorithm

Abstract This article presents an intelligent strategy to achieve appropriate real power sharing among distributed generators in a microgrid. The presented strategy employs two droop-based control methods and automatically adjusts their parameters. The first method is unit power control, which has specifications similar to the conventional droop method, and the second is feeder flow control, showing significant characteristics in both grid-connected and islanded modes operation of a microgrid. A combination of unit power control and feeder flow control methods is used for a multi-distributed generator microgrid. The microgrid operation mode passes from the grid-connected to the islanded through a transition. A new evolutionary algorithm called cuckoo search is employed to coordinate the power management of distributed generators within an on-line droop tuning. In comparison to the predecessor evolutionary algorithms, the cuckoo search algorithm represents more effective random processes with fewer parameters. Using the proposed control strategy, while the distributed generators contribute to load demand provision based on their rated powers, their powers are optimized in terms of overshoot and settling time. Digital time-domain simulation studies are carried out in the MATLAB/SIMULINK (The MathWorks, Natick, Massachusetts, USA) environment to verify the performance of the proposed control system.