Crow Search Algorithm For Improving The Performance Of An Inverter-Based Distributed Generation System

Distributed generation (DG) systems achieve an important role in electrical power networks due to their technical and economic benefits. This paper presents a novel application of the Crow Search Algorithm (CSA) with purpose of enhancing the performance of an inverter-based DG system. The control strategy of the inverter is based on a vector cascaded control scheme, which relies on the Proportional plus Integral (PI) controller. The proposed CSA is utilized to fine tune the PI controller parameters. The response surface methodology (RSM) is used to create the objective and constraint function of the optimization problem. The validity of the proposed control strategy is extensively verified using the simulation results, which are performed using PSCAD/EMTDC environment. These simulation results are investigated under different operating conditions such as 1) transition of the system from grid connected to islanded mode of operation, and 2) subject the system to a single line to ground fault in the autonomous mode. The effectiveness of the proposed controller is verified by comparing its results with that obtained using the genetic algorithm-based PI controller.