A robust firefly-swarm hybrid optimization for frequency control in wind/PV/FC based microgrid

Abstract This paper presents frequency regulation in a microgrid consisting of wind, photovoltaic (PV), fuel cell (FC) and diesel engine generator (DEG) along with the energy storage system such as flywheel energy storage (FES) and battery energy storage (BES). In this study, firefly and particle swarm (FF–PSO) based hybrid optimization technique is proposed to tune parameters the proportional–integral–derivative (PID) controller to minimize the frequency deviation in microgrid system under different operating conditions such as variation in wind speed, and load demand. Further, a comparative analysis for tuning of the PID controller is performed using particle swarm optimization (PSO), and firefly algorithms (FFA) to minimize the deviation in frequency. The power management as well as frequency control in microgrid is studied with the help of the performance indices; integral absolute errors (IAE), peak overshoots, settling times and standard deviation (SD). In addition, the effect of communication delay with higher non-linearity is tested to assess the performance of the controllers. Further, the frequency control is validated in real-time digital simulation environment using OPAL-RT. The qualitative, quantitative and real-time analysis reflects the improvements in frequency deviation in microgrid using the proposed hybrid FF–PSO optimized PID as comparison to the PSO/FF optimized PID controllers.

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