A Bacterial Foraging Optimization Technique and Predictive Control Approach for Power Management in a Standalone Microgrid

In this paper, the Bacterial Foraging Optimization (BFO) algorithm is proposed for real-time calculation of active and reactive power references estimation. This method emulates the behavior of E.coli bacteria to find the global minimum of a cost function. Using this technique, one estimates the power references of the system to use as input parameters for the developed predictive control strategy for the three-phase inverter. The comportment of the BFO and the predictive control, are tested using Matlab/Simulink under load variation. In addition, a detailed comparison between the BFO method and Particle Swarm Optimization (PSO) is provided.