Real-Time Implementation of the Predictive-Based Control with Bacterial Foraging Optimization Technique for Power Management in Standalone Microgrid Application

In this paper, the predictive-based control with bacterial foraging optimization technique for power management in a standalone microgrid is studied and implemented. The heuristic method based on social behavior of Escherichia coli bacteria employed to determine references from non-renewable energy sources loads proposed configuration, which consists fixed speed diesel generator battery storage system (BES). two-stage configuration controlled maintain DC-link voltage constant, regulate AC frequency, improve quality, simultaneously. For these tasks, side, obtained are used as input signals control. With help parameters, computes all possible states next sampling time compares them estimated using (BFO) get inverter current reference. DC same concept predictive approach DC-DC buck-boost converter by regulating forward Euler generate discrete-time model predict real-time BES current. strategies evaluated simulation results Matlab/Simulink presence different types loads, well experimental small-scale microgrid.