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

Félix Dubuisson, Miloud Rezkallah, Hussein Ibrahim and Ambrish Chandra
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Félix Dubuisson: Department of Electrical Engineering, École de Technologie Supérieure, Montréal, QC H3C 1K3, Canada
Miloud Rezkallah: Department of Electrical Engineering, École de Technologie Supérieure, Montréal, QC H3C 1K3, Canada
Hussein Ibrahim: CR2Ie, Sept-Îles, QC G4R 5B7, Canada
Ambrish Chandra: Department of Electrical Engineering, École de Technologie Supérieure, Montréal, QC H3C 1K3, Canada

Energies, 2021, vol. 14, issue 6, 1-15

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

Keywords: bacterial foraging optimization (BFO); battery energy storage; diesel generator; power management; power quality; predictive control; renewable energy sources; standalone microgrid (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2021
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