Secondary Control of Islanded Microgrids Using PI-Evolutionary Algorithms Under Uncertainties

Reda Rabeh, Mohammed Ferfra, Ahmed Ezbakhe

Abstract


Electrical grids converge now to a novel concept which named Microgrids (MG). it consists on producing energy with isolated connected to grid to reduce dependency on fuel and main grids due to its fluctuant cost and to decrease harmful emission in the atmosphere. Constituted by renewable sources, energy storage system and controllable sources, a hybrid combination of these DERs is adopted to maintain MG reliability, transparency and efficiency with the deregulate power production according to weather conditions; ( e.g. temperature, solar radiation, wind speed. . . ) of the non-controllable sources and load fluctuation. These perturbations affect frequency as one parameter of quality of energy sensitive to active power balance. That’s why a smart management of controllable sources is highly recommended to minimize this frequency deviation. In this paper, a dynamic model is adopted with PI controller in controllable sources and storage system and presents a novel approach to design PI controller parameters by hybrid Evolutionary Algorithm (EA) GA-TLBO for a robust control of frequency regulation under uncertainty. A simulated isolated MG is tested on scenarios to validate the approach adopted in conceiving the PI parameters to avoid the frequency fluctuation in the different cases of study.


Keywords


Isolated MG; controlled sources; noncontrolled sources; frequency control; PI controller; evolutionary algorithm; genetic algorithm; teaching-learning based optimization.

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DOI (PDF): https://doi.org/10.20508/ijrer.v9i4.9977.g7787

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