Abstract
A novel method of frequency of control of isolated microgrid by optimization of model predictive controller (MPC) is proposed in this study. The suggested controller is made for a microgrid that employs renewable energy sources as well as storage systems. The proposed control scheme makes use of MPC to continuously optimize and modify the controller coefficients. The MPC parameters specifically the input control rate weight parameter, prediction horizon, and control horizon are optimized using genetic algorithm. The frequency perturbations that occur after the power fluctuations in the microgrid due to the power imbalance are minimized by the proposed controller by sending a control signal to the sources. This power imbalance is caused by the sporadic nature of power generation by renewable energy resources like wind and solar units and load disruption in an isolated microgrid. The suggested control method efficacy is assessed through simulation work on the islanded microgrid in MATLAB environment wherein the proposed controller performs better than conventional MPC, fuzzy-based MPC, and particle swarm optimization-based MPC. In comparison with other approaches, the suggested control method performs better when parameters are changed and has been able to successfully reduce the number of oscillations and amplitude of frequency fluctuations. It is also more resilient to the indeterminacy of microgrid specifications when compared to other approaches.
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Tudu, A.K., Naguru, N., Dey, S.H.N. et al. Load frequency control of an isolated microgrid using optimized model predictive control by GA. Electr Eng (2024). https://doi.org/10.1007/s00202-023-02206-6
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DOI: https://doi.org/10.1007/s00202-023-02206-6