Microgrid on the ship: load Frequency- control of the microgrid, taking into account the Sea Wave energy by the optimized model predictive controller

Load-frequency control is among the important concerns in controlling microgrids, which are operated independently of the main grid. In this paper, load-frequency control in microgrids on ships is studied. Resources such as batteries and flywheels are considered controllable resources in load-frequency control. Besides, the model predictive control is used as the controller to design a load-frequency control system. The model predictive control weight parameters, which play a substantial role in determining the performance of this controller, are optimized using the craziness-based particle swarm optimization algorithm. The proposed algorithm accelerates convergence. The results of the proposed controller are compared under several different scenarios considering the uncertainty of parameters using Multi-Objective Fuzzy Type 1 PI and Multi-Objective interval Fuzzy Type 2 PI controllers, which are optimized by the black hole algorithm, the fuzzy proportional integral controllers, and Ziegler–Nichols proportional integral controllers. The effectiveness of the proposed method with regard to the response speed, the decrease in overshoot and undershoot, and robustness against the parameter uncertainties is indicated. The proposed controller responds faster than the other conventional control methods and accelerates the process of responding to oscillations by 7%. In addition, the proposed controller performs better in reducing overshoot and reducing undershoot and it shows a 5% improvement with regard to the decrease in overshoot and undershoot in the oscillations. Simulations are also carried out in MATLAB (Simulink).