Suppression of low-frequency oscillations in hybrid/multi microgrid systems with an improved model predictive controller

Grid-forming inverters are used for voltage regulation and frequency control in autonomous hybrid microgrids and multi-microgrid systems by imitating synchronous generators. However, in microgrids with weak grids including low inertia levels and small X/R ratios, these inverters interact with each other, and as a result low-frequency oscillations (LFO) arise. LFO impacts the frequency stability of multi-microgrid systems. Nevertheless, LFO can be mitigated by the load-frequency control system, which serves as a secondary control mechanism. However, the presence of wind turbines and photovoltaic systems in hybrid microgrids adds complexity to the operation of the load-frequency control due to the uncertainty associated with these renewable energy resources, and various controllers have been employed. This paper proposes a novel approach to enhance the performance of the load-frequency control system and suppress LFO. The presented technique reduces the complexity of the hybrid microgrid structure by reducing the number of controllers. The model predictive control (MPC) technique is utilized for load-frequency control and the weight parameters of the MPC are determined using the rain optimization algorithm. The proposed method demonstrates improved dynamic response, reduced overshoot and undershoot responses, decreased controller complexity, and effective LFO suppression. The simulation results verify the effectiveness of the method. (1) Load frequency control (LFC) in hybrid microgrid based on model predictive control (MPC). (2) Reduction of controllers used for energy storage systems such as batteries, flywheels, and super magnetic energy storage (less complexity). (3) Improving the performance and adjusting the weight parameters of the MPC against disturbances and uncertainty related to the hybrid microgrid parameters using the rain optimization algorithm (ROA). (4) Testing the performance of the proposed algorithm compared to GA and PSO algorithms in optimizing the weight parameters of the MPC considering the ITAE objective function. (5) Performance testing of the proposed controller (MPC-ROA) to improve the performance of LFC against disturbances and uncertainty of the parameters related to the hybrid microgrid. image