Power allocation scheme for grid interactive microgrid with hybrid energy storage system using model predictive control

Grid-interactive microgrids have become a promising alternative to traditional centralized power systems as a result of the rising demand for reliable and sustainable energy solutions. DC microgrids (MG) based upon renewable energy sources (RES) are on the rise due to high energy efficiency and compact size than the AC microgrids. Microgrid equipped with hybrid energy storage system is sensible for a reliable and stable power supply to the system. Implementation of a potent control system makes sure of the system stability. A model predictive control (MPC) based control strategy is proposed due to its easy implementation approach and inclusion nonlinear dynamics & constraints of the controlled system. An efficient power allocation scheme is developed in this paper for a grid-interactive photovoltaic microgrid featuring a hybrid energy storage system (HESS). The system-level power allocation scheme (PAS) considers the real-time data of load demands, generation, market energy cost, and energy storage state-of-charge to actively manage the power flow within the microgrid and also with the utility grid. The proposed control scheme uses a sophisticated model predictive current control for the DC/DC bi-directional converters control and model predictive combined power and voltage control is used for bidirectional interlink converter. The proposed control approach provides faster DC bus voltage recovery. The HESS consisting of battery and supercapacitor is used as energy buffers for responding to the fluctuation of power generation and demand for smoothing the PV power. The potency of the proposed controller is verified using MATLAB/Simulink (2021b) environment. Also, the real-time implementation of the proposed approach is carried out using the OPAL-RT OP4510 simulator.