Energy management strategy using model predictive control for power-to-gas (PtG) system integrated with microgrid

Abstract

Abstract The present study proposes a model predictive control (MPC)-based energy management strategy (EMS) for a hybrid storage-based microgrid (µG) integrated with a power-to-gas system. EMS has several challenges such as maximum utilization of renewable power, proper control of the operating limits of the state of charge of storage, and balance in demand and supply. Sudden transient power variation in FC and EL can lead to the degradation of these components. The proposed EMS effectively controls the above-mentioned issues in µG operation. Special attention is given to power-sharing between the different FC generators based on the stored hydrogen in the hydrogen storage tanks. Therefore, the amount of stored hydrogen in different storage tanks can be balanced. The EMS is developed and verified in the simulation domain using MATLAB Simulink. Results show that the rate of balancing the stored hydrogen can be adjusted by tuning the weight factors in MPC. Results show that ≈120 min. is taken to balance the amount of stored hydrogen in MH tanks (5000 nominal liters each) for 700 W power-sharing between the two FC units (1 kW each). Graphical abstract Highlights 1. Energy management system (EMS) for hybrid energy storage. 2. Model predictive control-based EMS. 3. The smooth operation of Electrolyzer and Fuel cell in a microgrid. Discussion Output characteristics of fuel cell and electrolyzer and their limitations on the rate of output change are challenges in designing effective EMS. To handle multiple constraints and control objectives, the present study focuses on a control strategy using MPC. The performance of the controller with different weight factors on the control objectives and outputs has been studied in detail.