An Intelligent Control Strategy for Microgrid Energy Storage Systems Using Distributed Collaborative Approach

In the islanded DC Microgrid (MG) with the significant presence of renewable energy sources (RES), the integration of energy storage units (ESU) becomes crucial in mitigating the stochastic and intermittent nature of these RES. This research article introduces an intelligent distributed collaborative control scheme for managing multiple hybrid energy storage systems (HESS) within the islanded DC MG. The hierarchical control assembly is built to ensure coordinated and secure operation among the HESS units, and accurate power sharing and voltage regulation. The primary control layer utilizes a virtual-resistance droop control approach, employing a low-pass filter (LPF) to distribute the power between a battery and a supercapacitor. The state of charge (SoC) based Control schemes are presented to achieve safe and coordinated operation among the HESSs. Operating on a sparse communication network, the secondary control layer focuses on regulating the average voltage and proportional current of each hybrid energy storage system. This approach addresses issues arising from significant bus voltage deviations and inaccurate power-sharing due to virtual and line resistances. To enhance the performance of the islanded DC microgrid, an intelligent control scheme is implemented, utilizing the attributes of an Artificial Neural Network (ANN) controller alongside a traditional PI controller. To validate the proposed control method’s effectiveness and robustness in an islanded DC microgrid, extensive simulations and analyses are conducted using MATLAB/Simulink software. The results are compared with those obtained using a PI-based distributed collaborative control strategy. The Performance of ANN demonstrates that the presented controller has the capability to maintain the voltage stability of the islanded DC MG and achieve accurate power-sharing.