This paper proposes an intuitionistic fuzzy Takagi–Sugeno (TS) approach for managing renewable energy flows in a direct current (DC) microgrid (MG) with composite photovoltaic (PV) and wind (WT) generators and energy storage systems. The system aims to maximize external energy and minimize consumption, ensuring stability and reliability. The fuzzy rule bank, initially built using expert knowledge, is optimized using a procedure that combines particle swarm optimization (PSO) for structuring the antecedents of the rules and batch least squares (BLS) for optimizing the output. The complete scheme is modeled using MatLab/Simulink, and the results show comparable performance to those obtained using a hybrid approach based on PSO and BLS. The main contributions include the optimization of the fuzzy rule bank, the use of intuitionistic fuzzy sets to handle uncertainties, and the improved efficiency of the system in maximizing power from renewable sources and reducing hydrogen consumption. The paper also discusses the physical-mathematical characteristics of the renewable sources, the modeling and control of the lead-acid battery and fuel cell, and the implementation and performance of the proposed EMS.This paper proposes an intuitionistic fuzzy Takagi–Sugeno (TS) approach for managing renewable energy flows in a direct current (DC) microgrid (MG) with composite photovoltaic (PV) and wind (WT) generators and energy storage systems. The system aims to maximize external energy and minimize consumption, ensuring stability and reliability. The fuzzy rule bank, initially built using expert knowledge, is optimized using a procedure that combines particle swarm optimization (PSO) for structuring the antecedents of the rules and batch least squares (BLS) for optimizing the output. The complete scheme is modeled using MatLab/Simulink, and the results show comparable performance to those obtained using a hybrid approach based on PSO and BLS. The main contributions include the optimization of the fuzzy rule bank, the use of intuitionistic fuzzy sets to handle uncertainties, and the improved efficiency of the system in maximizing power from renewable sources and reducing hydrogen consumption. The paper also discusses the physical-mathematical characteristics of the renewable sources, the modeling and control of the lead-acid battery and fuel cell, and the implementation and performance of the proposed EMS.