Optimal Control Architecture of Smart Energy Interconnected System with Multi-Factor Integration in New Power System

This study advocates an optimization control framework for an intelligent energy interaction system based on fuzzy logic control, with the aim of enhancing the collaborative efficiency of multiple energy components. This system integrates multiple energy elements such as power grids, renewable energy, and energy storage facilities, and achieves efficient collaborative management of various subsystems in complex energy networks with the help of fuzzy logic control. This paper deeply explores the conception of the optimization control algorithm, covering the construction of fuzzy logic inference criteria and the implementation of multi-objective optimization strategies. In addition, by building a corresponding simulation model, the dynamic response characteristics of the system under variable load scenarios are reproduced. Simulation data reveal that this control framework can significantly enhance the overall stability and energy utilization efficiency of the system, and effectively alleviate peak load pressure. Accurate data analysis results confirm the superiority of the framework under variable working conditions, especially in the scenario of renewable energy access with significant volatility, showing strong adaptability and flexibility. This study has laid an important theoretical foundation and technical pillar for the in-depth development of the future intelligent energy interaction system.