Research on Optimization and Scheduling Control Strategy of Renewable Energy Grid-Connection Based on Intelligent Control - Li, Guo; Ji, Shaowei; Wang, MingHua; Guo, Chenyuan (Distributed Generation & Alternative Energy Journal, 2026)
With the rapid development of renewable energy, the fluctuation of its output poses huge challenges to the stability and reliability of power systems. To improve the efficiency of renewable energy grid-connection, this paper studies an optimization and scheduling control strategy for renewable energy grid-connection based on intelligent control. First, the limitations of traditional scheduling strategies in the face of large-scale renewable energy integration are analyzed, and an optimized scheduling model combining intelligent control algorithms is proposed. This model responds in real time to the dynamic changes of the power system, optimizes the consumption of renewable energy generation, and effectively reduces the volatility in system scheduling. On this basis, an intelligent optimization control framework is proposed. By intelligently adjusting the scheduling strategies of power generation units, it ensures system load balance while maximizing the proportion of green energy use. Real-time load forecasting and power generation forecasting information are used to optimize scheduling decisions, thereby enhancing the economy, flexibility, and reliability of the system. Experimental results show that the proposed strategy has significant advantages over traditional scheduling methods in terms of system operation costs, energy consumption efficiency, and renewable energy utilization rate.