Research on Intelligent Load Optimization Technology for Distribution Networks Based on Distributed Collaborative Control

To address voltage over-limit and transformer overload issues in distribution grids caused by large-scale distributed PV integration, this paper proposes a distributed cooperative-based intelligent load optimization technique for distribution grids. First, by analyzing the limitations of traditional centralized control in communication burden, response speed, and fault tolerance, the necessity of distributed cooperative control is demonstrated. Subsequently, leveraging the bidirectional power regulation capability of energy storage systems, a distributed PV-storage system cooperative control model based on a consensus algorithm is constructed. This model comprehensively considers PV output fluctuations, energy storage state of charge, and grid regulation demands. Through multi-node information exchange and iterative updates of consensus variables, the model achieves coordinated power allocation among systems and voltage overlimit mitigation. Simulation results demonstrate that the proposed method effectively smooths PV fluctuations and alleviates local overloads in distribution grids. It simultaneously accommodates capacity differences and operational constraints across energy storage systems, enhancing system response speed and robustness. This provides effective technical support for the safe operation of distribution grids under high penetration of distributed renewable energy.