Congestion Management Strategy for Distribution Networks Considering Flexible Loads and Advanced Energy Storage under Renewable Energy Integration

Abstract

: Large-scale integration of customer-side flexible resources and distributed resources can aggravate line congestion and voltage violations in active distribution networks, particularly under power supply guarantee scenarios. This paper develops a bi-level congestion management method that coordinates heterogeneous flexible resources through a Stackelberg game framework. Distributed energy storage, electric vehicles, interruptible loads, and time-shiftable loads are scheduled, and vehicle-to-grid capability is explicitly incorporated to enhance operational flexibility during critical supply periods. The model captures the interaction between the load aggregator (LA) and the distribution system operator (DSO): the LA optimizes the dispatch of aggregated flexible resources in response to price signals, while the DSO seeks to maximize social welfare subject to network security constraints. To solve the nested bi-level problem, an improved grey wolf optimizer (IGWO) with Tent chaotic initialization and nonlinear convergence control is employed. Simulations on a modified IEEE 33-bus system show that the proposed method can relieve line overloading, keep nodal voltages within allowable limits, smooth net-load fluctuations, and improve peak-shaving and valley-filling performance, thereby reducing social welfare losses. The results indicate that the method provides practical support for the secure and economic operation of active distribution networks and facilitates the effective integration of renewable generation and distributed storage.