Research on Voltage Autonomy and Cooperative Active Support Operation Optimization Strategy for Distribution Network Considering Grid-Connected Distributed Generation

Abstract

: The increasing penetration of distributed generation (DG) in distribution networks poses significant challenges to power quality due to the inherent variability and uncertainty of DG output. Traditional voltage control methods based on static stability constraints and reactive power compensation devices struggle to achieve fine-grained regulation across multiple nodes and time scales. This paper proposes a hierarchical operational optimization strategy for voltage control in distribution networks with grid-connected DG. First, a steady-state analysis model is established to quantitatively characterize the impact of renewable energy sources on system voltage distribution. Based on this foundation, a three-layer voltage coordination control architecture is constructed, comprising: (i) a local autonomous layer for millisecond-level fast response using DG inverter reactive power; (ii) a regional coordination layer employing model predictive control (MPC) for minute-level coordination of multiple devices; and (iii) a global optimization layer utilizing deep reinforcement learning (DRL) combined with mixed-integer programming for hourly economic scheduling. This architecture achieves decoupled control in both temporal and spatial dimensions. Simulation verification on modified IEEE 33-bus and IEEE 123-bus systems demonstrates that the proposed strategy: reduces the risk of voltage violations by over 60% compared to conventional decentralized control; decreases daily network energy losses by approximately 15%; and reduces the operation counts of traditional mechanical devices (OLTCs and capacitor banks) by more than 60%, significantly extending equipment lifespan. The proposed method provides a feasible solution for safe and economic operation of distribution networks with high DG penetration.