Security and Economic Dispatch of Active Distribution Network and Virtual Power Plant Based on Stackelberg Game

With the increasing penetration of virtual power plants (VPPs) in distribution networks, the bidirectional power flow between active distribution networks (ADNs) and VPPs presents significant challenges for coordinated scheduling and control. To address this issue, this paper proposes a securityconstrained economic scheduling method based on a Stackelberg game framework to enable effective ADN-VPP coordination. The proposed approach incorporates various distributed energy resources (DERs) from both ADNs and VPPs into a game-theoretic structure, formulating a bi-level optimization model in which the distribution network operator (DNO) acts as the leader and the VPPs serve as followers. In this framework, the DNO generates electricity price signals using a linearized power flow model with embedded voltage security constraints, thereby guiding VPPs to optimize their internal dispatch strategies while ensuring both operational security and economic efficiency of the distribution network. Under the DNO’s pricing signals, VPPs coordinate their internal DERs and energy storage systems (ESS) to maximize operational profits. To validate the effectiveness of the proposed methodology, case studies are conducted on the IEEE 33 distribution network. The results demonstrate that the proposed approach effectively alleviates node voltage violations and improves both the economic performance and operational stability of the power grid.