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Lanqing Shan

Publications and source records attributed to Lanqing Shan.

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Voltage Stability Assessment with Path-Coupled Load Growth and Corrective Generator Response

Voltage stability margin assessment is essential for the secure operation of renewable-dominated power systems. Conventional continuation-based methods evaluate the margin along predefined load-growth paths with fixed generator partic- ipation, while practical operation allows generators to be redis- patched to alleviate voltage stress and reshape the power-flow trajectory as the system approaches voltage collapse. This paper proposes a path-coupled margin assessment approach that incor- porates corrective generator response into static voltage stability margin assessment. In the proposed approach, the load-growth direction and generator response direction are simultaneously determined at each continuation step, enabling the assessment trajectory to account for generator response while tracing the system toward voltage collapse. The voltage stability margin is then evaluated by the cumulative active load increase along this coupled trajectory. Based on the obtained trajectory and collapse point, a feasible redispatch direction is further derived to improve the margin of the current operating state. The economic cost of voltage stability enhancement is quantified through a marginal stability cost, providing an economic indicator for additional sta- bility support. Case studies on various test systems demonstrate that the proposed framework can effectively capture the impact of corrective generator redispatch on voltage stability assessment, provide effective guidance for margin enhancement, and quantify the cost associated with voltage stability improvement.

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Connection-Aware P2P Trading: Simultaneous Trading and Peer Selection

Peer-to-peer (P2P) trading is seen as a viable solution to handle the growing number of distributed energy resources in distribution networks. However, when dealing with large-scale consumers, there are several challenges that must be addressed. One of these challenges is limited communication capabilities. Additionally, prosumers may have specific preferences when it comes to trading. Both can result in serious asynchrony in peer-to-peer trading, potentially impacting the effectiveness of negotiations and hindering convergence before the market closes. This paper introduces a connection-aware P2P trading algorithm designed for extensive prosumer trading. The algorithm facilitates asynchronous trading while respecting prosumer's autonomy in trading peer selection, an often overlooked aspect in traditional models. In addition, to optimize the use of limited connection opportunities, a smart trading peer connection selection strategy is developed to guide consumers to communicate strategically to accelerate convergence. A theoretical convergence guarantee is provided for the connection-aware P2P trading algorithm, which further details how smart selection strategies enhance convergence efficiency. Numerical studies are carried out to validate the effectiveness of the connection-aware algorithm and the performance of smart selection strategies in reducing the overall convergence time.

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