Distributed converter current command collaborative optimization method and system

CN122315740APending Publication Date: 2026-06-30SHANGHAI JIAOTONG UNIV +1
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Patent Information

Application Number
CN202610325845.0
Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
Filing Date
2026-03-17
Publication Date
2026-06-30

AI Technical Summary

Technical Problem

Existing technologies struggle to effectively coordinate and control multiple distributed converters in a wide-area power grid, leading to voltage performance degradation. This is especially true in weak areas of the grid or under asymmetrical faults, where the system voltage imbalance increases significantly, affecting power quality and equipment safety. Furthermore, traditional control methods suffer from slow response speeds and insufficient flexibility, making them unable to adapt to the rapid spatiotemporal changes in scenarios with high penetration of new energy sources.

Method used

By establishing a wide-area power grid system model containing multiple distributed converters, introducing auxiliary variables and convex relaxation methods, the current command collaborative optimization problem is transformed into a convex optimization problem. By integrating phase current amplitude, active power output and synchronization stability constraints, the optimal current command is generated and converted to the local coordinate system for execution.

Benefits of technology

It achieves efficient and proactive management of system voltage performance, significantly improves grid voltage quality, avoids equipment overload and system instability risks, is suitable for mild or moderate to severe grid voltage imbalance scenarios, and provides a reliable solution for extreme operating conditions.

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Abstract

This invention provides a method and system for collaborative optimization of current commands for distributed converters. Through system modeling and collaborative optimization, it achieves optimal coordinated control of multiple distributed converters in a wide-area power grid. With minimizing the global voltage imbalance as the optimization objective, it integrates physical constraints such as phase current amplitude, active power output, and synchronization stability of each distributed converter. Based on positive and negative sequence power flow equations, it establishes the voltage and current coupling relationship of the system, constructing a collaborative optimization model with rigorous physical feasibility. Furthermore, by introducing mathematical methods such as auxiliary variable substitution and convex relaxation, the original non-convex optimization problem is transformed into a convex optimization form that can be solved efficiently. Thus, while ensuring stable system operation, it solves for the optimal current commands of each converter, fully leveraging the cluster control potential of distributed converters, and providing an economical, reliable, and scalable solution for improving the voltage performance of wide-area power grids.
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Citation Information

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