Abstract:

This paper proposes a distributed coordinated optimization method for multi?microgrid systems based on the Alternating Direction Method of Multipliers (ADMM). The proposed model comprehensively accounts for generation costs, energy storage operation, and inter?microgrid interactions, while employing second?order cone relaxation techniques to address nonlinear power flow constraints. By optimizing the ADMM iteration process and parameter selection, the method significantly improves computational efficiency while protecting data privacy through its distributed architecture. Case studies demonstrate that the method converges within only five iterations, achieves a 76.7% improvement in computational efficiency compared with centralized optimization, and maintains a solution accuracy within a 0.34% deviation from the global optimum. Compared to linear programming methods, the ADMM enhances voltage regulation performance by 40.0% and reduces line losses by 15.5%. The method exhibits excellent scalability with computational complexity increasing linearly with the number of microgrids, is applicable to various network topologies, and requires sharing only boundary interaction information, thus providing effective technical support for multi?microgrid coordination optimization.

Key words: Multi?microgrid system, ADMM, Distributed optimization, Coordinated dispatch

摘要：

提出一种基于ADMM的多微网系统分布式协调优化方法，构建了综合考虑发电成本、储能运行及微网间交互的优化模型，并采用二阶锥松弛技术处理了潮流非线性约束。通过优化ADMM迭代流程和参数选择，该方法显著提高了计算效率，同时通过分布式架构保护了数据隐私。算例分析结果表明，该方法仅需5次迭代即可收敛，计算效率比集中式优化提高了76.7%，优化结果相差仅0.34%；与线性规划方法相比，ADMM提升了40.0%的电压控制效果，减少了15.5%的线路损耗。该方法具有良好的可扩展性，计算复杂度随微网数量呈线性增长，适用于多种网络拓扑结构，仅需共享边界交互信息，为多微网协调优化提供了有效的技术支撑。

关键词: 多微网系统, ADMM, 分布式优化, 协调调度