基于目标级联法的多主体主动配电网自治协同优化

Analytical Target Cascading Based Active Distribution Network Level Multiagent Autonomous Collaborative Optimization

随着“双碳”目标的战略推进,可再生能源在主动配电网(active distribution network,ADN)的大规模消纳提上日程,但受限于调度控制方式和数据交互模式,现有的集中式控制方法无法有效满足分布式能源消纳需求和配电网运行经济性目标。为此,提出了一种基于目标级联法(analytical target cascading,ATC)的主动配电网区域多主体自治协同优化方法,将柔性负荷、分布式电源和储能视为受控单元主体,根据配电网整体的经济性优化目标和微电网区域的局部自治优化需求,设计“ADN主体-节点主体-受控单元主体”的调度框架;并通过ATC处理主体间的共享交互信息,将不同层级的系统解耦为主系统和子系统,达到兼顾整体和局部目标协同优化的效果。最后,通过搭建D9M2和IEEE 33节点配电系统,验证了该方法的有效性。

As part of the strategic push toward achieving carbon neutrality,the imperative to integrate renewable energy into active distribution networks(ADNs)on a large scale has become a priority.However,the traditional centralized control methods are hamstrung by dispatch control strategies and data interchange modes,falling short in accommodating the needs for distributed energy assimilation and meeting the economic operation goals of distribution networks.In response,this work introduces an innovative regional multi-agent autonomous collaborative optimization approach for ADNs,grounded in Analytical Target Cascading(ATC).This approach treats flexible loads,distributed energy resources,and storage systems as controllable unit agents.It aligns with the overall economic optimization objectives of the distribution network and the localized autonomous optimization requirements of microgrid domains,framing a dispatch architecture structured around"ADN entity-node entity-controlled unit entity."Leveraging ATC to handle the inter-agent shared interactive information,the approach effectively separates complex system hierarchies into primary systems and subsystems.This separation facilitates a synergistic optimization that respects both the comprehensive and specific regional goals.The method's robustness and efficiency are substantiated through the development and testing within D9M2 and IEEE 33 node distribution systems,demonstrating its validity in practical scenarios.