Hierarchical autonomous collaboration strategy to support multiple types of resource access to distribution network
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摘要:
分布式资源大规模并网要求配电网的灵活调控能力不断增强,如何充分利用多层级灵活性资源协助系统运行成为目前亟待解决的问题。为此,文中提供一种支撑多种资源接入配电网的分级自治协同策略。首先,分析多层级下灵活性资源特性,对分布式资源出力采用概率模型以减少其不确定性因素影响。其次,构建主变-馈线-台区分层分区优化调度模型,台区层进行内部自治并将等值结果传递给馈线层,馈线层基于网络架构和资源运行特性进行区域划分,实现兼顾系统安全性和经济性的主配协同优化,并采用基于谱惩罚参数的自适应交替方向乘子法(spectral penalty parameter based adaptive alternating direction method of multipliers, SPPA-ADMM)进行求解。最后,选用改进的IEEE 33节点算例进行仿真,仿真结果表明文中所采用的并行控制方式能有效提高优化求解的效率,验证了所提策略对多种分布式资源分级接入配电网运行调控具有指导意义。
Abstract:
The large-scale connection of distributed resources requires the flexible control ability of distribution network to be enhanced continuously. How to make full use of multi-level flexible resources to assist system operation has become an urgent problem. Therefore,a hierarchical autonomous collaboration strategy to support multiple types of resource access to distribution network is provided in this paper. Firstly,the characteristics of flexibility resources under multi-level are analyzed,and a probabilistic model for distributed resource output to reduce the influence of its uncertainty factors is adopted. Secondly,a hierarchical zonal optimization and dispatch model is constructed for the main substation-feeder-station area. The station area layer carries out internal autonomy and passes the equivalent results to the feeder layer. The feeder layer divides the area based on the network architecture and the operating characteristics of the resources,so as to realize the main-distribution cooperative optimization taking into account the security and economy of the system,and the spectral penalty parameter based adaptive alternating direction method of multipliers (SPPA-ADMM) is used for the solving. Finally,the improved IEEE 33-node example is selected for simulation. The simulation results show that the parallel control method adopted in this paper can effectively improve the efficiency of optimization solution,which verifies that the proposed strategy has guiding significance for the operation regulation of multiple distributed resources.