面向新能源并网的低压用户链路识别算法

Link Identification Method of Low-voltage User for Renewable Energy Integration

针对新能源并网带来的电压特性变化和低压拓扑关系辨识颗粒度细化需求,提出了基于图信号处理的用户链路识别模型。该识别模型利用相邻节点间的电压相似性表征图信号的平滑性,结合节点电流定律对网络结构的约束,克服新能源并网带来的同相用户电压相似性变差的影响;利用图结构固有的链路属性,实现低压拓扑识别下沉至用户之间的上下游连接关系识别。最后,利用真实用户数据搭建仿真模型验证了所提算法的有效性,探讨了所提算法在不同场景下的性能表现,并与已有识别算法进行了比较分析。算例表明,所提算法与已有算法相比,可有效识别用户链路关系,且对新能源并网渗透率和数据误差率有较好的鲁棒性。

In view of the voltage characteristic changes brought by the renewable energy integration and the fine-grained need for low-voltage topological relationship identification,a user link identification model based on graph signal processing(GSP)is proposed.The identification model uses the voltage similarity between adjacent nodes to represent the smoothness of the graph signal.The constraints of node current law on network structure are combined to overcome the influence of the in-phase user voltage similarity deterioration caused by renewable energy integration.The inherent link properties of the graph structure are used to realize the identification of the low-voltage topology down to the upstream and downstream connections between users.Finally,the simulation model based on real user data is used to verify the effectiveness of the proposed method.The performance of the proposed methods in different scenarios is discussed,and the proposed method is compared with existing identification methods.The example shows that,compared with the existing methods,the proposed method can effectively identify the user link relationship,and has better robustness to the penetration rate of renewable energy integration and data error rate.