含特殊负荷的配电网分层故障定位方法

特殊负荷接入配电网，增强了电源、负荷与电网之间的互动性，对故障定位提出了更高的要求，为此，提出了一种快速定位故障点的分层定位方法. 首先分析基于遗传算法的单层含特殊负荷配电网故障定位的不完备性；其次在单层模型的理论基础上，提出改进量子免疫算法的区域定位方法和隐枚举法的区段定位方法；最后对所提模型和基于单一智能算法的单层模型进行了对比仿真实验. 结果表明:与遗传算法、免疫算法和改进量子免疫算法构建的单层定位模型相比，所提分层定位方法大大简化了故障辨识模型的复杂度，在提高定位效率的同时保证了定位的容错性和稳定性，可将故障搜索维度降低69%，故障定位耗时在1 s以内，故障辨识率达到100%. 

Hierarchical Fault Location Method for Distribution Network with Special Load

Special load is connected to the distribution network, which enhances the interaction between the power supply, load and power grid, and imposes higher requirements for fault location. To deal with this, a hierarchical location method for fast locating fault points is proposed. Firstly, the incompleteness of the genetic algorithm based fault location model is analyzed for single-layer distribution network with special load. Secondly, based on the theory of the single-layer model, a regional positioning method and a segment method are proposed, which respectively improves quantum immune algorithm and implicit enumeration method. Finally, a comparative simulation is carried out between the proposed model and the single-layer model that is based on a single intelligent algorithm. Compared with the genetic algorithm, immune algorithm and improved single-layer positioning model constructed by quantum immune algorithm, the hierarchical positioning method can greatly simplify the complexity of the fault identification model, ensure the fault tolerance and stability of the positioning while improving the positioning efficiency. In addition, this method reduces the fault search dimension by 69%, takes less than 1s to locate the fault, and the fault identification rate is 100%.