Small World Stratification for Power System Fault Diagnosis with Causality

基于因果关系的电力系统故障诊断的小世界分层本项目的目标是利用小世界（SW）策略和分层聚类（HC）技术，研究和开发配电系统的因果关系故障诊断方法，以大幅提高故障诊断的准确性和推理能力。智力优势：本课题的智力优势在于：(1)有效、高效地利用现有信息进行准确的配电故障诊断，发现正确的故障因果关系知识，从而大大提高后续配电故障的预测和缓解控制。(2)建议的工作将提供一个总体框架，从中评估具有相似症状的案例，地理环境和故障诊断的拓扑连通性，并将给出因果关系的背景。本项目将以电力分配（一个典型的复杂系统）为测试平台，评估小世界（SW）策略和层次聚类（HC）技术在复杂系统因果故障诊断中的有效性。更广泛的影响：该框架可以应用于各种其他技术领域，包括电力传输系统，运输系统，制造系统，医疗保健系统，能源系统，国土安全，它将促进性能改进和故障诊断技术的进步。这个项目的教育部分涉及研究生和本科生的研究、高级设计项目、部门研讨会和高中在大学实验室的实习。技术和其他成果将整合到课程和课程中。该项目已与当地一家公用事业公司（Progress Energy）建立了工业合作，涉及学生实习生。通过论文、会议演讲、教程、短期课程和一个专门的公众网站，及时向研究界和技术界以及公众传播研究成果。

Small World Stratification for Power System Fault Diagnosis with CausalityThe objective of this project is to investigate and develop a fault diagnosis with causality methodology for power distribution systems using Small World (SW) strategy and Hierarchical Clustering (HC) technology to substantially improve fault diagnosis accuracy and reasoning. Intellectual Merit:The intellectual merits of this project are: (1) The proposed work can provide effective and efficient use of available information to give accurate power distribution fault diagnosis and to discover proper fault causality knowledge, which can substantially enhance the subsequent power distribution fault prognosis and mitigation control. (2) The proposed work will provide a general framework from which to evaluate cases with similar symptoms, geographical settings and topological connectivity for the fault diagnosis and will give the context for causality. The project will use power distribution (a typical complex system) as a test bed to evaluate the effectiveness on the investigation of using Small World (SW) strategy and Hierarchical Clustering (HC) technology for fault diagnosis with causality on complex systems.Broader Impacts: The framework can be applied to a wide variety of other technical areas, including power transmission systems, transportation systems, manufacturing systems, healthcare systems, energy systems, homeland security where it will facilitate performance improvements and advancements in fault diagnosis technologies.The educational component of this project pertains to graduate and undergraduate research, senior design projects, departmental seminars, and high school internships at the university laboratory. Technologies and other results will be integrated into courses and curriculum. Industrial collaboration with a local utility company (Progress Energy) involving student interns has been established for this project. Timely dissemination of research results to the research and technical community as well as the general public will occur through papers, conference presentations, tutorials, short courses and a dedicated publicly accessible website.