Data Mining of Transformer Frequency Response Analysis (FRA) Results for Characterisation and Interpretation

变压器频率响应分析 (FRA) 结果的数据挖掘，用于表征和解释

• 批准号: 1964639
• 金额: --
• 依托单位: University of Manchester
• 依托单位国家: 英国
• 项目类别: Studentship
• 财政年份: 2017
• 资助国家: 英国
• 起止时间: 2017 至 无数据
• 项目状态: 已结题
• 来源: https://gtr.ukri.org/projects?ref=studentship-1964639
• 关键词: Data; Mining; Transformer; Frequency; Response

The infrastructure and equipment in the UK electrical power transmission system are encountering the issue of ageing, whilst the integration of renewable energy generations is expected to increase which continually challenge the capacity of accommodation renewable energy resource into the grid. A substantial proportion of transformers has been operated well beyond their designed lifetime, mainly due to low utilisation and good maintenance. Hence, it is essential to manage these aged assets in a safe and cost-effective manner to avoid catastrophic failures. One of the main challenges faced by asset managers is the unavailability of historical details dated to these transformers, including their designs. The analysis of frequency response measurements is effectively used for the determination of mechanical malfunction of transformers. This project focuses on data mining and mathematical modelling techniques to support asset managers to identify transformers with common design aspects and latent mechanical problems through the analysis of Frequency Response Analysis (FRA) measurement results, in addition to expert knowledge and forensic analysis. The research output is envisaged to allow incorporating more targeted management techniques to those individual transformer asset groups.The tasks of this project are: 1. Collect all the available FRA measurements and establish a database in acommon format that enables automatic processing.2. Develop an algorithm to process all the FRA measurements and identify similarmeasurements and hence similar transformers.The FRA measurement results to be used in the project will be from transformersbelonging to National Grid. Hence, the student will have the opportunity to spend aconsiderable amount of time in National Grid as well as to work closely with theirtransformer asset management. In order to achieve the tasks mentioned above, the student should conduct the project by using programming software, such as Matlab or C++ language, to develop new codes to implement the analysis of the FRA measurements. The conditions of aged transformer in service hopefully can be determined by analysing the results of FRA measurements according to the relevant standards of IEC and IEEE. In addition, the student will have the opportunity to attend local and international conferences during their study to share knowledge with other experts in the same area.

英国电力传输系统中的基础设施和设备正面临老化的问题，而可再生能源发电的整合预计将增加，这将不断挑战可再生能源进入电网的能力。大部分变压器的运行时间远远超过其设计寿命，主要原因是利用率低和维护良好。因此，必须以安全和具有成本效益的方式管理这些老化资产，以避免灾难性故障。资产管理公司面临的主要挑战之一是无法获得这些变压器的历史细节，包括其设计。频率响应测量的分析是有效地用于确定变压器的机械故障。该项目侧重于数据挖掘和数学建模技术，以支持资产管理人员通过分析频率响应分析（FRA）测量结果，以及专业知识和法医分析来识别具有常见设计方面和潜在机械问题的变压器。研究成果的设想是将更有针对性的管理技术纳入这些个别Transformer资产组。收集所有可用的FRA测量数据，并建立一个通用格式的数据库，以便自动处理.开发一种算法来处理所有FRA测量结果，并识别类似的测量结果和类似的变压器。项目中使用的FRA测量结果将来自国家电网的变压器。因此，学生将有机会在国家电网度过相当长的时间，并与他们的变压器资产管理密切合作。为了实现上述任务，学生应该通过使用编程软件，如Matlab或C++语言，开发新的代码来实现FRA测量的分析。根据IEC和IEEE的相关标准，通过对FRA测试结果的分析，可以确定老化Transformer在役的状态。此外，学生将有机会在学习期间参加当地和国际会议，与同一领域的其他专家分享知识。