High-voltage overhead transmission lines are a key element of the power system, and their condition gradually deteriorates due to ageing as well as operational and environmental stresses. To enable data-driven and efficient maintenance, asset health indices are used, which quantitatively combine inspection results, measurements and failure records into a single, comparable assessment of the condition and remaining service life of the equipment.
Developing a standardised methodology for calculating the health index of transmission lines is challenging, since these assets form an extensive linear infrastructure system with interdependent components operating in diverse environments. A uniform methodology has not yet been established, which justifies further research in this area. At ELES, the Slovenian transmission system operator, which manages more than 3000 km of transmission lines and operates in accordance with the ISO 55001 asset management standard, there is a need for a systematic health index to support objective, data-driven maintenance decision making.
This master’s thesis focuses on the development of a methodology for calculating the health index of overhead transmission lines, tailored to the needs of ELES. First, domestic and international approaches, guidelines and good practices of transmission system operators are reviewed. This is followed by a detailed analysis of transmission line components and their ageing mechanisms, based on which suitable ageing models are selected. The methodology comprises three modules, the first uses ageing models, the second evaluates the findings of field inspections and the third quantifies environmental loads. The partial indices of the modules are combined using weights into a single health index at the level of each transmission line. The methodology is demonstrated on data from ELES’s infrastructure.
The proposed methodology enables objective assessment of transmission line condition and transparent prioritisation of maintenance, and supports the transition from time-based to condition-based maintenance. The thesis also provides recommendations for future enhancements, including shifting the assessment to the level of line sections and integrating advanced condition monitoring methods to support more effective asset management.
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