Prioritisation of faults in district heating substations: Towards predictive maintenance and optimised operation

Effectively detecting and handling faults in district heating substations is vital to ensure the security of heat supply and improve system efficiency. This is a challenging task due to the growing number of substations and limited monitoring and service personnel. Digitalisation on the demand side offers an opportunity to develop data-driven methods for automatic fault detection, enabling utilities to optimise maintenance interventions across multiple customers. A variety of different faults can occur in substations, which can reflect differently on operational data. It is then necessary to prioritise faults to address the most relevant ones in developing adequate detection methods and supporting operators in their Operation and Maintenance (O&M) processes. Failure Modes and Effects Analysis (FMEA) is a widely used methodology to prioritise potential failures, but it misses aspects relevant to O&M. In this study, we propose an adaptation of the original FMEA for the prioritisation of faults with focus on O&M optimisation. The methodology uses a Maintenance Priority Number (MPN) for the ranking of faults based on severity, occurrence, monitoring potential and maintenance capability of the fault. Severe and frequent faults, which have a potential to be monitored and maintained yield the highest MPNs and should be in focus from an O&M perspective. Using the proposed methodology the most relevant faults for predictive maintenance in substations in Germany have been identified. These are the contamination of screening devices, pump failures and fouling of heat exchangers. These faults should be in focus when developing automatic fault detection and diagnosis methods. • FMEA adaptation to prioritise faults for predictive maintenance. • Comprehensive list of faults in district heating substations adds German experience. • Rating criteria for the evaluation of faults in district heating substations. • Prioritisation of faults in district heating substations for predictive maintenance. • Fault evaluation survey with German district heating practitioners.