Context
Utilities operating hydro power plants require asset condition monitoring to support maintenance decisions across the hydro generation fleet.
Challenge
Asset maintenance in hydro power plants is reactive and fragmented, leading to unplanned downtime and higher costs. Maintenance operators require early identification of emerging equipment issues to enable timely intervention.
AI Solution
Applied AI to analyse operational data from hydro power plants, detect anomalies early, and generate alarms for maintenance operators. The value‑based maintenance approach focuses on identifying deviations at an early stage to support prompt response.
Impact & evidence
The solution enables monitoring of the condition of the hydro fleet by directing operator attention to detected issues rather than manual issue identification. Operators focus on analysing relevant faults instead of searching for them. Early failure detection supports a reduction in unplanned maintenance.
Implementation / Adoption
Implementation of the solution has been enabled by the consolidation of operational hydro plant data in a cloud environment and the standardisation of metadata across plants, supported by internal data science and machine learning engineering capabilities. Data intake activities began in 2019 and were followed by continuous additions of capabilities, improvements, and scale‑outs, allowing the solution to be progressively applied across the hydro fleet. This foundation has supported deployment across hydro operations in Sweden and Finland and underpins the ability to replicate the solution across additional plants.
Furthermore, replication of this solutions requires consolidated operational data in cloud environment, standardized metadata across plants, as well as internal skills in data science and machine learning engineering.
Data
The solution uses internal operational data from hydro power plants and weather data. Data conditions include consolidated operational data in a cloud environment and standardised metadata across plants.
Future enhancements
Planned enhancements include scale‑out to additional plants, coverage of additional failure modes, and further integration into the issue management process.
