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Optimizing hydro power plant maintenance planning

The School of Engineering FHNW has developed a method to support operators of AXPO hydro power plants.



Identifying the best maintenance scenarios for hydro power plants with the help of linear programming.


Operating hydro power plants in the most efficient way is crucial for economic reasons and to guarantee electricity supply security. The planning complexity of individual plant maintenance optimization arises from diverse configurations of generators, pumps, bypasses and reservoirs and large seasonal variability of hydrological flows and electricity prices. Revenue loss minimization for maintenance windows is a computationally challenging task for which the standard Stochastic Dynamic Programming approaches are limiting in terms of computation time.


The Institute of Data Science FHNW successfully develops an analytical solution from scratch to assess maintenance scenarios of individual hydro power plants. Leveraging a linear programming approach the implemented model reaches predictive accuracy comparable to Stochastic Dynamic Programming for a majority of plants and scenarios. Given the dramatically reduced computational costs our solution is well suited for an interactive planning tool.


Client AXPO
Execution FHNW Institute for Data Science
Duration 6 months
Team Dr. Michael Graber, Prof. Dr. Daniel Perruchoud, Simon Beck


Prof. Dr. André Csillaghy
Prof. Dr. André Csillaghy

Head of FHNW Institute for Data Science

Telephone +41 56 202 76 85 (direct)