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Projects

Optimizing hydro power plant maintenance planning, FHNW School of Engineering and Environment

School of Engineering and Environment


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

Top Bild i4Ds

Project details

Type
Research project
Topics
Data science and engineering, Computer science and data science and Technologies and engineering
University
FHNW School of Computer Science / Institute of Data Science
Partner
AXPO
Running time
6 Months
Management
Dr. Michael Graber, Prof. Dr. Daniel Perruchoud, Simon Beck

Objectives

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

Background

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.

Results

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.


Projectdetails

Type
Research project
Topics
Data science and engineering, Computer science and data science and Technologies and engineering
University
FHNW School of Computer Science / Institute of Data Science
Partner
AXPO
Running time
6 Months
Management
Dr. Michael Graber, Prof. Dr. Daniel Perruchoud, Simon Beck

Contact us

For further information about the FHNW School of Computer Science or to discuss potential collaboration opportunities, please contact us.

André Csillaghy

Prof. Dr. André Csillaghy

Head of FHNW Institute for Data Science
Phone
+41 56 202 76 85 (Direct)
E-Mail
andre.csillaghy@fhnw.ch

More Projects

DrugSafety: Semi-automated reporting of side effects of drugs

A system for extracting relevant information from medical reports in order to report side effects of drugs semi-automatically to the responsible authorities.
Institute
School of Engineering and Environment

Marvel: Real-time pollen information

Together with our project partners, we develop zero-shot learning and other machine learning tools for recognising pollen particles anywhere in the world. As a result, it will be easier to create reliable pollen weather forecasts.
Research field
AI, Machine Learning & Natural Language Processing (NLP), Exploratory Data Science and Image Processing & Computer Vision

Knowledge Assistant – AI-based information retrieval tool

AI can organise and retrieve information – at least in theory. In practice, turning corporate data into a user-friendly resource is a big challenge. Our collaboration project tackles the challenge.
Research field
AI, Machine Learning & Natural Language Processing (NLP)

School of
Engineering and Environment FHNW University of Applied Sciences and Arts Northwestern Switzerland

  • About the School
    • FHNW School of Engineering and Environment
    • Degree Programmes
    • Continuing Education
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  • About FHNW
    • Organisation
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    • IT Support
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    • Webmail
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