MVEX01-17-17 Wind power plant maintenance near the end-of-life

Wind power is a growing means of electricity generation, and probably crucial to increase the reliability of, in order to contribute to a healthy environment on planet Earth. Wind power owners’ concern about maintenance schedules towards the wind turbine end-of-life, say the last five years, is governed mainly by financial issues rather than reliability issues. 

This means that preventive replacements (that is, replacing one or several components before they need to be scrapped) towards the turbine end-of-life are not preferred and should be avoided. This is contradictory to most maintenance optimization models in the field, which do not consider this aspect of scheduling. The optimization group has worked within this field of mathematical modelling since 2001, and would like to investigate the extension of the so-far best model (known as the PMSPIC) to include this aspect of the model. That is goal #1.

Furthermore, there is another area of improvement that is connected to the discrete time steps at which the decisions can be made. In previous work written among the research group Mathematical Sciences/Optimization we have considered a rather large time step of 1 month. One question to be solved is this: is it possible to create an initial schedule with this large time step, and then go into more detail and optimize it over a finer time step like once per day, considering the weather and power forecasts – i.e., creating a kind of discretization approach to the problem?

These two activities can either be divided into two group works, then combined at the end, or be performed jointly. 

Obs! För GU-studenter räknas projektet som ett projekt i Tillämpad Matematik (MMG900/MMG920).

Projektkod MVEX01-17-17
Gruppstorlek 3-4 studenter
Förkunskapskrav good grades on TMA947/MMG620 and/or TMA521/MMA511
Handledare Michael Patriksson,, Quanjiang Yu,​ 
Examinator Maria Roginskaya, Marina Axelson-Fisk
Institution Matematiska Vetenskaper

Sidansvarig Publicerad: on 09 nov 2016.