Stochastic Wind Park Modelling and Maintenance Scheduling under Uncertainty a Serious Game
The objective of this ESR 3 is to develop novel stochastic models for the operational phase of an offshore wind farm that advance significantly beyond existing models. Current state of the art models simulate weather, power production from the turbines, the transfer of the maintenance crews to the wind park with different access vessels, and the repair of turbine components using publicly available data.
A second objective of the ESR 3 is to develop novel maintenance strategies including the uncertainty in information, e.g., by including weather forecasts with limited accuracy and incomplete information about turbine status.
Bayesian statistical decision theory will be used to derive optimal strategies for maintenance scheduling under such conditions, and will be contrasted with other machine learning approaches.
A final objective is to extend and modify the model to a serious game that has the aim of demonstrating the complexity of running a wind farm to potential end users, decision makers and the general public, and that will create awareness for the advantages and disadvantages of wind energy versus conventional energy sources. This game will be freely distributed as an outreach activity and learning experience. The main scientific objective behind developing the game mechanics is the development of an intelligent and adaptive asset management strategy.
More generally, the objective of the training is to provide ESR3 with in-depth knowledge and the needed capabilities to perform research at the highest level both in an industrial setting as well as in academia. As the topic of ESR3 is cross-disciplinary, this means a thorough engagement with different subjects, exposition to different working environments, and a lot of technical and complementary training.
Tentative schedule: February – May 2016
ForWind – Oldenburg
Tentative schedule: February – May 2017
Seyr, H and Muskulus, M (2016) Value of information of repair times for offshore wind farm maintenance planning, Journal of Physics: Conference Series, 753(092009), DOI: 10.1088/1742-6596/753/9/092009. Full text: http://iopscience.iop.org/article/10.1088/1742-6596/753/9/092009
Seyr, H and Muskulus, M (2016) Safety Indicators for the Marine Operations in the Installation and Operating Phase of an Offshore Wind Farm, Energy Procedia, 94:72-81. DOI: 10.1016/j.egypro.2016.09.200. Full text: http://www.sciencedirect.com/science/article/pii/S1876610216308694
Seyr, H and Muskulus, M (2017) How does Accuracy of Weather Forecasts Influence the Maintenance Cost in Offshore Wind Farms?, Energy Procedia
Seyr, H (2017) The Impact of Maintenance Duration on the Downtime of an Offshore Wind Farm – Alternating Renewal Process, COMADEM 2017 – Best Student Presentation award
BSc in Technical Mathematics
MSc in Applied Economics
Host Institution:Norwegian University of Science and Technology (NTNU)