Posters
Come meet the poster presenters to ask them questions and discuss their work
We would like to invite you to come and see the posters at our upcoming conference. The posters will showcase a diverse range of research topics and provide an opportunity for delegates to engage with the authors and learn more about their work. Whether you are a seasoned researcher or simply curious about the latest developments in your field, we believe that the posters will offer something of interest to everyone. So please, join us at the conference and take advantage of this opportunity to learn and engage with your peers in the academic community. We look forward to seeing you there!
PO234: Predicting the capacity factor of wind farms using explainable deep neural networks for estimating age related performance degradation.
Manuel S Mathew, PhD Research Fellow, Universitetet i Agder
Abstract
Being continuously exposed to adverse working environments and fluctuating load conditions, performance of wind energy conversion systems gradually decline over its life cycle. Understanding this age-related performance degradation is essential in efficiently maintaining and managing these capital-intensive assets. For example, this is essential in planning the maintenance and overhauling schedules of the turbines. Further, these degradation patterns can also give insights to the remaining useful life (RUL) of the systems which can then be used for strategizing the repowering and lifetime extension plans for the wind farms. In this paper, we present an efficient DNN model for predicting the capacity factor of wind farms, which is demonstrated with the case of a 400 MW Norwegian farm. Apart from the deep learning approach adopted, the study has the novel feature of applying explainable AI in interpreting the influence of various input features on the predicted capacity factor of the windfarm. The proposed DNN model can be useful in understanding the age-related performance degradation of wind farms. This can be further be extended to the estimation of the remaining useful life of the windfarms, which is an important information for the industry in strategizing the repowering and lifetime extension plans of the windfarms.
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