All Outputs (6)

Explainable AI for Intelligent Decision Support in Operations & Maintenance of Wind Turbines (2020)
Conference Proceeding
Chatterjee, J. (2020). Explainable AI for Intelligent Decision Support in Operations & Maintenance of Wind Turbines. In J. M. Alonso, & U. Cortés (Eds.), Proceedings of the 1st Doctoral Consortium at the European Conference on Artificial Intelligence (DC-ECAI2020-proceedings) (53-54)

As global efforts in transitioning to sustainable energy sources rise, wind energy has become a leading renewable energy resource. However, turbines are complex engineering systems and rely on effective operations & maintenance (O&M) to prevent catas... Read More about Explainable AI for Intelligent Decision Support in Operations & Maintenance of Wind Turbines.

Deep reinforcement learning for maintenance planning of offshore vessel transfer (2020)
Conference Proceeding
Chatterjee, J., & Dethlefs, N. (2020). Deep reinforcement learning for maintenance planning of offshore vessel transfer. In C. Guedes Soares (Ed.), Developments in Renewable Energies Offshore Proceedings of the 4th International Conference on Renewable Energies Offshore (RENEW 2020, 12 - 15 October 2020, Lisbon, Portugal) (435-443)

Offshore wind farm operators need to make short-term decisions on planning vessel transfers to turbines for preventive or corrective maintenance. These decisions can play a pivotal role in ensuring maintenance actions are carried out in a timely and... Read More about Deep reinforcement learning for maintenance planning of offshore vessel transfer.

A Dual Transformer Model for Intelligent Decision Support for Maintenance of Wind Turbines (2020)
Conference Proceeding
Chatterjee, J., & Dethlefs, N. (2020). A Dual Transformer Model for Intelligent Decision Support for Maintenance of Wind Turbines. In 2020 International Joint Conference on Neural Networks (IJCNN). https://doi.org/10.1109/IJCNN48605.2020.9206839

© 2020 IEEE. Wind energy is one of the fastest-growing sustainable energy sources in the world but relies crucially on efficient and effective operations and maintenance to generate sufficient amounts of energy and reduce downtime of wind turbines an... Read More about A Dual Transformer Model for Intelligent Decision Support for Maintenance of Wind Turbines.

Temporal Causal Inference in Wind Turbine SCADA Data Using Deep Learning for Explainable AI (2020)
Journal Article
Chatterjee, J., & Dethlefs, N. (2020). Temporal Causal Inference in Wind Turbine SCADA Data Using Deep Learning for Explainable AI. Journal of Physics: Conference Series, 1618(2), Article 022022. https://doi.org/10.1088/1742-6596/1618/2/022022

© 2020 Published under licence by IOP Publishing Ltd. Machine learning techniques have been widely used for condition-based monitoring of wind turbines using Supervisory Control & Acquisition (SCADA) data. However, many machine learning models, inclu... Read More about Temporal Causal Inference in Wind Turbine SCADA Data Using Deep Learning for Explainable AI.

The Promise of Causal Reasoning in Reliable Decision Support for Wind Turbines (2020)
Presentation / Conference
Chatterjee, J., & Dethlefs, N. (2020, August). The Promise of Causal Reasoning in Reliable Decision Support for Wind Turbines. Paper presented at Fragile Earth: Data Science for a Sustainable Planet. KDD 2020, Virtual Conference

The global pursuit towards sustainable development is leading to increased adaptation of renewable energy sources. Wind turbines are promising sources of clean energy, but regularly suffer from failures and down-times, primarily due to the complex en... Read More about The Promise of Causal Reasoning in Reliable Decision Support for Wind Turbines.

Deep learning with knowledge transfer for explainable anomaly prediction in wind turbines (2020)
Journal Article
Chatterjee, J., & Dethlefs, N. (2020). Deep learning with knowledge transfer for explainable anomaly prediction in wind turbines. Wind energy, 23(8), 1693-1710. https://doi.org/10.1002/we.2510

The last decade has witnessed an increased interest in applying machine learning techniques to predict faults and anomalies in the operation of wind turbines. These efforts have lately been dominated by deep learning techniques which, as in other fie... Read More about Deep learning with knowledge transfer for explainable anomaly prediction in wind turbines.