Deep reinforcement learning for cost-optimal condition-based maintenance policy of offshore wind turbine components

J Cheng, Y Liu, W Li, T Li - Ocean Engineering, 2023 - Elsevier
… Life cycle cost analysis of the offshore wind turbine In this paper, the life cycle costs of an
offshore wind turbine component are the maintenance costs including inspection costs, repair …

Deep reinforcement learning based on proximal policy optimization for the maintenance of a wind farm with multiple crews

L Pinciroli, P Baraldi, G Ballabio, M Compare, E Zio - Energies, 2021 - mdpi.com
… The life cycle of wind turbines depends on the operation and maintenance policies adopted.
With the critical components of wind turbines being equipped with condition monitoring and …

Deep reinforcement learning based preventive maintenance for wind turbines

W Dong, T Zhao, Y Wu - … on energy internet and energy system …, 2021 - ieeexplore.ieee.org
… the complex wind turbine system with many components and the … in this paper: e The wind
turbine system is reduced to four … of wind turbines are depicted by four in-series components, …

Optimization of the operation and maintenance of renewable energy systems by deep reinforcement learning

L Pinciroli, P Baraldi, G Ballabio, M Compare, E Zio - Renewable Energy, 2022 - Elsevier
… functioning of the plant's components, reducing the risk of … condition-based maintenance in
offshore wind farms. In Ref. [65… a wind farm taking into account the stochasticity of wind power

Power regulation and load mitigation of floating wind turbines via reinforcement learning

J Xie, H Dong, X Zhao - IEEE Transactions on Automation …, 2023 - ieeexplore.ieee.org
… Zhao, “Intelligent wind farm control via deep reinforcement learning and high-fidelity …
De Breuker, “Fatigue and extreme load reduction of wind turbine components using smart …

Deep reinforcement learning for maintenance planning of offshore vessel transfer

J Chatterjee, N Dethlefs - … in renewable energies offshore, 2020 - taylorfrancis.com
… an offshore wind farmoffshore wind turbine, and we use his toric time-series data captured
through sensors (includ ing meteorological data, mechanical and electrical sub component

… Inspection and Maintenance Planning for Deteriorating Structures via Markov Decision Processes and Deep Reinforcement Learning. Application to Offshore Wind …

PG Morato Dominguez - 2021 - orbi.uliege.be
… to the management of offshore wind substructures, both at component and system levels. In
… of offshore wind substructures, both at the offshore wind turbine and offshore wind farm levels…

Composite experience replay-based deep reinforcement learning with application in wind farm control

H Dong, X Zhao - IEEE Transactions on Control Systems …, 2021 - ieeexplore.ieee.org
In this article, a deep reinforcement learning (RL)-… wind farm control problem. Specifically,
a novel composite experience replay (CER) strategy is designed and embedded in the deep

[HTML][HTML] Self-adaptive optimized maintenance of offshore wind turbines by intelligent Petri nets

A Saleh, M Chiachío, JF Salas, A Kolios - Reliability Engineering & System …, 2023 - Elsevier
… Petri net modelling with Reinforcement Learning and is … that is solved through Deep
Reinforcement Learning (DRL) [44]… , these states differ from component to component, with a …

Jointly improving energy efficiency and smoothing power oscillations of integrated offshore wind and photovoltaic power: a deep reinforcement learning approach

X Yin, M Lei - Protection and Control of Modern Power Systems, 2023 - ieeexplore.ieee.org
… In this paper, the NREL offshore 5-MW baseline wind turbine is considered for the … 3, the
overall control architecture comprises three parts, ie, the Actor networks (online actor and target …