Deep Reinforcement Learning Based on Proximal Policy Optimization for the Maintenance of a Wind Farm with Multiple Crews

Luca Pinciroli, Piero Baraldi, Guido Ballabio, Michele Compare and Enrico Zio
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Luca Pinciroli: Energy Department, Politecnico di Milano, 20133 Milan, Italy
Piero Baraldi: Energy Department, Politecnico di Milano, 20133 Milan, Italy
Guido Ballabio: Aramis S.r.l., 20121 Milan, Italy
Michele Compare: Aramis S.r.l., 20121 Milan, Italy
Enrico Zio: Energy Department, Politecnico di Milano, 20133 Milan, Italy

Energies, 2021, vol. 14, issue 20, 1-17

Abstract: 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 Prognostics and Health Management (PHM) capabilities, it is feasible to significantly optimize operation and maintenance (O&M) by combining the (uncertain) information provided by PHM with the other factors influencing O&M activities, including the limited availability of maintenance crews, the variability of energy demand and corresponding production requests, and the long-time horizons of energy systems operation. In this work, we consider the operation and maintenance optimization of wind turbines in wind farms woth multiple crews. A new formulation of the problem as a sequential decision problem over a long-time horizon is proposed and solved by deep reinforcement learning based on proximal policy optimization. The proposed method is applied to a wind farm of 50 turbines, considering the availability of multiple maintenance crews. The optimal O&M policy found outperforms other state-of-the-art strategies, regardless of the number of available maintenance crews.

Keywords: wind turbines; operation and maintenance; prognostics and health management; deep reinforcement learning; imitation learning; proximal policy optimization (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2021
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (8)

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