TechRxiv
Abstract_ICOE_2020_Prognostic and health management in ocean energy system A self-healing framework based on reinforcement learning.pdf (561.11 kB)

Prognostic and Health Management in Ocean Energy System A Self-Healing Framework based on Reinforcement Learning

Download (561.11 kB)
preprint
posted on 30.07.2020 by Yufei Tang
In this paper, for minimizing the cost from the ocean generator power production by optimizing the operation and maintenance (O&M) policy over an infinite time horizon, while considering the uncertainty of the renewable sources and components failure behaviors, we develop a self-healing framework for ocean energy systems. It consists of three major modules: data manipulation, health assessment, and decision-making. Specifically, a graph-theoretic approach is first proposed for ocean generator health monitoring utilizing multivariate time-series data, then, reinforcement learning (RL) based technique exploits the health states of the system that provides decision support for optimal O&M management.

Funding

ECCS-1809164

History

Email Address of Submitting Author

tangy@fau.edu

Submitting Author's Institution

Florida Atlantic University

Submitting Author's Country

United States of America

Licence

Exports