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, 23:10 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