Prognostic and Health Management in Ocean Energy System A Self-Healing Framework based on Reinforcement Learning
preprintposted on 2020-07-30, 23:10 authored by Yufei TangYufei 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.
Email Address of Submitting Authortangy@fau.edu
Submitting Author's InstitutionFlorida Atlantic University
Submitting Author's Country
- United States of America