Multi-State Reliability Assessment Model of Base-Load Cyber-Physical Energy Systems (CPES) during Flexible Operation Considering the Aging of Cyber Components

Abstract

Cyber-Physical Energy Systems (CPESs) are energy systems which rely on cyber components for energy production, transmission and distribution control, and other functions. With the penetration of Renewable Energy Sources (RESs), CPESs are required to provide flexible operation (e.g., load-following, frequency regulation) to respond to any sudden imbalance of the power grid, due to the variability in power generation by RESs. This raises concerns on the reliability of CPESs traditionally used as base-load facilities, such as Nuclear Power Plants (NPPs), which were not designed for flexible operation, and more so, since traditionally only hardware components aging and stochastic failures have been considered for the reliability assessment, whereas the contribution of the degradation and aging of the cyber components of CPSs has been neglected. In this paper, we propose a multi-state model that integrates the hardware components stochastic failures with the aging of cyber components, and quantify the unreliability of CPES in load-following operations under normal/emergency conditions. To show the application of the reliability assessment model, we consider the case of the Control Rod System (CRS) of a NPP typically used for a base-load energy supply.

A sequential decision problem formulation and deep reinforcement learning solution of the optimization of O&M of cyber-physical energy systems (CPESs) for reliable and safe power production and supply

“…Such control system is not only exposed to components stochastic failures, but also to cyber failures that can contribute to the ALFRED unreliability [63,67,68]; however in this work, the components are considered subjected only to stochastic failures over a mission time 𝑇 𝑀 of 5 years (1825 days)…”

Guest Editorial: Special Issue of ESREL2020 PSAM15

“…The last paper in the Special Issue is by Zhaojun Hao, Francesco Di Maio, and Enrico Zio, which presents a multi-state model for incorporating the hardware components' stochastic failures with the aging of cyber components, and quantifying the unreliability of cyber-physical energy systems in load-following operations [7].…”