@article{Cao2026, 
author = {Maosen Cao and Bo Hu and Changzheng Shao and Kaigui Xie and Zilang Xia and Weixin Zhang},
title = {Dynamic Temperature Model of AA-CAES for Reliability Evaluation of IES},
year = {2026},
journal = {CSEE Journal of Power and Energy Systems},
volume = {12},
number = {4},
pages = {2073-2085},
keywords = {AA-CAES, Dynamic temperature model, IES, Multi-state Markov model},
url = {https://www.sciopen.com/article/10.17775/CSEEJPES.2022.04130},
doi = {10.17775/CSEEJPES.2022.04130},
abstract = {Integrated energy systems (IES) have become popular in the sector of energy supply because of advancement of energy intelligent technologies. Advanced adiabatic compressed air energy storage (AA-CAES) is an expansible physical energy storage technology with great potential in peak regulation and renewables accommodation. While AA-CAES improves energy efficiency, internal component failure and partial failure between different subsystems induce multiple operational risks for IES. In this paper, a multi-state Markov model is proposed for reliability evaluation of AA-CAES considering partial function failure. The reliability-oriented dynamic optimal energy flow (DOEF) model and reliability evaluation framework for IES considering AA-CAES are proposed. By considering dynamic temperature characteristics of thermal energy storage (TES) tank, reliability evaluation of IES can be more accurate. Under appropriate assumptions and simplifications, the highly nonlinear dynamic temperature model (DTM) is turned into a linear programming problem. A testing system is used to validate the proposed model and approach.}
}