Coordinated Control and Parameter Optimization for the Energy Release Process of Large-Scale A-CAES

Large-scale adiabatic compressed air energy storage (A-CAES) is essential for stabilizing power grids with high renewable energy penetration. However, the complex thermo-mechanical coupling in its multistage expansion and reheat systems poses significant challenges for dynamic control and operational safety. This study develops a coordinated control framework for the A-CAES energy release process. Based on control-oriented characteristic analysis revealing bidirectional power–temperature coupling mechanisms, a power setpoint feedforward decoupling strategy is proposed, reducing the stage-averaged temperature dynamic deviation of the four expander inlet temperatures from 7.74 K to 1.57 K during the upward power ramp. Furthermore, the gradient-based optimization (GBO) algorithm with the piecewise reset ITAE objective function is employed to optimize the PI controller parameters, yielding stage-averaged temperature dynamic deviations of 1.882 K and 2.249 K during AGC ramp-up and ramp-down, respectively, corresponding to reductions of 27% and 26% relative to empirical tuning. Numerical simulations of load rejection and three-phase short-circuit faults indicate the system’s dynamic stability and safety margins under the considered extreme conditions. This work provides model-based technical support for a 300 MW-class A-CAES demonstration project.

Authors

Institutions

Publication Details

Journal
Energies
Published
2026-08-17
DOI
https://doi.org/10.3390/en19163856
Primary Topic
Thermodynamic and Exergetic Analyses of Power and Cooling Systems
Type
article
Field-Weighted Citation Impact
0.00

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Coordinated Control and Parameter Optimization for the Energy Release Process of Large-Scale A-CAES

Junfeng Liu, Wen Chen, Jun Zeng, Zhigang Liu et al.
Energies
Thermodynamic and Exergetic Analyses of Power and Cooling Systems
article

Coordinated Control and Parameter Optimization for the Energy Release Process of Large-Scale A-CAES

Junfeng Liu, Wen Chen, Jun Zeng, Zhigang Liu, Shi Liu, Hua Li
article en

Abstract

Large-scale adiabatic compressed air energy storage (A-CAES) is essential for stabilizing power grids with high renewable energy penetration. However, the complex thermo-mechanical coupling in its multistage expansion and reheat systems poses significant challenges for dynamic control and operational safety. This study develops a coordinated control framework for the A-CAES energy release process. Based on control-oriented characteristic analysis revealing bidirectional power–temperature coupling mechanisms, a power setpoint feedforward decoupling strategy is proposed, reducing the stage-averaged temperature dynamic deviation of the four expander inlet temperatures from 7.74 K to 1.57 K during the upward power ramp. Furthermore, the gradient-based optimization (GBO) algorithm with the piecewise reset ITAE objective function is employed to optimize the PI controller parameters, yielding stage-averaged temperature dynamic deviations of 1.882 K and 2.249 K during AGC ramp-up and ramp-down, respectively, corresponding to reductions of 27% and 26% relative to empirical tuning. Numerical simulations of load rejection and three-phase short-circuit faults indicate the system’s dynamic stability and safety margins under the considered extreme conditions. This work provides model-based technical support for a 300 MW-class A-CAES demonstration project.

EnergiesVol. 19(16)
China Southern Power Grid (China) (CN), South China University of Technology (CN)
National Key Research and Development Program of China
Affordable and clean energy
Openalex Percentile: Top 18%
Thermodynamic and Exergetic Analyses of Power and Cooling Systems
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.