A key use case motivating this work is the integration of PTES systems with wind farms to enable dispatchable operation. In previous work [2], we addressed this challenge by designing a scheduling optimization problem to manage the PTES system's state of charge given wind power and electricity price profiles, aiming to maximize profit through charge–discharge scheduling over a time horizon of five days. That study was based on a quasi-steady-state model, which did not capture transient behaviour and assumed ideal and instantaneous transitions between operating modes.
Building upon this, we introduce a dynamic simulation model developed in MATLAB Simulink to assess the feasibility and performance of the proposed operation strategies under more realistic conditions. Charge and discharge power setpoints are now generated by the higher-level optimization layer, aimed at maximizing profit, while the full dynamic behaviour of the system is captured in simulation, including key components such as the thermal storage units, heat exchangers, and turbomachinery.
Simulation scenarios encompass dynamic charging and discharging, start-up, shutdown, and provision of grid services. The results show that the thermal inertia—particularly in the heat exchangers—act as a limiting factor in the system, while the power block exhibits faster dynamics. The dynamic model enables to quantify these limitations and assess their implications for grid integration.
To enable reliable dynamic operation, we develop a plantwide control strategy focused on tracking the charge–discharge power setpoints generated by the scheduling layer. The control architecture is informed by a plantwide analysis and implemented using a network of temperature, pressure, and flow control loops [3]. Turbomachinery units are operated under variable-speed control, and cascade arrangements are employed where appropriate to enhance control performance. This coordinated control structure ensures stable and responsive operation across all regimes while respecting component and system-level constraints.
The integrated control and simulation framework presented here is particularly relevant for ancillary services such as secondary frequency regulation, which require power modulation over timescales of tens of seconds to several minutes. Wind turbines and variable frequency pumped hydro energy storage systems, for instance, have demonstrated the technical capability to provide such services through automatic generation control mechanisms [4,5], and similar functionality is enabled in PTES systems through proper control system design. This work demonstrates the importance of coupling high-level scheduling with dynamic simulation and control system design to evaluate the true performance potential of PTES systems under realistic, time-varying grid conditions.
References:
[1] Sharma, S., & Mortazavi, M. (2023). Pumped thermal energy storage: A review. International Journal of Heat and Mass Transfer, 213, 124286.
[2] Albay, A., Zhu, Z., & Mercangöz, M. (2025). Optimization-based state-of-charge management strategies for supercritical CO₂ Brayton cycle pumped thermal energy storage systems. Journal of Energy Storage, 111, 115387.
[3] Luyben, W. L., & Tyreus, B. D. (1997). Plantwide control design procedure. AIChE Journal, 43(12), 3161–3174. https://doi.org/10.1002/aic.690431205
[4] Gevorgian, V., & Zhang, Y. (2020). Ancillary services from wind turbines: Automatic generation control from a single Type 4 turbine. Wind Energy Science, 5(2), 225–236. https://wes.copernicus.org/articles/5/225/2020/
[5] Zhu, Z., Pan, W., Liu, T., & Liu, M. (2023). Frequency response mechanism modeling and performance analysis of adjustable-speed pumped storage unit. Power System Technology, 47, 463–474.