Abstract
This paper presents a novel framework for the preliminary design of multi-energy Pumped Thermal Energy Storage (m-PTES) systems, also known as Carnot batteries. Built upon Finite Dimension Thermodynamics (FDT), the steady-state approach determines the operating conditions corresponding to near-maximum round-trip efficiency. The proposed method offers three key advantages. It is: 1) general, remaining independent of working fluids and cycle architecture; 2) analytical, relying on few physical parameters to describe system behavior; and 3) computationally very efficient, requiring minimal numerical resources. These attributes make FDT well suited for early-stage design of complex multi-energy PTES systems, where rapid evaluation of thermodynamic potential is essential. The proposed method is applied to a case study in northern Canada to illustrate the influence of main parameters on system performance. The results reveal that the storage temperature has a major impact on all key optimal operating conditions, including intermediate temperature, heat-exchanger conductances and heat rates. From an energetic standpoint, the optimal configuration corresponds to the highest achievable storage temperature. At a storage temperature of 800 °C, when transitioning from the endoreversible case to an irreversible case with 30% internal losses, the round-trip efficiency ηRT decreases almost linearly from 0.63 to 0.42, while the optimal storage capacity CTES increases from 199 MWh to 263 MWh. Overall, this work demonstrates that FDT is a powerful framework for preliminary conceptual m-PTES design, enabling efficient identification of suitable working fluids and boundary conditions for further detailed modeling and optimization.
| Original language | English |
|---|---|
| Article number | 129727 |
| Journal | Applied Thermal Engineering |
| Volume | 289 |
| DOIs | |
| Publication status | Published - Mar 2026 |
!!!Keywords
- Carnot batteries
- Finite dimension thermodynamics
- Multi-energy pumped thermal energy storage
- Optimization
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