Energy Storage Appl., Volume 2, Issue 4 (December 2025) – 5 articles

Current CO₂-based energy storage systems still face several unsolved technical challenges, including strong thermal destruction between the multi-stage compression and expansion processes, significant exergy destruction in heat exchange units, limited utilization of low-grade heat, and the lack of an integrated comprehensive performance framework capable of simultaneously evaluating thermodynamic, economic, and environmental performance. Although previous studies have explored various compressed CO₂ energy storage (CCES) configurations and CCES–Organic Rankine Cycle (ORC) couplings, most works treat the two subsystems separately, neglect interactions between the heat exchange loops, or overlook the combined effects of exergy losses, cost trade-offs, and CO₂-emission reduction. These gaps hinder the identification of optimal operating conditions and limit the system-level understanding needed for practical application. To address these challenges, this study proposes an innovative system that integrates a multi-stage CCES system with ORC. The system introduces ethylene glycol as a dual thermal carrier, coupling waste-heat recovery in the CCES with low-temperature energy utilization in the ORC, while liquefied natural gas (LNG) provides cold energy to improve cycle efficiency. A comprehensive 4E (energy, exergy, economic, and environmental) assessment framework is developed, incorporating thermodynamic modeling, exergy destruction analysis, CEPCI-based cost estimation, and environmental metrics including primary energy saved (PES) and CO₂ emission reduction. Sensitivity analyses on the high-pressure tank (HPT) pressure, heat exchanger pinch temperature difference, and pre-expansion pressure of propane (P₃₀) reveal strong nonlinear effects on system performance. A multi-objective optimization combining NSGA-II and TOPSIS identifies the optimal operating condition, achieving 69.6% system exergy efficiency, a 2.07-year payback period, and 1087.3 kWh of primary energy savings. The ORC subsystem attains 49.02% thermal and 62.27% exergy efficiency, demonstrating synergistic effect between the CCES and ORC. The results highlight the proposed CCES–ORC system as a technically and economically feasible approach for high-efficiency, low-carbon energy storage and conversion. Full article

Molten salt heat exchangers are crucial components in systems requiring high-temperature heat transfer and energy storage, especially in renewable energy and advanced nuclear technologies. Their ability to operate efficiently at high temperatures while offering significant energy storage capacity makes them highly valuable in modern energy systems. They have high thermal stability. In the framework of this research, a computational fluid dynamics (CFD) simulation model of the HITEC molten salt cooling system has been developed. HITEC molten salt is a specialized heat transfer and thermal energy storage medium primarily used in industrial processes and solar thermal power plants. It is a eutectic blend of sodium nitrate, sodium nitrite, and potassium nitrate. COMSOL multi-physics code has been employed in this research. It simultaneously solves the fluid flow, energy, and heat conduction transport equations. Two cases have been investigated in this paper: a water flowing velocity of 1 [m/s] and a water flowing velocity of 10 [m/s]. The results indicate that the maximal surface temperature of the Crofer^®22 H reached 441.2 °C in the first case. The maximal surface temperature of the Crofer^®22 H reached 500 °C in the second case. Crofer^®22 H alloy provides excellent steam oxidation, high corrosion resistance, and thermal creep resistance. The proposed HITEC molten thermal system may be applied in the oil and gas industries and in power plants (such as the Organic Rankine Cycle). Full article

The global decarbonisation strategy has accelerated the shift toward renewable energy and electric transport, demanding advanced electrochemical energy storage systems. Conventional anodes such as graphite and silicon composites face challenges in conductivity, stability and cycling performance. MXenes, a class of two-dimensional (2D) materials, offer promising alternatives owing to their metallic conductivity, tunable surface chemistry and high theoretical capacity. Here, we synthesise and characterise Mo₂TiC₂T_x and V₂CT_x (T = O, OH, F and/or Cl) MXenes for lithium-ion battery anodes and supercapacitors. Unlike Ti₃C₂T_x, which stores charge via intercalation and surface redox reactions, Mo₂TiC₂T_x and V₂CT_x exhibit conversion-type mechanisms. We also identify novel V₂C–VO_x heterostructures, achieving a specific capacitance of 532.4 F g⁻¹ at 2 mV s⁻¹ and an initial capacity of 493.3 mAh g⁻¹ at 50 mA g⁻¹ in lithium half-cells, with a low decay rate of 0.071% per cycle over 200 cycles. Pristine Mo₂TiC₂T_x shows 391.7 mAh g⁻¹ at 50 mA g⁻¹, decaying by 0.109% per cycle. These results experimentally validate theoretical predictions, revealing how MXene structure and transition metal chemistry govern electrochemical behaviour, thus guiding electrode design for next-generation batteries and supercapacitors. Full article

The paper examines the experimental performance of air–rock bed, oil only, and oil–rock bed systems for storing heat suitable for cooking applications. The air–rock bed system is charged using hot air from a compressed air tank, while the oil–rock bed system employs a resistive heating element to heat a small volume of oil, which then circulates naturally. The charging process for the oil systems was controlled by adjusting funnel heights, and temperature measurements were taken using thermocouples connected to a data logger. Both systems can store thermal energy ranging from 4.5 kWh to 8 kWh and achieve temperatures between 150 °C and 300 °C, depending on supply temperatures. The simpler oil–rock bed allows for the direct boiling of water using the high temperature produced, and tests indicated comparable boiling times between systems. The findings suggest that these heat storage systems could enhance the advancement and integration of solar cookers, enabling more flexible cooking options. Full article

The challenge of optimally controlling energy storage systems under uncertainty conditions, whether due to uncertain storage device dynamics or load signal variability, is well established. Recent research works tackle this problem using two primary approaches: optimal control methods, such as stochastic dynamic programming, and data-driven techniques. This work’s objective is to quantify the inherent trade-offs between these methodologies and identify their respective strengths and weaknesses across different scenarios. We evaluate the degradation of performance, measured by increased operational costs, when a reinforcement learning policy is adopted instead of an optimal control policy, such as dynamic programming, Pontryagin’s minimum principle, or the Shortest-Path method. Our study examines three increasingly intricate use cases: ideal storage units, storage units with losses, and lossy storage units integrated with transmission line losses. For each scenario, we compare the performance of a representative optimal control technique against a reinforcement learning approach, seeking to establish broader comparative insights. Full article