Numerical and experimental analysis of weathering effect in liquid air tank of liquid air energy storage system

Decoupled integration of air separation unit and liquid air energy storage for enhanced efficiency, economic, and environmental performance

A review of advancements in liquid air energy storage: system architecture, integration strategies, and thermodynamic analysis

Thermodynamic analysis of a liquid air energy storage system integrated with liquefied natural gas cold energy recovery

Improved liquid air energy storage process utilizing LNG cold energy: Continuous and flexible energy storage

Conceptualisation and analysis of a Brayton cycle operational strategy for solar-aided liquid air energy storage

The model of a liquid desiccant dehumidification air conditioning (LDAC) system is one of the key foundations for achieving efficient cooling, dehumidification and regeneration, and saving energy consumption. The data-driven modeling method does not need to understand the complex heat and mass transfer mechanism and equipment physical information, thus the modeling complexity is greatly reduced. This paper proposes a temperature and humidity prediction model integrating the Black Kite Algorithm (BKA), Bidirectional Temporal Convolutional Network (BiTCN), Bidirectional Long Short-Term Memory (BiLSTM), and Self-Attention mechanism (SA). The model extracts local spatiotemporal features from sequence data through BiTCN, enhances the understanding of contextual dependencies in temporal data using BiLSTM, and employs the SA to assign dynamic weights to different time steps. Furthermore, BKA is adopted to optimize the hyperparameter combinations of the neural network, thereby improving prediction accuracy. To validate the model performance, an experimental platform for an LDAC system was established to collect operational data under multiple working conditions, constructing a comprehensive dataset for simulation analysis. Experimental results demonstrate that compared to conventional time-series prediction models, the proposed model achieves higher accuracy in predicting outlet temperature and humidity across various operating conditions, providing reliable technical support for system real-time control and performance optimization.

The increasing share of renewable energy sources (RES) in modern power systems necessitates the development of efficient, large-scale energy storage technologies capable of mitigating generation variability. Liquid Air Energy Storage (LAES), particularly in its adiabatic form, has emerged as a promising candidate by leveraging thermal energy storage and high-pressure air liquefaction and regasification processes. Although LAES has been widely studied, the impact of ambient temperature on its performance remains insufficiently explored. This study addresses that gap by examining the thermodynamic response of an adiabatic LAES system under varying ambient air temperatures, ranging from 0 °C to 35 °C. A detailed mathematical model was developed and implemented in Aspen Hysys to simulate the system, incorporating dual refrigeration loops (methanol and propane), thermal oil intercooling, and multi-stage compression/expansion. Simulations were conducted for a reference charging power of 42.4 MW at 15 °C. The influence of external temperature was evaluated on key parameters including mass flow rate, unit energy consumption during liquefaction, energy recovery during expansion, and round-trip efficiency. Results indicate that ambient temperature has a marginal effect on overall LAES performance. Round-trip efficiency varied by only ±0.1% across the temperature spectrum, remaining around 58.3%. Mass flow rates and power output varied slightly, with changes in discharging power attributed to temperature-driven improvements in expansion process efficiency. These findings suggest that LAES installations can operate reliably across diverse climate zones with negligible performance loss, reinforcing their suitability for global deployment in grid-scale energy storage applications.

Abstract Following the widespread use of microflow from nl min −1 to μl min −1 in fields such as biotechnology, organic chemistry and the automotive industry, there is a growing need for microflow calibration. However, at such flow rates, the effects of liquid evaporation, air disturbance, and flow instability make accurate measurement of microflow a serious challenge. In this study, a passive piston calibration device is presented based on the interference method. The movement of the piston is entirely driven by the measured liquid, which displacement can be detected precisely by interference fringes to ensure the measurement accuracy. Additionally, the closed system reduces errors caused by liquid evaporation and air disturbance. In order to validate our proposed new device, microflows from 0.02 μl min −1 to 10 μl min −1 are tested. The experimental results demonstrate that the device can detect the flow variations with an expanded uncertainty of less than 1.5% ( k = 2). For example, when the microflow is 0.1 μl min −1 , the corresponding expanded uncertainty is 0.0011 μl min −1 ( k = 2). Moreover, the accuracy of the flow measurement and the uncertainty of the device are verified by conducting the interface tracking method as comparison. The results show that the innovative device developed in this study has the potential to be widely used in flow calibration at nl min −1 .

We exploit the optical lever principle to detect minute fluctuations of a liquid–air interface. Waves propagating on the interface deflect a specularly reflected laser beam, inducing angular deviations captured by a dual-element photodiode. We implement this principle in a compact setup that includes a temperature-controlled fluid sample. This allows us to detect deflection angle fluctuations across 5 orders of magnitude in frequency, from individual low-frequency surface eigenmodes to the thermal distribution of high-frequency capillary waves. In addition to demonstrating the method’s versatility and broad dynamical range, we highlight practical considerations in characterizing liquid interface dynamics, bridging established optical methods with their application to fluid and soft-matter systems.

Material properties of aqueous potassium acetate solutions for use in liquid desiccant air conditioning

Thermodynamic and economic analysis of an advanced liquid air energy storage system coupled with LNG cold energy, waste heat and solar energy

Techno-economic analysis of a novel liquid air energy storage integrated with thermochemical energy storage

A new application study of liquefied natural gas in assisting in the start-up of the liquid air energy storage system without sufficient cold storage energy

Integrated LNG cold energy-based system combining liquid air energy storage and air separation unit: A novel synergistic solution for supply-demand coordination and power grid peak-shaving

A multi-energy polygeneration liquid air energy storage system integrated with drying functions

Dynamic modelling and response characteristics of a solar-assisted liquid air energy storage system with poly-generation

Design and analysis of a cascade solid-packed bed cold storage system using liquid heat transfer fluids for liquid air energy storage

This study investigates the impact of a time-varying axial magnetic field on the dynamics of plasma discharges at the liquid–air interface using conductive sodium chloride solutions. Generating the magnetic field using a Helmholtz coil reveals that the Lorentz force significantly alters the dynamics of the jet, stretching the vertical plasma jet horizontally, immediately, and rapidly converting it into horizontal arcs. Consequently, the formation of atmospheric plasmoids is prevented. Spectroscopic measurements reveal pronounced spatial variations in plasma emission: strong Balmer series emissions are observed near the cathode, shifting to dominant sodium and hydroxyl radical emissions at greater distances. Furthermore, magnetic field-induced lateral plasma motion generates distinct liquid surface flow patterns in the vicinity of the cathode. This paper clarifies the mechanism by which plasmoid formation is suppressed and highlights the potential of magnetic field control in applications involving precise plasma–liquid interactions.

Techno-economic analysis of a novel liquid air energy storage system coupled with thermal power unit