Experimental and modelling analysis of efficiency enhancement in a liquid piston gas compressor using metal plate inserts for compressed air energy storage application

Khaljani, M.; Vennard, Ashlene; Harrison, John; Surplus, David; Murphy, Adrian; Mahmoudi, Yasser

doi:10.1016/j.est.2021.103240

Cited by 14 publications

(2 citation statements)

References 31 publications

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“…Results indicated that the maximum round-trip efficiency could reach up to 63%. In the same year, his team [24] developed a liquid piston gas compressor prototype with aluminum parallel plates to increase compression efficiency. Experimental results indicated that when the plate inserts with a height of 0.2 m, 0.35 m, and 0.5 m, the compression efficiency could be increased by approximately 3%, 4%, and 8%, respectively.…”

Section: Introductionmentioning

confidence: 99%

Experimental Investigation on the Performance of Compressors for Small-Scale Compressed Air Energy Storage in Parallel Mode

Yang,

Xu,

Zhang

et al. 2023

Sustainability

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The Compressed Air Energy Storage (CAES) system is a promising energy storage technology that has the advantages of low investment cost, high safety, long life, and is clean and non-polluting. The compressor/expander is the core equipment of the CAES system, and its performance has a decisive impact on the overall system efficiency and economic performance. Based on the pneumatic motor, this study proposes and designs a test bench of the CAES system that integrates compression and expansion functions. The off-design operation condition represented by the pressure change in the air tank has an important influence on the efficiency and economy of the CAES system. The effect of key parameters such as air tank pressure, torque, and mass flow rate on the output and efficiency of the compressor is investigated. When the CAES system is operating in energy storage mode, the compressor must continuously deliver gas to the gas storage. The working pressure of the compressor increases with the pressure in the air tank, so the compressor used for energy storage must operate continuously over a wide range of working conditions. The parallel operation mode of the compressor is proposed to improve the working condition range of the compressor torque and current, and improve the isotropic efficiency. When the air receiver pressure is 2.6 bar and the rotational speed is 2850 r/min, the power consumption of the compressor reaches the maximum value of approximately 1233.1 W. This new parallel mode could provide a CAES unit a systematic solution.

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Section: Introductionmentioning

confidence: 99%

Experimental Investigation on the Performance of Compressors for Small-Scale Compressed Air Energy Storage in Parallel Mode

Yang,

Xu,

Zhang

et al. 2023

Sustainability

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show abstract

“…1 The energy of the compressor is generated from the efficient and reliable high-speed rotation of the blades. 2 With high pressure and strong centrifugal force, the blades tend to develop initial cracks, causing failure as the cracks propagate. 3,4 For the structural health monitoring of compressor blades, monitoring the onset of crack can effectively avoid crack propagation and improve the reliability of blades.…”

Section: Introductionmentioning

confidence: 99%

Two-level fusion of multi-sensor information for compressor blade crack detection based on self-attention mechanism

Song

Shen

et al. 2022

Structural Health Monitoring

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Nowadays, acoustic and vibration signals have been widely used to detect crack and its degree on compressor blades for non-destructive evaluation and structural health monitoring. Due to complex working conditions and interference of strong noise, single signal-based methods reach unsatisfactory accuracy. To improve the reliability and accuracy of crack detection, the two-level fusion method based on Mahalanobis distance (MD) and self-attention mechanism is proposed based on multi-acoustic, vibration, and acoustic emission information. First, the MD is calculated to measure the similarity between raw samples and group, which can fuse the same type of samples in data level. Then, the processed raw and data-level fusion samples are inputted to one-dimensional convolutional neural network, and the preliminary decisions are obtained. Finally, the decision-level fusion based on self-attention mechanism and credit assignment is proposed to modify and correct the preliminary decisions. The compressor experiments are implemented to test the proposed method under single and mixed working conditions with strong noise intensity. Further, the results illustrate that the proposed method can accurately detect crack for compressor blades. By comparing with other data fusion approaches, the advantage of the proposed method is validated under complex conditions.

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The accuracy of the mean value engine model affected little by the accuracy of compressor mass flow rate model for a marine diesel engine

Tang,

Xia,

Zhang

et al. 2023

J Mar Sci Technol

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Experimental and modelling analysis of efficiency enhancement in a liquid piston gas compressor using metal plate inserts for compressed air energy storage application

Cited by 14 publications

References 31 publications

Experimental Investigation on the Performance of Compressors for Small-Scale Compressed Air Energy Storage in Parallel Mode

Experimental Investigation on the Performance of Compressors for Small-Scale Compressed Air Energy Storage in Parallel Mode

Two-level fusion of multi-sensor information for compressor blade crack detection based on self-attention mechanism

The accuracy of the mean value engine model affected little by the accuracy of compressor mass flow rate model for a marine diesel engine

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