Identifying the key system parameters of the organic Rankine cycle using the principal component analysis based on an experimental database

Yan, Dong; Yang, Fubin; Yang, Fufang; Zhang, Hongguang; Guo, Zhiyu; Li, Jian; Wu, Yuting

doi:10.1016/j.enconman.2021.114252

Cited by 19 publications

(4 citation statements)

References 32 publications

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“…The uncertainties of the power output and efficiency of the PM and generator and are calculated as [ 36 ]

Δ Y = \sqrt{\sum_{normali}^{normaln} {(\frac{\partial Y}{\partial X_{i}} Δ X_{i})}^{2}}

…”

Section: Resultsmentioning

confidence: 99%

“…The uncertainties of the power output and efficiency of the PM and generator and are calculated as [36] ΔY ¼ ffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi ffi X n i ∂Y ∂X i ΔX i a microscale CAES system. The PM acts as an expander and a compressor during forward and reverse rotations.…”

Section: Uncertainty Analysismentioning

confidence: 99%

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Experimental Research on the Forward and Reverse Rotation Characteristics of a Pneumatic Motor for a Microscale Compressed Air Energy Storage System

Zhang

Yang

et al. 2022

Energy Tech

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Microscale compressed air energy storage is not dependent on geographical environment, exhibits a flexible layout, and is especially suitable for distributed energy systems. Herein, a test bench of microscale compressed air energy storage is established. The effects of key parameters, such as regulated pressure, current, voltage, and rotating speed, on the output performance of a pneumatic motor (PM) and generator are examined. The power performance, economic performance, and energy efficiency of the PM in forward and reverse rotations are also investigated. The differences in the output performances of the PM and generator under the forward and reverse rotations of the PM are analyzed. Experimental results show that the PM's power performance, economy, and efficiency in forward rotation are greater than those in reverse rotation. The power output of the generator with the PM in forward rotation is greater than that in reverse rotation. The maximum values of the power output and efficiency and the minimum compressed air consumption rate of the PM are 650 W, 6.92%, and 0.165 g J−1, respectively. The maximum efficiency of the generator is 94.35%.

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“…The uncertainties of the power output and efficiency of the PM and generator and are calculated as [ 36 ]

Δ Y = \sqrt{\sum_{normali}^{normaln} {(\frac{\partial Y}{\partial X_{i}} Δ X_{i})}^{2}}

…”

Section: Resultsmentioning

confidence: 99%

Section: Uncertainty Analysismentioning

confidence: 99%

Experimental Research on the Forward and Reverse Rotation Characteristics of a Pneumatic Motor for a Microscale Compressed Air Energy Storage System

Zhang

Yang

et al. 2022

Energy Tech

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show abstract

“…TPR or Recall or Sensitivity = TP/(TP + FN) (7) FDR = FP/(FP + TP) (8) Accuracy = (TP + TN)/(TP + TN + FP + FN) (9) where TP denotes the number of pixels with both predicted and actual power lines; TN denotes the number of pixels with neither predicted nor actual power lines; FP denotes the number of pixels with predicted power lines and actual background; FN denotes the number of pixels with predicted background and actual power lines. Accuracy refers to the ratio of the number of correctly predicted samples to the total number of predicted samples and it does not consider whether the predicted samples are positive or negative.…”

Section: Evaluation Parametersmentioning

confidence: 99%

“…The accurate extraction of power lines is one of the core steps of UAV inspection [1,2] and, as the basis for distance monitoring [3][4][5], broken strand monitoring [6][7][8], ice cover monitoring [9][10][11], foreign object monitoring [12,13], and power line arc sag measurement [14][15][16] of hazardous operations, it is important to extract power lines accurately and quickly. Laser point cloud data have high accuracy and high-density 3D spatial information [17][18][19][20] and are used by some scholars for fine power line extraction; the literature [21] realizes single power line fine extraction based on the residual clustering method.…”

Section: Introductionmentioning

confidence: 99%

Automatic Extraction of Power Lines from Aerial Images of Unmanned Aerial Vehicles

Song

Qian

et al. 2022

Sensors

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Automatic power line extraction from aerial images of unmanned aerial vehicles is one of the key technologies of power line inspection. However, the faint power line targets and complex image backgrounds make the extraction of power lines a greater challenge. In this paper, a new power line extraction method is proposed, which has two innovative points. Innovation point one, based on the introduction of the Mask RCNN network algorithm, proposes a block extraction strategy to realize the preliminary extraction of power lines with the idea of “part first and then the whole”. This strategy globally reduces the anchor frame size, increases the proportion of power lines in the feature map, and reduces the accuracy degradation caused by the original negative anchor frames being misclassified as positive anchor frames. Innovation point two, the proposed connected domain group fitting algorithm solves the problem of broken and mis-extracted power lines even after the initial extraction and solves the problem of incomplete extraction of power lines by background texture interference. Through experiments on 60 images covering different complex image backgrounds, the performance of the proposed method far exceeds that of commonly used methods such as LSD, Yolact++, and Mask RCNN. DSCPL, TPR, precision, and accuracy are as high as 73.95, 81.75, 69.28, and 99.15, respectively, while FDR is only 30.72. The experimental results show that the proposed algorithm has good performance and can accomplish the task of power line extraction under complex image backgrounds. The algorithm in this paper solves the main problems of power line extraction and proves the feasibility of the algorithm in other scenarios. In the future, the dataset will be expanded to improve the performance of the algorithm in different scenarios.

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Comparative investigations on dynamic characteristics of basic ORC and cascaded LTES-ORC under transient heat sources

Wang

et al. 2022

Applied Thermal Engineering

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Identifying the key system parameters of the organic Rankine cycle using the principal component analysis based on an experimental database

Cited by 19 publications

References 32 publications

Experimental Research on the Forward and Reverse Rotation Characteristics of a Pneumatic Motor for a Microscale Compressed Air Energy Storage System

Experimental Research on the Forward and Reverse Rotation Characteristics of a Pneumatic Motor for a Microscale Compressed Air Energy Storage System

Automatic Extraction of Power Lines from Aerial Images of Unmanned Aerial Vehicles

Comparative investigations on dynamic characteristics of basic ORC and cascaded LTES-ORC under transient heat sources

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