Fault line selection method of DC distribution network based on transient current fault component

Gao, Shuping; Duan, Bicong; Song, Guobing; Shao, Mingxing

doi:10.1109/ifeea51475.2020.00097

Cited by 3 publications

(3 citation statements)

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“…(1) Linearity test and normality test In Pearson correlation coefficient, whether the data is linear, and outliers have a big impact on the results, and the data needs to satisfy the normal distribution. Before calculating the coefficients, this paper carries out the linearity test and normality test by making scatter plot and Q-Q plot respectively [1].…”

Section: Relevance Analysis 21 Correlation Analysismentioning

confidence: 99%

Research on Pricing and Replenishment Strategies of Supermarket Vegetables Based on LSTM Neural Network and Goal Planning

Zhou

2023

JCEIM

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This paper focuses on the daily replenishment volume and pricing of vegetable commodities, especially the impact of freshness on market selling price. Through Pearson correlation analysis, this study first explored the correlation between different vegetable categories and their single products and evaluated the sales correlation between each category and the single products of the same category. Secondly, this paper considers the cost-plus pricing method to analyze the relationship between the total sales volume of vegetable products and the pricing. The LSTM neural network model is used to forecast the sales volume and wholesale price of vegetable commodities, with special attention to the forecast data from July 1 to 7. Finally, this paper establishes a goal planning model with the goal of maximizing supermarket returns. Considering the total quantity of replenishment, sales volume and cost pricing as constraint conditions, the depth-first search algorithm is adopted to solve the problem, and the daily replenishment volume and pricing strategy for vegetable products in the next week are provided.

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Section: Relevance Analysis 21 Correlation Analysismentioning

confidence: 99%

Research on Pricing and Replenishment Strategies of Supermarket Vegetables Based on LSTM Neural Network and Goal Planning

Zhou

2023

JCEIM

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“…However, the traveling wave method has the problems of limiting the transition resistance and the amplitude of the traveling wave head, which makes it difficult to accurately calibrate the starting point of the wave head [5][6] . The fault analysis method is vulnerable to the influence of line parameters and frequency variation characteristics, and the inconsistency of transient transmission characteristics of data acquisition and transmission equipment will also affect the accuracy and reliability of ranging [7][8][9] .…”

Section: Introductionmentioning

confidence: 99%

Fault location of flexible DC system based on BP neural network

Liu

Sihua

2023

Eighth International Symposium on Advances in Electrical, Electronics, and Computer Engineering (ISAEECE 2023)

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As a bridge of the transmission system, flexible DC transmission line plays an important role. If a fault occurs, it will bring serious consequences to the entire transmission system. It is very important to study the fault location of the flexible DC transmission line. According to the system structure of flexible DC transmission line, the mathematical model, operation mode and control strategy of MMC are analyzed. According to the characteristics of transmission line with bipolar short circuit fault, a fault location method based on BP neural network is proposed. Combined with PSCAD/EMTDC, a twoterminal flexible DC transmission system is built, and the fault data of the flexible DC transmission line is obtained by simulation. After preprocessing the data, a sample set is constructed. The neural network analysis uses the two-terminal fault location method, and finally a high-precision fault location model is obtained, which verifies the accuracy and effectiveness of the location method proposed in this paper.

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“…The passive line-selection method mainly uses signal characteristics for line selection, including the steady-state component method, transient component method, traveling wave component method, etc. [5]. The active line-selection method mainly uses a sudden change signal or injection signal to achieve fault-line selection, including the small disturbance method, signal injection method, residual flow increment method, etc.…”

Section: Introductionmentioning

confidence: 99%

Distribution Network Fault-Line Selection Method Based on MICEEMDAN–Recurrence Plot–Yolov5

Hou

Guo

2022

Processes

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Distribution system fault signals contain severe noise components. In order to solve the problem of distribution network fault-line selection, a fault-line selection method based on modifying the Improved Complete Ensemble Empirical Mode Decomposition Adaptive Noise (MICEEMDAN) algorithm, Recurrence Plot, and Yolov5 network is proposed. First, ICEEMDAN is optimized using multi-scale weighted permutation entropy (MWPE). MICEEMDAN can decompose an electrical signal into a series of intrinsic mode functions (IMFs). Recurrence Plot transformation of all IMFs, obtained from decomposition and stitching from top to bottom, realizes the conversion of 1D time series to 2D images. Then, the recurrence maps obtained from all lines in the distribution network are stitched to obtain the distribution network recurrence map, realizing the mining of the fault-signal features of the whole distribution network. Finally, the Yolov5 network is used to mine the fault features of the recurrence map of the distribution network autonomously to realize the fault-line selection. The experiments show that the method has a good noise immunity and 99.98% fault-selection accuracy, which can effectively complete the distribution network fault selection.

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Fault line selection method of DC distribution network based on transient current fault component

Cited by 3 publications

References 0 publications

Research on Pricing and Replenishment Strategies of Supermarket Vegetables Based on LSTM Neural Network and Goal Planning

Research on Pricing and Replenishment Strategies of Supermarket Vegetables Based on LSTM Neural Network and Goal Planning

Fault location of flexible DC system based on BP neural network

Distribution Network Fault-Line Selection Method Based on MICEEMDAN–Recurrence Plot–Yolov5

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