Pearson Correlation in Determination of Quality of Current Transformers

Burgund, Davorin; Nikolovski, Srete; Galić, Dario; Maravić, Nedeljko

doi:10.3390/s23052704

Cited by 8 publications

(3 citation statements)

References 2 publications

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“…The Pearson correlation method [59,60] was used to analyze the simulation effect, which indicates a fitting degree between the simulated and measured dew values or the accuracy of the model simulation. OriginPro 2023 (OriginLab Corporation, Northampton, MA, USA) was used for data analysis and mapping.…”

Section: Discussionmentioning

confidence: 99%

Characteristics and Estimation of Dew in the Loess Hilly Region of Northern Shaanxi Province, China

Jia,

Chang,

Liu

et al. 2024

Sustainability

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As a non-precipitation water source, dew is important for plant and animal survival and crop production in arid and water-scarce areas. This study assessed the amount of dew in a dry zone in a long-term (2016 to 2022) field observation experiment at the Ansai Experimental Station, a typical loess hilly area in China. Dew primarily occurred in summer and autumn, with a frequency of >50%. The average annual dew amount was 29.20 mm, with an average annual rainfall of 641.8 mm. The average annual dew-to-rain ratio was 4.58%, and the average annual number of dew days was 143.6 d/a. The surface soil moisture content increased by approximately 1.02% with increasing dew amounts. The change in the soil moisture at a 5 cm depth was 0.14% on average and lagged substantially by 1 h. Using the Beysens model, the annual estimated and measured dew amounts in 2022 were 25.27 and 29.84 mm, respectively, and the annual normalized root mean square deviation (NRMSD) was 0.17. Thus, the Beysens model evaluated the dew amount in the study area well at the monthly and annual scales. The quantification of dew resources can provide support for the development, utilization, and management of limited water resources in arid areas, promoting more accurate decision-making for the sustainable development of water resources in the future.

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Section: Discussionmentioning

confidence: 99%

Characteristics and Estimation of Dew in the Loess Hilly Region of Northern Shaanxi Province, China

Jia,

Chang,

Liu

et al. 2024

Sustainability

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“…Pearson's method, which has a wide range of applications, was used to identify potential linear relationships. In [37], the authors applied it to demonstrate the correlation between the accuracy of current transformers (CT) and changes in temperature and frequency. In [38], Pearson's method was used in the context of fuzzy picture sets to solve problems with multiple attribute decision making (MADM).…”

Section: Methods Of Analysing Data Of Electricity Demand Profilesmentioning

confidence: 99%

An Analysis of Energy Consumption in Railway Signal Boxes

Kampik,

Bodzek,

Piaskowy

et al. 2023

Energies

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This study assessed hourly electricity consumption profiles in railway signal boxes located in Poland. The analyses carried out consisted of assessing the correlation among the hourly demand profile, weather indicators, and calendar indicators, e.g., temperature, cloud cover, day of the week, and month. The analysis allowed us to assess which indicator impacts the energy consumption profile and would be useful when forecasting energy demand. In total, 15 railway signal boxes were selected for analysis and grouped according to three characteristic repeatability profiles. On this basis, six of the signal boxes and one that did not fit into any of the groups were selected for further analysis. Four correlation research methods were selected for analysis: Pearson’s method, Spearman’s method, scatter plots, and distance covariance. The possibility of forecasting electricity consumption based on previously aggregated profiles and determining correlations with indicators was presented. The given indicators vary depending on the facility. Analyses showed different dependencies of the electricity demand profile. The ambient temperature and time of day have the greatest impact on the profile. Regarding the correlation with temperature, the results of the Pearson’s and Spearman’s coefficients ranged from approximately −0.4 to more than −0.8. The highest correlation coefficients were obtained when comparing the demand profile with the previous day. In this case, the Pearson’s and Spearman’s coefficients for all analysed objects range from approximately 0.7 to over 0.9.

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“…To verify the effectiveness of the scenario generation model based on Time-GAN, this paper uses t-SNE to evaluate the data distribution features, the autocorrelation coefficient method (Chen et al, 2018) to evaluate time-series correlation, and the Pearson method (Burgund et al, 2023) to evaluate spatial correlation.…”

Section: Scenario Generation Quality Assessmentmentioning

confidence: 99%

Power system data-driven dispatch using improved scenario generation considering time-series correlations

Li,

Huang,

Liang

et al. 2023

Front. Energy Res.

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Reinforcement learning (RL) is recently studied for realizing fast and adaptive power system dispatch under the increasing penetration of renewable energy. RL has the limitation of relying on samples for agent training, and the application in power systems often faces the difficulty of insufficient scenario samples. So, scenario generation is of great importance for the application of RL. However, most of the existing scenario generation methods cannot handle time-series correlation, especially the correlation over long time scales, when generating the scenario. To address this issue, this paper proposes an RL-based dispatch method which can generate power system operational scenarios with time-series correlation for the agent’s training. First, a time-generative adversarial network (GAN)-based scenario generation model is constructed, which generates system operational scenarios with long- and short-time scale time-series correlations. Next, the “N-1” security is ensured by simulating “N-1” branch contingencies in the agent’s training. Finally, the model is trained in parallel in an actual power system environment, and its effectiveness is verified by comparisons against benchmark methods.

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Pearson Correlation in Determination of Quality of Current Transformers

Cited by 8 publications

References 2 publications

Characteristics and Estimation of Dew in the Loess Hilly Region of Northern Shaanxi Province, China

Characteristics and Estimation of Dew in the Loess Hilly Region of Northern Shaanxi Province, China

An Analysis of Energy Consumption in Railway Signal Boxes

Power system data-driven dispatch using improved scenario generation considering time-series correlations

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