Search for the Single-type Load Schedules of the Power Facility

Tavlintsev, Alexander; Suvorov, A. A.; Gusev, Sergey; Staymova, E.D.; Zicmane, Inga; Bērziņa, Kristīna

doi:10.1109/rtucon.2018.8659825

Cited by 3 publications

(3 citation statements)

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“…The statistical approach is based on the analysis of measurements obtained by passive observation of the object of study [7], [22], [23]. One of the difficulties is clustering of measurements related to different load compositions in use.…”

Section: B Statistical Equilibrium Load Node Conditionsmentioning

confidence: 99%

“…The algorithm of static load model identification using continuous field measurements of voltage and active and reactive power is based on the ideas outlined in [7], [23]. The proposed algorithm consists of three steps: data collection and pre-processing, measurement clustering into statistical equilibrium load conditions, and load model identification.…”

Section: Proposed Algorithm Of Static Load Model Identification Using the Statistical-based Approachmentioning

confidence: 99%

“…The article describes the statistical method, used for processing current operating mode parameters of collected data from power system to obtain estimates of load model parameters. The method is based on the ideas presented in the works [7], [22], [23]. A fragment of Unified Energy System of Russia with a predominant share of oil industry (about 90 %) was selected for testing.…”

Section: Introductionmentioning

confidence: 99%

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A Statistical-Based Approach to Load Model Parameter Identification

Gulakhmadov

Tavlintsev

Pankratov³

et al. 2021

IEEE Access

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In the last few years, a great number of methods for identifying the load model parameters have been proposed. This article discusses the use of statistical approach to estimate the substation equivalent load model parameters for supplying to oil-producing industrial region. The disadvantages of existing statistical approach are the low accuracy obtained for the parameter estimates, especially when using samples size is small. To eliminate this deficiency, the current measurement data archive from SCADA system of electrical parameters for 15 months was collected. For the purpose of verifying the obtained results of statistical processing of SCADA data, a full-scale experiment was carried out in relation to the studied substation. The article describes the statistical method used to process the current SCADA measurement data, the results of archived statistical processing and experimental SCADA data. The electrical load models' parameters received from the experimental studies results are of practical importance.

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Section: B Statistical Equilibrium Load Node Conditionsmentioning

confidence: 99%

Section: Proposed Algorithm Of Static Load Model Identification Using the Statistical-based Approachmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

A Statistical-Based Approach to Load Model Parameter Identification

Gulakhmadov

Tavlintsev

Pankratov³

et al. 2021

IEEE Access

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Development of a cluster analysis method for solving the problem of identifying static voltage load characteristics

Kondrashov

Popov

Bukharov³

et al. 2020

J. Phys.: Conf. Ser.

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Identification of static voltage load characteristics is not a trivial task. It is extremely difficult to develop a single methodology that will allow achieving the required accuracy results for any input data. The authors made an attempt to solve the problem, developed a method based on the use of methods for processing large data sets – BigData. One of the most important stages of this method is the stage of cluster analysis. The problem of choosing a method of cluster analysis also has nuances: it is necessary to maintain a balance between time and accuracy of calculations, while performing calculations with sufficient accuracy on various data. A number of domestic and foreign authors have investigated this issue, but the proposed options cannot be used in the developed methodology. The purpose of this research is to develop a cluster analysis method that will satisfy the above requirements. The author’s method is based on the k-means method. The main feature of the author’s method is the mechanism of initial generation of cluster centroids, which allows to exclude the influence of random generation of two-dimensional coordinates imperfection and to achieve uniform generation of initial clusters centers. The developed method was tested on a model problem with all known solutions, which can be easily verified analytically. Also the method was tested on actual industrial load data. The results obtained the requirements of accuracy and calculation speed and allow us to conclude that the developed method of cluster analysis can be used in the task of identifying static voltage load characteristics.

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