Application of Expectation Maximization Algorithm for Measurement-based Power System Load Modeling; Control and Communications (SIBCON-2019)
| Parent link: | Control and Communications (SIBCON-2019).— 2019.— [18739750, 5 p.] |
|---|---|
| مؤلف مشترك: | |
| مؤلفون آخرون: | , , , , , |
| الملخص: | Title screen This paper describes a practical application of the Expectation Maximization algorithm for computing the static load model of large electricity consumers. Such a model is necessary for effective and reliable operational control of electric power systems. The possibility of estimating basic states of electrical load using arrays of measured voltage and power data is shown. The criteria for selecting the most appropriate clusters are formulated and a step by step linear load model parameter estimation method is proposed. A practical method application is illustrated by using measurements of voltage and real power obtained at a large industrial facility. As a result, a load model with two basic states and corresponding linear models is obtained. Режим доступа: по договору с организацией-держателем ресурса |
| اللغة: | الإنجليزية |
| منشور في: |
2019
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| الموضوعات: | |
| الوصول للمادة أونلاين: | https://doi.org/10.1109/SIBCON.2019.8729610 |
| التنسيق: | الكتروني فصل الكتاب |
| KOHA link: | https://koha.lib.tpu.ru/cgi-bin/koha/opac-detail.pl?biblionumber=661049 |
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| 200 | 1 | |a Application of Expectation Maximization Algorithm for Measurement-based Power System Load Modeling |f A. V. Pankratov [et al.] | |
| 203 | |a Text |c electronic | ||
| 300 | |a Title screen | ||
| 320 | |a [References: 23 tit.] | ||
| 330 | |a This paper describes a practical application of the Expectation Maximization algorithm for computing the static load model of large electricity consumers. Such a model is necessary for effective and reliable operational control of electric power systems. The possibility of estimating basic states of electrical load using arrays of measured voltage and power data is shown. The criteria for selecting the most appropriate clusters are formulated and a step by step linear load model parameter estimation method is proposed. A practical method application is illustrated by using measurements of voltage and real power obtained at a large industrial facility. As a result, a load model with two basic states and corresponding linear models is obtained. | ||
| 333 | |a Режим доступа: по договору с организацией-держателем ресурса | ||
| 463 | |t Control and Communications (SIBCON-2019) |o proceedings of International Siberian Conference, April 18-20, 2019, Russia, Tomsk |v [18739750, 5 p.] |d 2019 | ||
| 610 | 1 | |a электронный ресурс | |
| 610 | 1 | |a труды учёных ТПУ | |
| 610 | 1 | |a cluster analysis | |
| 610 | 1 | |a mathematical statistics | |
| 610 | 1 | |a EM algorithm | |
| 610 | 1 | |a power system | |
| 610 | 1 | |a load modeling | |
| 610 | 1 | |a parameter estimation | |
| 610 | 1 | |a measurement-based approac | |
| 610 | 1 | |a кластерный анализ | |
| 610 | 1 | |a математическая статистика | |
| 610 | 1 | |a алгоритмы | |
| 610 | 1 | |a система питания | |
| 610 | 1 | |a моделирование | |
| 610 | 1 | |a нагрузки | |
| 701 | 1 | |a Pankratov |b A. V. |c specialist in the field of electric power engineering |c Associate Professor of Tomsk Polytechnic University, Candidate of technical sciences |f 1983- |g Aleksey Vladimirovich |3 (RuTPU)RU\TPU\pers\33022 | |
| 701 | 1 | |a Batseva |b N. L. |c Specialist in the field of electric power engineering |c Associate Professor of Tomsk Polytechnic University, Candidate of technical sciences |f 1968- |g Natalya Lenmirovna |3 (RuTPU)RU\TPU\pers\31306 |9 15484 | |
| 701 | 1 | |a Polyakova |b E. S. |g Ekaterina Sergeevna | |
| 701 | 1 | |a Tavlintsev |b A. S. |g Alexander Sergeevich | |
| 701 | 1 | |a Lapatin |b I. L. |g Ivan | |
| 701 | 1 | |a Lipnitsky |b I. Yu. |g Iljya | |
| 712 | 0 | 2 | |a Национальный исследовательский Томский политехнический университет |b Инженерная школа энергетики |b Отделение электроэнергетики и электротехники (ОЭЭ) |3 (RuTPU)RU\TPU\col\23505 |
| 801 | 2 | |a RU |b 63413507 |c 20191119 |g RCR | |
| 856 | 4 | 0 | |u https://doi.org/10.1109/SIBCON.2019.8729610 |
| 942 | |c CF | ||