دورية أكاديمية

A Statistical-Based Approach to Load Model Parameter Identification

التفاصيل البيبلوغرافية
العنوان: A Statistical-Based Approach to Load Model Parameter Identification
المؤلفون: Aminjon Gulakhmadov, Alexander Tavlintsev, Aleksey Pankratov, Anton Suvorov, Anastasia Kovaleva, Ilya Lipnitskiy, Murodbek Safaraliev, Sergey Semenenko, Pavel Gubin, Stepan Dmitriev, Khusrav Rasulzoda
المصدر: IEEE Access, Vol 9, Pp 66915-66928 (2021)
بيانات النشر: IEEE, 2021.
سنة النشر: 2021
المجموعة: LCC:Electrical engineering. Electronics. Nuclear engineering
مصطلحات موضوعية: Load modeling, power system, power system study, static load model, ZIP model, Electrical engineering. Electronics. Nuclear engineering, TK1-9971
الوصف: 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.
نوع الوثيقة: article
وصف الملف: electronic resource
اللغة: English
تدمد: 2169-3536
Relation: https://ieeexplore.ieee.org/document/9419005/; https://doaj.org/toc/2169-3536
DOI: 10.1109/ACCESS.2021.3076690
URL الوصول: https://doaj.org/article/99071ed1506247ce965e6c3227afae35
رقم الأكسشن: edsdoj.99071ed1506247ce965e6c3227afae35
قاعدة البيانات: Directory of Open Access Journals
الوصف
تدمد:21693536
DOI:10.1109/ACCESS.2021.3076690