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A Statistical-Based Approach to Load Model Parameter Identification

Authors: Aminjon Gulakhmadov; Alexander Tavlintsev; Aleksey Pankratov; Anton Suvorov; Anastasia Kovaleva; Ilya Lipnitskiy; Murodbek Safaraliev; +4 Authors

A Statistical-Based Approach to Load Model Parameter Identification

Abstract

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.

Country
Russian Federation
Keywords

static load model, PARAMETER ESTIMATION, STATISTICAL APPROACH, STATIC LOAD MODEL, EQUIVALENT LOAD MODEL, ELECTRIC LOADS, ZIP model, DATA HANDLING, POWER SYSTEM STUDY, Load modeling, ZIP MODEL, FULL-SCALE EXPERIMENT, SCADA SYSTEMS, PARAMETER ESTIMATE, STATISTICS, TK1-9971, LOAD MODELING, STATISTICAL PROCESSING, power system, ELECTRICAL PARAMETER, POWER SYSTEM, SCADA MEASUREMENTS, PRACTICAL IMPORTANCE, Electrical engineering. Electronics. Nuclear engineering, power system study

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citations
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
1
Average
Average
Average
Green
gold