کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
704282 1460879 2016 8 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Off-line tracking of series parameters in distribution systems using AMI data
ترجمه فارسی عنوان
ردیابی خارج از خط پارامترهای سری در سیستم های توزیع با استفاده از داده های AMI
کلمات کلیدی
تجزیه و تحلیل سیستم توزیع؛ برآورد پارامتر؛ برآورد حالت؛ تشخیص تغییر
موضوعات مرتبط
مهندسی و علوم پایه مهندسی انرژی مهندسی انرژی و فناوری های برق
چکیده انگلیسی


• Application of parameter estimation to power distribution systems (three-phase).
• Increased measurement redundancy by combining multiple measurement snapshots.
• Process is able to detect a 5% resistance change with 2% measurement noise and 10% error in other system parameters.

In the past, electric distribution systems have lacked measurement points, and equipment is often operated to its failure point, resulting in customer outages. The widespread deployment of sensors improves distribution level observability. This paper presents an off-line parameter tracking procedure that leverages the increased deployment of distribution level measurement devices to estimate changes in impedance parameters over time. Parameter tracking enables the discovery of non-diurnal and non-seasonal changes, which can be flagged for investigation. The presented method uses an unbalanced distribution-system state-estimator and a measurement-residual based parameter-estimation procedure. Measurement residuals from multiple measurement snapshots are combined to increase effective local redundancy and improve robustness to measurement noise. The input data used in the experiments consists of data from devices on the primary distribution system and from customer meters, via an AMI system. Results of simulations on the IEEE 13-Node Test Feeder with 307 measurements and 246 parameters are presented to illustrate the proposed approach applied to changes in series impedance parameters. The proposed approach can detect a 5% change in series resistance elements with 2% measurement error using less than 1 day of measurement snapshots for a single estimate.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Electric Power Systems Research - Volume 134, May 2016, Pages 205–212
نویسندگان
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