Statistical quantification of voltage violations in distribution networks penetrated by small wind turbines and battery electric vehicles

Chao Long; Mohamed Emad Farrag (Emad); Chengke Zhou; Donald Hepburn

doi:10.1109/TPWRS.2013.2252472

Statistical quantification of voltage violations in distribution networks penetrated by small wind turbines and battery electric vehicles

Chao Long, Mohamed Emad Farrag (Emad), Chengke Zhou, Donald Hepburn

Research output: Contribution to journal › Article › peer-review

Abstract

Voltage violation tends to be one of the dominant constraints or critical factors that limit the penetration of small wind turbines (SWTs) and battery electric vehicles (BEVs) in distribution networks. To quantify the voltage violation, a statistical time series based approach is developed in this paper. The daily time varying characteristics of electric loads, wind speeds and BEV charging loads have been taken into consideration in a statistical manner. The method has been compared with the conventional time series approach. It is proven that the proposed methodology, whilst providing a global picture on voltage violations, can potentially be used for fast evaluation of the probability of a voltage violation occurring in a network.

Original language	English
Pages (from-to)	2403-2411
Number of pages	9
Journal	IEEE Transactions on Power Systems
Volume	28
Issue number	3
Early online date	30 Apr 2013
DOIs	https://doi.org/10.1109/TPWRS.2013.2252472
Publication status	Published - Aug 2013

Keywords

voltage violation
probability distribution
time series analysis
small wind turbines
battery electric vehicles
BEV

Documents and Links

10.1109/TPWRS.2013.2252472

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title = "Statistical quantification of voltage violations in distribution networks penetrated by small wind turbines and battery electric vehicles",

abstract = "Voltage violation tends to be one of the dominant constraints or critical factors that limit the penetration of small wind turbines (SWTs) and battery electric vehicles (BEVs) in distribution networks. To quantify the voltage violation, a statistical time series based approach is developed in this paper. The daily time varying characteristics of electric loads, wind speeds and BEV charging loads have been taken into consideration in a statistical manner. The method has been compared with the conventional time series approach. It is proven that the proposed methodology, whilst providing a global picture on voltage violations, can potentially be used for fast evaluation of the probability of a voltage violation occurring in a network. ",

keywords = "voltage violation, probability distribution , time series analysis , small wind turbines, battery electric vehicles , BEV",

author = "Chao Long and {Farrag (Emad)}, {Mohamed Emad} and Chengke Zhou and Donald Hepburn",

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AU - Long, Chao

AU - Farrag (Emad), Mohamed Emad

AU - Zhou, Chengke

AU - Hepburn, Donald

PY - 2013/8

Y1 - 2013/8

N2 - Voltage violation tends to be one of the dominant constraints or critical factors that limit the penetration of small wind turbines (SWTs) and battery electric vehicles (BEVs) in distribution networks. To quantify the voltage violation, a statistical time series based approach is developed in this paper. The daily time varying characteristics of electric loads, wind speeds and BEV charging loads have been taken into consideration in a statistical manner. The method has been compared with the conventional time series approach. It is proven that the proposed methodology, whilst providing a global picture on voltage violations, can potentially be used for fast evaluation of the probability of a voltage violation occurring in a network.

AB - Voltage violation tends to be one of the dominant constraints or critical factors that limit the penetration of small wind turbines (SWTs) and battery electric vehicles (BEVs) in distribution networks. To quantify the voltage violation, a statistical time series based approach is developed in this paper. The daily time varying characteristics of electric loads, wind speeds and BEV charging loads have been taken into consideration in a statistical manner. The method has been compared with the conventional time series approach. It is proven that the proposed methodology, whilst providing a global picture on voltage violations, can potentially be used for fast evaluation of the probability of a voltage violation occurring in a network.

KW - voltage violation

KW - probability distribution

KW - time series analysis

KW - small wind turbines

KW - battery electric vehicles

KW - BEV

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DO - 10.1109/TPWRS.2013.2252472

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JO - IEEE Transactions on Power Systems

JF - IEEE Transactions on Power Systems

SN - 0885-8950

IS - 3

ER -