Detailed Information

Cited 13 time in webofscience Cited 19 time in scopus
Metadata Downloads

A Novel Framework to Determine the Impact of Time Varying Load Models on Wind DG Planning

Authors
Ahmed, AliKhan, Muhammad Faisal NadeemKhan, IrfanAlquhayz, HaniKhan, Muhammad AdnanKiani, Arooj Tariq
Issue Date
Jan-2021
Publisher
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
Keywords
Load modeling; Wind speed; Indexes; Planning; Resource management; Probabilistic logic; Reactive power; Distributed generation; impact indices; salp swarm algorithm; time varying voltage dependent loads
Citation
IEEE ACCESS, v.9, pp.11342 - 11357
Journal Title
IEEE ACCESS
Volume
9
Start Page
11342
End Page
11357
URI
https://scholarworks.bwise.kr/gachon/handle/2020.sw.gachon/81309
DOI
10.1109/ACCESS.2021.3050307
ISSN
2169-3536
Abstract
Distributed Generation (DG) based on Renewable Energy Sources (RES) are considered as an effective and economical technology for the advancement of an Electric Power System (EPS) to fulfill the load demand. Mostly, studies pertaining to DG planning are performed while considering constant load demand and DG generation. However, these considerations may provide misleading and inconsistent values for loss reduction, voltage profile, power quality, and other operational parameters. Therefore, this paper proposes a novel framework to determine the impact of different Time Varying Voltage Dependent (TVVD) load models on wind DG planning study. Firstly, wind DG optimal allocation is performed using Salp Swarm Algorithm (SSA) for different TVVD load models. Afterwards, impact of different TVVD load models on wind DG planning is investigated. Comparative evaluation of various impact indices, real and reactive power (losses and intakes), penetration level, and apparent power support provided due to integration of wind DG are discussed for various TVVD loads. The analysis of results indicates that TVVD loads have a significant impact on performance of distribution system and DG planning studies.
Files in This Item
There are no files associated with this item.
Appears in
Collections
ETC > 1. Journal Articles

qrcode

Items in ScholarWorks are protected by copyright, with all rights reserved, unless otherwise indicated.

Related Researcher

Researcher Khan, Muhammad Adnan photo

Khan, Muhammad Adnan
College of IT Convergence (Department of Software)
Read more

Altmetrics

Total Views & Downloads

BROWSE