Developing a Decision Tree Algorithm for Wind Power Plants Siting and Sizing in Distribution Networks

The interconnection of wind power plants (WPPs) with distribution networks has posed many challenges concerned with voltage stability at the point of common coupling (PCC). In a distribution network connected WPP, the short-circuit ratio (SCR) and impedance angle ratio seen at PCC (X/R<sub>PCC...

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Main Authors: Santosh Ghimire, Seyed Morteza Alizadeh
Format: Article
Language:English
Published: MDPI AG 2021-04-01
Series:Energies
Subjects:
Online Access:https://www.mdpi.com/1996-1073/14/8/2293
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spelling doaj-46daa1f0a4c34716aee45952f40ebd242021-04-19T23:03:14ZengMDPI AGEnergies1996-10732021-04-01142293229310.3390/en14082293Developing a Decision Tree Algorithm for Wind Power Plants Siting and Sizing in Distribution NetworksSantosh Ghimire0Seyed Morteza Alizadeh1Engineering Institute of Technology, Faculty of Electrical Engineering and Industrial Automation, Melbourne, VIC 3000, AustraliaEngineering Institute of Technology, Faculty of Electrical Engineering and Industrial Automation, Melbourne, VIC 3000, AustraliaThe interconnection of wind power plants (WPPs) with distribution networks has posed many challenges concerned with voltage stability at the point of common coupling (PCC). In a distribution network connected WPP, the short-circuit ratio (SCR) and impedance angle ratio seen at PCC (X/R<sub>PCC</sub>) are the most important parameters, which affect the PCC voltage (V<sub>PCC</sub>) stability. Hence, design engineers need to conduct the WPP siting and sizing assessment considering the SCR and X/R<sub>PCC</sub> seen at each potential PCC site to ensure that the voltage stability requirements defined by grid codes are provided. In various literature works, optimal siting and sizing of distributed generation in distribution networks (DG) has been carried out using analytical, numerical, and heuristics approaches. The majority of these methods require performing computational tasks or simulate the whole distribution network, which is complex and time-consuming. In addition, other works proposed to simplify the WPP siting and sizing have limited accuracy. To address the aforementioned issues, in this paper, a decision tree algorithm-based model was developed for WPP siting and sizing in distribution networks. The proposed model eliminates the need to simulate the whole system and provides a higher accuracy compared to the similar previous works. For this purpose, the model accurately predicts key voltage stability criteria at a given interconnection point, including V<sub>PCC</sub> profile and maximum permissible wind power generation, using the SCR and X/R<sub>PCC</sub> values seen at that point. The results confirmed the proposed model provides a noticeable high accuracy in predicting the voltage stability criteria under various validation scenarios considered.https://www.mdpi.com/1996-1073/14/8/2293wind power plantdistribution networkX/R ratioshort-circuit capacitydecision tree
collection DOAJ
language English
format Article
sources DOAJ
author Santosh Ghimire
Seyed Morteza Alizadeh
spellingShingle Santosh Ghimire
Seyed Morteza Alizadeh
Developing a Decision Tree Algorithm for Wind Power Plants Siting and Sizing in Distribution Networks
Energies
wind power plant
distribution network
X/R ratio
short-circuit capacity
decision tree
author_facet Santosh Ghimire
Seyed Morteza Alizadeh
author_sort Santosh Ghimire
title Developing a Decision Tree Algorithm for Wind Power Plants Siting and Sizing in Distribution Networks
title_short Developing a Decision Tree Algorithm for Wind Power Plants Siting and Sizing in Distribution Networks
title_full Developing a Decision Tree Algorithm for Wind Power Plants Siting and Sizing in Distribution Networks
title_fullStr Developing a Decision Tree Algorithm for Wind Power Plants Siting and Sizing in Distribution Networks
title_full_unstemmed Developing a Decision Tree Algorithm for Wind Power Plants Siting and Sizing in Distribution Networks
title_sort developing a decision tree algorithm for wind power plants siting and sizing in distribution networks
publisher MDPI AG
series Energies
issn 1996-1073
publishDate 2021-04-01
description The interconnection of wind power plants (WPPs) with distribution networks has posed many challenges concerned with voltage stability at the point of common coupling (PCC). In a distribution network connected WPP, the short-circuit ratio (SCR) and impedance angle ratio seen at PCC (X/R<sub>PCC</sub>) are the most important parameters, which affect the PCC voltage (V<sub>PCC</sub>) stability. Hence, design engineers need to conduct the WPP siting and sizing assessment considering the SCR and X/R<sub>PCC</sub> seen at each potential PCC site to ensure that the voltage stability requirements defined by grid codes are provided. In various literature works, optimal siting and sizing of distributed generation in distribution networks (DG) has been carried out using analytical, numerical, and heuristics approaches. The majority of these methods require performing computational tasks or simulate the whole distribution network, which is complex and time-consuming. In addition, other works proposed to simplify the WPP siting and sizing have limited accuracy. To address the aforementioned issues, in this paper, a decision tree algorithm-based model was developed for WPP siting and sizing in distribution networks. The proposed model eliminates the need to simulate the whole system and provides a higher accuracy compared to the similar previous works. For this purpose, the model accurately predicts key voltage stability criteria at a given interconnection point, including V<sub>PCC</sub> profile and maximum permissible wind power generation, using the SCR and X/R<sub>PCC</sub> values seen at that point. The results confirmed the proposed model provides a noticeable high accuracy in predicting the voltage stability criteria under various validation scenarios considered.
topic wind power plant
distribution network
X/R ratio
short-circuit capacity
decision tree
url https://www.mdpi.com/1996-1073/14/8/2293
work_keys_str_mv AT santoshghimire developingadecisiontreealgorithmforwindpowerplantssitingandsizingindistributionnetworks
AT seyedmortezaalizadeh developingadecisiontreealgorithmforwindpowerplantssitingandsizingindistributionnetworks
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