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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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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