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

Engineering Institute of Technology, Faculty of Electrical Engineering and Industrial Automation, Melbourne, VIC 3000, Australia
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Academic Editor: Gianfranco Chicco
Energies 2021, 14(8), 2293; https://doi.org/10.3390/en14082293
Received: 24 March 2021 / Revised: 14 April 2021 / Accepted: 16 April 2021 / Published: 19 April 2021
(This article belongs to the Special Issue Future Wind Power Plants: Challenges and Developments)
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/RPCC) are the most important parameters, which affect the PCC voltage (VPCC) stability. Hence, design engineers need to conduct the WPP siting and sizing assessment considering the SCR and X/RPCC 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 VPCC profile and maximum permissible wind power generation, using the SCR and X/RPCC 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. View Full-Text
Keywords: wind power plant; distribution network; X/R ratio; short-circuit capacity; decision tree wind power plant; distribution network; X/R ratio; short-circuit capacity; decision tree
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MDPI and ACS Style

Ghimire, S.; Alizadeh, S.M. Developing a Decision Tree Algorithm for Wind Power Plants Siting and Sizing in Distribution Networks. Energies 2021, 14, 2293. https://doi.org/10.3390/en14082293

AMA Style

Ghimire S, Alizadeh SM. Developing a Decision Tree Algorithm for Wind Power Plants Siting and Sizing in Distribution Networks. Energies. 2021; 14(8):2293. https://doi.org/10.3390/en14082293

Chicago/Turabian Style

Ghimire, Santosh; Alizadeh, Seyed M. 2021. "Developing a Decision Tree Algorithm for Wind Power Plants Siting and Sizing in Distribution Networks" Energies 14, no. 8: 2293. https://doi.org/10.3390/en14082293

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