Distributed PV Bearing Capacity Assessment Method Based on Source–Load Coupling Scenarios

To address the insufficient consideration of system static voltage stability and PV–load coupling in distributed photovoltaic (PV) hosting capacity assessment, this study first investigates the impact of distributed PV integration on power system transient voltage stability based on a typical power supply system. Building on this analysis, we propose a Static Grid Stability Margin (SGSM) index. Subsequently, leveraging historical PV and load data, the copula function is introduced to establish a joint distribution function characterizing their correlation. Massive evaluation scenarios are generated through sampling, with robust clustering methods employed to form representative evaluation scenarios. Finally, a distributed PV bearing capacity assessment model is established with the objectives of maximizing PV bearing capacity, optimizing economic efficiency, and enhancing static voltage stability. Through simulation verification, the power system has a higher capacity for distributed PV when distributed PV is integrated into nodes with weak static voltage stability and a decentralized integration scheme is adopted.

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Publication Details

Journal
Energies
Published
2025-10-20
DOI
https://doi.org/10.3390/en18205520
Primary Topic
Islanding Detection in Power Systems
Type
article
Field-Weighted Citation Impact
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article

Distributed PV Bearing Capacity Assessment Method Based on Source–Load Coupling Scenarios

Yongcheng Liu, Yalong Li, Yalu Sun, Zhou Wang et al.
Energies
Islanding Detection in Power Systems
article

Distributed PV Bearing Capacity Assessment Method Based on Source–Load Coupling Scenarios

Yongcheng Liu, Yalong Li, Yalu Sun, Zhou Wang, Yi Jiang
article en

Abstract

To address the insufficient consideration of system static voltage stability and PV–load coupling in distributed photovoltaic (PV) hosting capacity assessment, this study first investigates the impact of distributed PV integration on power system transient voltage stability based on a typical power supply system. Building on this analysis, we propose a Static Grid Stability Margin (SGSM) index. Subsequently, leveraging historical PV and load data, the copula function is introduced to establish a joint distribution function characterizing their correlation. Massive evaluation scenarios are generated through sampling, with robust clustering methods employed to form representative evaluation scenarios. Finally, a distributed PV bearing capacity assessment model is established with the objectives of maximizing PV bearing capacity, optimizing economic efficiency, and enhancing static voltage stability. Through simulation verification, the power system has a higher capacity for distributed PV when distributed PV is integrated into nodes with weak static voltage stability and a decentralized integration scheme is adopted.

EnergiesVol. 18(20)
China University of Mining and Technology (CN), Economic Research Institute (BG)
Openalex Percentile: Top 70%
Islanding Detection in Power Systems
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