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Regular Paper | Open Access

Possibilistic Approach for Photovoltaic Hosting Capacity Evaluation on Distribution Networks Considering both Exogenous and Endogenous Uncertainties

Hongmin YaoWenping Qin( )Xiang JingZhilong ZhuKe WangXiaoqing Han
Key Laboratory of Power System Operation and Control, Taiyuan University of Technology, Taiyuan 030024, China
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Abstract

Large-scale access of distributed photovoltaic (PV) in distribution networks (DNs), if not properly evaluated, brings several operational problems. Uncertainties arising from both PV outputs and load demand significantly impact evaluation results. To address this issue, this paper proposes a possibilistic approach to evaluate PV hosting capacity (PVHC). First, possibility distribution is used to model load demand in order to reflect uncertainties associated with human factor, whereas the interval model is applied to deal with uncertainties of PV outputs. Second, a voltage deterioration index is proposed considering overvoltage risk of entire system on time scale. After that, possibilistic PVHC evaluation method based on this index is proposed. A 6-bus system is used to illustrate advantages of the proposed method, followed by a discussion of role of PVHC possibility distribution in actual decision-making of utilities. Moreover, sensitivity of simulation parameters is analyzed to reduce computational burden. Finally, the proposed method is tested on the IEEE 123-bus DN to validate adaptability to a larger system and to analyze impact of PVHC results against different acceptable values set by utilities.

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CSEE Journal of Power and Energy Systems
Pages 271-281

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Cite this article:
Yao H, Qin W, Jing X, et al. Possibilistic Approach for Photovoltaic Hosting Capacity Evaluation on Distribution Networks Considering both Exogenous and Endogenous Uncertainties. CSEE Journal of Power and Energy Systems, 2026, 12(1): 271-281. https://doi.org/10.17775/CSEEJPES.2022.01320

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Received: 02 March 2022
Revised: 17 May 2022
Accepted: 27 May 2022
Published: 28 December 2023
© 2022 CSEE.

This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).