Piecewise affine policy-based stochastic-robust hosting capacity evaluation of rooftop photovoltaics considering lifecycle carbon contribution

•A lifecycle carbon emission-oriented PV hosting capacity evaluation model is developed.•A solution method for stochastic-robust optimization is proposed by simplex approximation-based affine policy. Renewable output curtailment-based hosting capacity improvement provides more carbon contribution by...

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Bibliographic Details
Published in:	International journal of electrical power & energy systems Vol. 172; p. 111304
Main Authors:	Liu, Hong, Lu, Shaohan, Li, Junkai, Liang, Zipeng, Tong, Yishen, Li, Huiqiang, Chung, Chi-yung, Xue, Li
Format:	Journal Article
Language:	English
Published:	Elsevier Ltd 01.11.2025 Elsevier
Subjects:	Lifecycle carbon contribution PV hosting capacity Renewable output curtailment Renewable output curtailment PV hosting capacity Lifecycle carbon contribution
ISSN:	0142-0615
Online Access:	Get full text
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Summary:	•A lifecycle carbon emission-oriented PV hosting capacity evaluation model is developed.•A solution method for stochastic-robust optimization is proposed by simplex approximation-based affine policy. Renewable output curtailment-based hosting capacity improvement provides more carbon contribution by increasing grid-connected zero-carbon energy. However, it also leads to the growth in carbon emission of unit renewable output due to generation abandonment. To evaluate the maximum low-carbon benefits supported by distribution networks, this paper proposes a rooftop photovoltaics (PVs) hosting capacity optimization model considering lifecycle carbon contribution. Specifically, a two-stage stochastic-robust framework is utilized to depict uncertain external carbon intensity and renewable outputs. The product of multiple decision variables contained in this model brings strong nonlinear characteristics. Therefore, a systematic solution methodology is designed to transform nonlinear stochastic-robust model into mixed-integer second-order cone programming. The product of multiple decision variables in “min–max” operator are solved by leveraging dual transformation, simplex approximation-based piecewise affine policy and McCormick relaxation. Numerical results verify that lifecycle carbon contribution increases more than 20% by renewable output curtailment-based hosting capacity improvement.
ISSN:	0142-0615
DOI:	10.1016/j.ijepes.2025.111304