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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Veröffentlicht in:International journal of electrical power & energy systems Jg. 172; S. 111304
Hauptverfasser: Liu, Hong, Lu, Shaohan, Li, Junkai, Liang, Zipeng, Tong, Yishen, Li, Huiqiang, Chung, Chi-yung, Xue, Li
Format: Journal Article
Sprache:Englisch
Veröffentlicht: Elsevier Ltd 01.11.2025
Elsevier
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ISSN:0142-0615
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Abstract •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.
AbstractList •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.
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.
ArticleNumber 111304
Author Lu, Shaohan
Liang, Zipeng
Li, Junkai
Tong, Yishen
Xue, Li
Liu, Hong
Li, Huiqiang
Chung, Chi-yung
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  organization: Key Laboratory of Smart Grid of Ministry of Education, Tianjin University, Tianjin 300072, China
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  givenname: Junkai
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  email: lijunkai6666@163.com
  organization: Key Laboratory of Smart Grid of Ministry of Education, Tianjin University, Tianjin 300072, China
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  givenname: Zipeng
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  surname: Xue
  fullname: Xue, Li
  organization: The Henan Chenshuo Energy Technology Co., Ltd, Zhengzhou 450000, China
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Keywords Renewable output curtailment
PV hosting capacity
Lifecycle carbon contribution
Language English
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Snippet •A lifecycle carbon emission-oriented PV hosting capacity evaluation model is developed.•A solution method for stochastic-robust optimization is proposed by...
Renewable output curtailment-based hosting capacity improvement provides more carbon contribution by increasing grid-connected zero-carbon energy. However, it...
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SubjectTerms Lifecycle carbon contribution
PV hosting capacity
Renewable output curtailment
Title Piecewise affine policy-based stochastic-robust hosting capacity evaluation of rooftop photovoltaics considering lifecycle carbon contribution
URI https://dx.doi.org/10.1016/j.ijepes.2025.111304
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