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Operation Mode Identification for High Renewable Energy Penetration Power Systems Based on Planning–Operation Coupling and SHAP Interpretability.

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Title: Operation Mode Identification for High Renewable Energy Penetration Power Systems Based on Planning–Operation Coupling and SHAP Interpretability.
Authors: Yang, Haotian1 (AUTHOR), Zhu, Shiyu2 (AUTHOR), Fu, Mengyu3 (AUTHOR), Wang, Peng3 (AUTHOR) wangpeng2020@mail.tsinghua.edu.cn, Xiong, Yijin1 (AUTHOR), Wang, Han4 (AUTHOR), Meraj, Sheikh Tanzim (AUTHOR) s.meraj@deakin.edu.au
Source: International Transactions on Electrical Energy Systems. 6/11/2026, Vol. 2026, p1-16. 16p.
Subject Terms: *Renewable energy sources, *Shapley Additive Explanations, *Electric power system management, *Cluster analysis (Statistics), *Electric power systems, *Decision trees, *Energy storage
Abstract: Under high renewable energy penetration, power system operation modes exhibit significant diversity and structural complexity, posing challenges to traditional scenario‐based analysis methods in capturing their formation mechanisms. This paper proposes an interpretable analytical framework for operation mode identification and driving mechanism analysis. Based on year‐round operational data, clustering is employed to label similar operation states, while the core analysis focuses on a decision tree model combined with the SHapley Additive Explanations (SHAP) method to automatically identify key driving factors and quantify their contributions. A robustness verification strategy is further developed through clustering parameter perturbation and model simplification comparison, ensuring the stability and explanatory adequacy of the identified factors. Case studies on both the HRP‐38 benchmark test system and a real‐world 154 node power system demonstrate that, as renewable energy penetration increases, operation modes become more numerous and structurally complex, with their formation mechanism shifting from load‐ and thermal‐dominated patterns to renewable–storage coordinated structures. The proposed framework provides accurate mode identification while enabling clear and physically interpretable insights into their formation mechanisms, offering practical support for operation analysis and planning‐oriented decision‐making in high‐renewable power systems. [ABSTRACT FROM AUTHOR]
Database: Energy & Power Source
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Header DbId: enr
DbLabel: Energy & Power Source
An: 194548619
AccessLevel: 6
PubType: Academic Journal
PubTypeId: academicJournal
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  Label: Title
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  Data: Operation Mode Identification for High Renewable Energy Penetration Power Systems Based on Planning–Operation Coupling and SHAP Interpretability.
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  Data: <searchLink fieldCode="AR" term="%22Yang%2C+Haotian%22">Yang, Haotian</searchLink><relatesTo>1</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Zhu%2C+Shiyu%22">Zhu, Shiyu</searchLink><relatesTo>2</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Fu%2C+Mengyu%22">Fu, Mengyu</searchLink><relatesTo>3</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Wang%2C+Peng%22">Wang, Peng</searchLink><relatesTo>3</relatesTo> (AUTHOR)<i> wangpeng2020@mail.tsinghua.edu.cn</i><br /><searchLink fieldCode="AR" term="%22Xiong%2C+Yijin%22">Xiong, Yijin</searchLink><relatesTo>1</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Wang%2C+Han%22">Wang, Han</searchLink><relatesTo>4</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Meraj%2C+Sheikh+Tanzim%22">Meraj, Sheikh Tanzim</searchLink> (AUTHOR)<i> s.meraj@deakin.edu.au</i>
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  Data: <searchLink fieldCode="JN" term="%22International+Transactions+on+Electrical+Energy+Systems%22">International Transactions on Electrical Energy Systems</searchLink>. 6/11/2026, Vol. 2026, p1-16. 16p.
– Name: Subject
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  Data: *<searchLink fieldCode="DE" term="%22Renewable+energy+sources%22">Renewable energy sources</searchLink><br />*<searchLink fieldCode="DE" term="%22Shapley+Additive+Explanations%22">Shapley Additive Explanations</searchLink><br />*<searchLink fieldCode="DE" term="%22Electric+power+system+management%22">Electric power system management</searchLink><br />*<searchLink fieldCode="DE" term="%22Cluster+analysis+%28Statistics%29%22">Cluster analysis (Statistics)</searchLink><br />*<searchLink fieldCode="DE" term="%22Electric+power+systems%22">Electric power systems</searchLink><br />*<searchLink fieldCode="DE" term="%22Decision+trees%22">Decision trees</searchLink><br />*<searchLink fieldCode="DE" term="%22Energy+storage%22">Energy storage</searchLink>
– Name: Abstract
  Label: Abstract
  Group: Ab
  Data: Under high renewable energy penetration, power system operation modes exhibit significant diversity and structural complexity, posing challenges to traditional scenario‐based analysis methods in capturing their formation mechanisms. This paper proposes an interpretable analytical framework for operation mode identification and driving mechanism analysis. Based on year‐round operational data, clustering is employed to label similar operation states, while the core analysis focuses on a decision tree model combined with the SHapley Additive Explanations (SHAP) method to automatically identify key driving factors and quantify their contributions. A robustness verification strategy is further developed through clustering parameter perturbation and model simplification comparison, ensuring the stability and explanatory adequacy of the identified factors. Case studies on both the HRP‐38 benchmark test system and a real‐world 154 node power system demonstrate that, as renewable energy penetration increases, operation modes become more numerous and structurally complex, with their formation mechanism shifting from load‐ and thermal‐dominated patterns to renewable–storage coordinated structures. The proposed framework provides accurate mode identification while enabling clear and physically interpretable insights into their formation mechanisms, offering practical support for operation analysis and planning‐oriented decision‐making in high‐renewable power systems. [ABSTRACT FROM AUTHOR]
PLink https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=enr&AN=194548619
RecordInfo BibRecord:
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      – Type: doi
        Value: 10.1155/etep/5130077
    Languages:
      – Code: eng
        Text: English
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        PageCount: 16
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      – SubjectFull: Renewable energy sources
        Type: general
      – SubjectFull: Shapley Additive Explanations
        Type: general
      – SubjectFull: Electric power system management
        Type: general
      – SubjectFull: Cluster analysis (Statistics)
        Type: general
      – SubjectFull: Electric power systems
        Type: general
      – SubjectFull: Decision trees
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      – SubjectFull: Energy storage
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      – TitleFull: Operation Mode Identification for High Renewable Energy Penetration Power Systems Based on Planning–Operation Coupling and SHAP Interpretability.
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            NameFull: Yang, Haotian
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            NameFull: Zhu, Shiyu
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            NameFull: Fu, Mengyu
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            – D: 11
              M: 06
              Text: 6/11/2026
              Type: published
              Y: 2026
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              Value: 2026
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            – TitleFull: International Transactions on Electrical Energy Systems
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