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Data-Driven Risk Warning of Electricity Sales Companies in the Whole Business Process

Author

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  • Biyun Chen

    (Guangxi Key Laboratory of Power System Optimization and Energy-Saving Technology, School of Electrical Engineering, Guangxi University, Nanning 530004, China)

  • Tianwang Fu

    (Guangxi Key Laboratory of Power System Optimization and Energy-Saving Technology, School of Electrical Engineering, Guangxi University, Nanning 530004, China)

  • Liming Wei

    (Guangxi Key Laboratory of Power System Optimization and Energy-Saving Technology, School of Electrical Engineering, Guangxi University, Nanning 530004, China)

  • Rong Zheng

    (China Southern Power Grid Guangxi Electric Power Trading Center, Nanning 530023, China)

  • Zhe Lin

    (China Southern Power Grid Guangxi Electric Power Trading Center, Nanning 530023, China)

  • Haiwei Liu

    (Guangxi Key Laboratory of Power System Optimization and Energy-Saving Technology, School of Electrical Engineering, Guangxi University, Nanning 530004, China)

  • Zhijun Qin

    (Guangxi Key Laboratory of Power System Optimization and Energy-Saving Technology, School of Electrical Engineering, Guangxi University, Nanning 530004, China)

Abstract

As China’s power market reforms deepen, the scale of market operations and the number of participants have reached new highs, introducing increasingly complex threats and heightened risk scenarios. Traditional risk early warning systems for electricity sales companies are heavily influenced by subjective factors, incomplete data, and poor real-time performance, which cannot meet the requirements of sustainable development. To achieve efficient, full-chain, and sustainable risk control, this paper proposes a data-driven risk warning method for electricity sales companies, encompassing the entire sales process. Firstly, based on data correlations across the electricity sales process, appropriate data sources for risk warnings are identified. Key elements are then extracted using Principal Component Analysis (PCA), while historical business data is adaptively clustered, with risk warning levels classified using the Adaptive Sparrow Optimization Density Peak Clustering Algorithm (DPC-SSA). Lastly, dynamic risk warnings are generated through the stacking identification model. The effectiveness and practicality of the proposed method are validated through an analysis using real data from a provincial power trading management platform.

Suggested Citation

  • Biyun Chen & Tianwang Fu & Liming Wei & Rong Zheng & Zhe Lin & Haiwei Liu & Zhijun Qin, 2025. "Data-Driven Risk Warning of Electricity Sales Companies in the Whole Business Process," Sustainability, MDPI, vol. 17(9), pages 1-22, April.
    • Handle: RePEc:gam:jsusta:v:17:y:2025:i:9:p:3884-:d:1642590
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    References listed on IDEAS

    as
    1. Gökhan Ekinci & Harun Kemal Ozturk, 2025. "Forecasting Wind Farm Production in the Short, Medium, and Long Terms Using Various Machine Learning Algorithms," Energies, MDPI, vol. 18(5), pages 1-27, February.
    2. Giovanni Baldissarro & Maria Elena Bruni & Gianpaolo Iazzolino & Donato Morea & Stefania Veltri, 2024. "Does It Pay Off to Integrate ESG Performance into Bank Investment Portfolio Selection? Empirical Evidence in the European Energy Sector," Sustainability, MDPI, vol. 16(23), pages 1-20, December.
    3. Allen, D.E. & Powell, R.J. & Singh, A.K., 2016. "Take it to the limit: Innovative CVaR applications to extreme credit risk measurement," European Journal of Operational Research, Elsevier, vol. 249(2), pages 465-475.
    4. Wanru Yang & Long Chen & Tong Ke & Huan He & Dehu Li & Kai Liu & Huiming Li, 2024. "Carbon Emission Trend Prediction for Regional Cities in Jiangsu Province Based on the Random Forest Model," Sustainability, MDPI, vol. 16(23), pages 1-17, November.
    5. Yingya Zhou & Chin Hao Chong & Weidou Ni & Zheng Li & Xiaoyong Zhou & Linwei Ma, 2024. "Data Modeling and Synchronization Method to Align Power Trading Rules for Integrated Energy Management Systems," Sustainability, MDPI, vol. 16(20), pages 1-20, October.
    6. Jun Dong & Dongxue Wang & Dongran Liu & Palidan Ainiwaer & Linpeng Nie, 2019. "Operation Health Assessment of Power Market Based on Improved Matter-Element Extension Cloud Model," Sustainability, MDPI, vol. 11(19), pages 1-25, October.
    7. Jing Liu & Qi Chu & Wenchao Yuan & Dasheng Zhang & Weifeng Yue, 2024. "WQI Improvement Based on XG-BOOST Algorithm and Exploration of Optimal Indicator Set," Sustainability, MDPI, vol. 16(24), pages 1-24, December.
    8. Mazin Alahmadi, 2024. "Optimizing Data Quality for Sustainable Development: An Integration of Green Finance with Financial Market Regulations," Sustainability, MDPI, vol. 16(23), pages 1-17, November.
    9. Li, Xueqin & Zheng, Zhuoji & Luo, Beier & Shi, Daqian & Han, Xianfeng, 2024. "The impact of electricity sales side reform on energy technology innovation: An analysis based on SCP paradigm," Energy Economics, Elsevier, vol. 136(C).
    10. Hui Wang & Congcong Wang & Wenhui Zhao, 2022. "Decision on Mixed Trading between Medium- and Long-Term Markets and Spot Markets for Electricity Sales Companies under New Electricity Reform Policies," Energies, MDPI, vol. 15(24), pages 1-23, December.
    11. Hengchun Li & Qiujun Lan & Qingyue Xiong, 2024. "Methodology for Smooth Transition from Experience-Based to Data-Driven Credit Risk Assessment Modeling under Data Scarcity," Mathematics, MDPI, vol. 12(15), pages 1-22, August.
    12. Cheng, Xiong & Lv, Xin & Li, Xianshan & Zhong, Hao & Feng, Jia, 2023. "Market power evaluation in the electricity market based on the weighted maintenance object," Energy, Elsevier, vol. 284(C).
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