Research on credit rating and risk measurement of electricity retailers based on Bayesian Best Worst Method-Cloud Model and improved Credit Metrics model in China's power market
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DOI: 10.1016/j.energy.2022.124088
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- 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).
- Jiacheng Jia & Guiliang Yin & Lingling Sun & Ahmed Abu-Siada, 2022. "Schedule Strategy Considering the Overload Violation Risk to the Security Region in Distribution Networks," Energies, MDPI, vol. 15(23), pages 1-18, November.
- Yu Xia & Ta Xu & Ming-Xia Wei & Zhen-Ke Wei & Lian-Jie Tang, 2023. "Predicting Chain’s Manufacturing SME Credit Risk in Supply Chain Finance Based on Machine Learning Methods," Sustainability, MDPI, vol. 15(2), pages 1-18, January.
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Keywords
Electricity retailers; Credit rating; Risk measurement; Bayesian Best Worst Method (BBWM)-Cloud; Credit metrics;All these keywords.
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