Research on Forecasting Method of Distribution Network Investment Scale of Municipal Power Supply Enterprise Considering Power Supply Division and Cost Difference Level

Gou Quanfeng; Yang Jie; Zhou Fei; Hu Lin; Yu Guangxiu; Li Qian; Du Le

doi:10.1051/e3sconf/202124501032

All issues

Volume 245 (2021)

E3S Web Conf., 245 (2021) 01032

References

Open Access

Issue		E3S Web Conf. Volume 245, 2021 2021 5^th International Conference on Advances in Energy, Environment and Chemical Science (AEECS 2021)


Article Number		01032
Number of page(s)		4
Section		Energy Development and Utilization and Energy-Saving Technology Application
DOI		https://doi.org/10.1051/e3sconf/202124501032
Published online		24 March 2021

Wang Ling, Wu Hongliang, Peng Daoxin. Grid investment scale prediction under the new round of transmission and distribution price supervision cycle——Based on optimized support vector machine model[J]. Technoeconomics, 2020, 39(10): 45–53. [Google Scholar]
Liu Wei, Li Meng, Li Qiuyan, Wang Lili, Hu Po, Ling Ruchen, Gao Yuqin, Li Zhi. Power grid portfolio forecasting method based on improved genetic algorithm[J]. Power System Protection and Control, 2020, 48(08):78–85. [Google Scholar]
Xie Wei, Pan Wenming, Wang Chenghua, Chen Li, Wang Yang, Ma Jing, Li Zhiwei, Du Haihong. Research on the medium and long-term investment scale prediction model of provincial power grid based on support vector machine[J]. Industrial Technology Economy, 2019, 38(08):154–160. [Google Scholar]
Mo Jinhe, Ye Minna. Construction and application of investment forecast allocation model based on asset wall——Taking A Province Power Grid Company as an example [J]. Enterprise Management, 2018(S2): 22–23. [Google Scholar]
Ji Liwei, Yang Liping, Fei Gaiying. Analysis and prediction of influencing factors of power grid project investment [J]. China Electric Power Enterprise Management, 2016(06): 85–92. [Google Scholar]

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[1] Wang Ling, Wu Hongliang, Peng Daoxin. Grid investment scale prediction under the new round of transmission and distribution price supervision cycle——Based on optimized support vector machine model[J]. Technoeconomics, 2020, 39(10): 45–53. [Google Scholar]

[2] Liu Wei, Li Meng, Li Qiuyan, Wang Lili, Hu Po, Ling Ruchen, Gao Yuqin, Li Zhi. Power grid portfolio forecasting method based on improved genetic algorithm[J]. Power System Protection and Control, 2020, 48(08):78–85. [Google Scholar]

[3] Xie Wei, Pan Wenming, Wang Chenghua, Chen Li, Wang Yang, Ma Jing, Li Zhiwei, Du Haihong. Research on the medium and long-term investment scale prediction model of provincial power grid based on support vector machine[J]. Industrial Technology Economy, 2019, 38(08):154–160. [Google Scholar]

[4] Mo Jinhe, Ye Minna. Construction and application of investment forecast allocation model based on asset wall——Taking A Province Power Grid Company as an example [J]. Enterprise Management, 2018(S2): 22–23. [Google Scholar]

[5] Ji Liwei, Yang Liping, Fei Gaiying. Analysis and prediction of influencing factors of power grid project investment [J]. China Electric Power Enterprise Management, 2016(06): 85–92. [Google Scholar]