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All issues Volume 352 (2022) E3S Web Conf., 352 (2022) 03003 References
Open Access
Issue
E3S Web Conf.
Volume 352, 2022
7th International Conference on Energy Science and Applied Technology (ESAT 2022)
Article Number 03003
Number of page(s) 5
Section Energy Sustainability & Energy-Related Environmental Science
DOI https://doi.org/10.1051/e3sconf/202235203003
Published online 27 June 2022
  1. Zou Pinjing, Yao Jiangang, Kong Weihui, et al. Mid-long Term Power Load Forecasting Based on Multivariable Time Series Inversion Self-memory Model[J]. Proceedings of the CSU-EPSA, 2017, 29(10): 98–105. [Google Scholar]
  2. Yuan Tie-Jiang, Yuan Jian-Dang, Chao Qin, et al. Study on the comprehensive model of mid-long term load forecasting[J]. Power System Protection and Control , 2012, 40(14): 143–146. [Google Scholar]
  3. Li Yiyan, Yan Zheng, Feng Donghan. Mid/long-term load forecasting model considering urbanization[J]. Electric Power Automation Equipment, 2016, 36(04): 54–61. [Google Scholar]
  4. Zhang Guanying, Xian Yiming, Ge Leijiao, et al. Medium and long-term load forecasting model based on Verhulst-SVM under new normal economy[J]. Electrical Measurement & Instrumentation, 2019, 56(1): 102–107. [Google Scholar]
  5. Hi Jiaqi, Zhang Jianhua. Load Forecasting Based on Multi-model by Stacking Ensemble Learning[J]. Proceedings of the CSEE, 2019, 39(14): 4032–4042. [Google Scholar]
  6. Liu Hengyong, Liu Yongli, Deng Shicong, et al. A power load identification method based on LSTM model [J]. Electrical Measurement & Instrumentation, 2019, 56(23): 62–69. [Google Scholar]
  7. Zheng Zhi-Jie, Li Lei, Zhao Lan-ming. Medium and long term load forecasting considering data uncertainty[J]. POWER SYSTEM PROTECTION AND CONTROL, 2011(07): 130–133. [Google Scholar]
  8. Gu Xi-Hua, Xing Mian, Niu Dong-xiao, et al. Medium and long-term load forecasting based on multifactor-influenced gray artificial neural network optimal combination algorithm in power system[J]. OURNAL OF NORTH CHINA ELECTRIC POWER UNIVERSITY, 2007, 34(6): 32–36. [Google Scholar]
  9. Chen Jianyong, Su Yihao. A Forecasting Model of Medium/Long Term Power Load in Combination of the Support Vector Machine and Markov Chain Algorithms[J]. Southern Power System Technology, 2012, 6(1): 54–57. [Google Scholar]
  10. Wu Yaohua. Long term load forecasting based on M-GRNN in power system[J]. RELAY, 2007, 35(6): 45–53. [Google Scholar]
  11. Zhao Zhipu, Gao Chao, Shen Yanxia, et al. A ethod for Load Forecasting Based on Correlated Fuzzy Neural Network and Improved Artificial Bee olony Algorithm. Electric Power, 2018, 51(2): 54–60. [Google Scholar]

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