Ultra-short-term wind power multi-step forecasting based on improved AWNN

被引：0
|
作者：
Lu, Jiping [1 ]
Zeng, Yanting [1 ]
Yu, Hua [2 ]
Liang, Pei [3 ]
Zhuang, Yi [1 ]
Ge, Jinjin [4 ]
机构：
[1] State Key Laboratory of Power Transmission Equipment & System Security and New Technology (Chongqing University), Chongqing,400044, China
[2] Chengdu Power Supply Company of State Grid Sichuan Provence Electric Power Company, Chengdu,610000, China
[3] Institute of Economics and Technology of State Grid Jiangsu Electric Power Limited Company, Nanjing,210008, China
[4] Wuhu Power Supply Company of State Grid Anhui Provence Electric Power Limited Company, Wuhu,241000, China
来源：
Taiyangneng Xuebao/Acta Energiae Solaris Sinica | 2021年 / 42卷 / 01期
关键词：
Adaptive wavelet neural network - BP neural networks - DE algorithms - Differential evolution algorithms - Improved particle swarm optimization algorithms - Local optima - Multi-step forecasting - Multi-step prediction;
D O I：
10.19912/j.0254-0096.tynxb.2018-0714
中图分类号：
学科分类号：
摘要：
17
引用
收藏
页码：166 / 173
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