Page 185 - 《中国电力》2026年第5期

赵军等：物理数据融合的风电场功率预测 2026 年第 5 期

prospect of key technologies for anti/de-icing technologies of wind PENG Sui, LI Feng, WANG Yanfeng, et al. Reserve capacity
turbine blades[J]. Electric Power, 2026, 59(3): 103–113. planning for high-proportion wind power systems considering
[6] 杨国华, 祁鑫, 贾睿, 等. 基于 CEEMD-SE 的 CNN&LSTM-GRU 短 extremely hot and cold days[J]. Guangdong Electric Power, 2025,
期风电功率预测 [J]. 中国电力, 2024, 57(2): 55–61. 38(10): 1–13.
YANG Guohua, QI Xin, JIA Rui, et al. Short-term wind power [14] 郑广宇, 辛征, 迟蔚然, 等. 基于偏最小二乘和改进时间卷积网络的
forecast based on CNN & LSTM-GRU model integrated with 风电场超短期发电功率预测 [J]. 山东电力技术, 2025, 52(12):
CEEMD-SE algorithm[J]. Electric Power, 2024, 57(2): 55–61. 1–16.
[7] 朱东杰, 吕昆烨, 宋长虹, 等. 基于密度修正的风电功率曲线线性拟 ZHENG Guangyu, XIN Zheng, CHI Weiran, et al. Ultra-short term
合模型 [J]. 综合智慧能源, 2025, 47(3): 84–91. power generation prediction of wind farm based on partial least
ZHU Dongjie, LYU Kunye, SONG Changhong, et al. Linear fitting squares and improved time convolutional network[J]. Shandong
model for wind power curves based on density correction[J]. Electric Power, 2025, 52(12): 1–16.

Integrated Intelligent Energy, 2025, 47(3): 84–91. [15] 皇甫陈萌, 阮贺彬, 徐俊俊. 融合 CEEMDAN-CNN-LSTM 的风电
[8] 张柏林, 李希德, 魏博, 等. 基于改进的场景分类和去粗粒化 机组多气象场景功率回归预测 [J]. 综合智慧能源, 2025, 47(9):

MCMC 的风电出力模拟方法 [J]. 电测与仪表, 2024, 61(7): 41–49, 38–50.
122. HUANGFU Chenmeng, RUAN Hebin, XU Junjun. Power regression
ZHANG Bolin, LI Xide, WEI Bo, et al. Wind power output prediction for wind turbines in multi-meteorological scenarios based
simulation method based on improved scene classification algorithm on CEEMDAN-CNN-LSTM integration[J]. Integrated Intelligent
and coarse-grained MCMC[J]. Electrical Measurement & Energy, 2025, 47(9): 38–50.
Instrumentation, 2024, 61(7): 41–49, 122. [16] 苏向敬, 宇海波, 符杨, 等. 基于 DALSTM 和联合分位数损失的海
[9] 程先龙, 张杰, 李思莹, 等. 基于 VMD-BP-BiLSTM 的短期风电功 上风电功率概率预测 [J]. 中国电力, 2023, 56(11): 10–19.
率预测 [J]. 综合智慧能源, 2025, 47(6): 20–29. SU Xiangjing, YU Haibo, FU Yang, et al. Probabilistic forecasting of
CHENG Xianlong, ZHANG Jie, LI Siying, et al. Short-term wind offshore wind power based on dual-stage attentional LSTM and joint
power prediction based on VMD-BP-BiLSTM[J]. Integrated quantile loss function[J]. Electric Power, 2023, 56(11): 10–19.
Intelligent Energy, 2025, 47(6): 20–29. [17] 赵建红, 东星, 刘仲稳, 等. 基于模糊控制的混合储能平抑风电功率
[10] 司雅昕, 刘训强, 苏向敬, 等. 海上风电功率预测研究综述 [J]. 浙江 波动 [J]. 湖南电力, 2023, 43(6): 124–131.
电力, 2025, 44(11): 59–71. ZHAO Jianhong, DONG Xing, LIU Zhongwen, et al. Hybrid energy
SI Yaxin, LIU Xunqiang, SU Xiangjing, et al. A review of offshore storage based on fuzzy control stabilizes wind power fluctuations[J].
wind power forecasting studies[J]. Zhejiang Electric Power, 2025, Hunan Electric Power, 2023, 43(6): 124–131.
44(11): 59–71. [18] GUO N Z, SHI K Z, LI B, et al. A physics-inspired neural network
[11] 黄学勤, 杨鹏举, 赵耀, 等. 考虑多维气象数据与时间影响的风电功 model for short-term wind power prediction considering wake
率区间预测 [J]. 浙江电力, 2026, 45(1): 66–77. effects[J]. Energy, 2022, 261: 125208.
HUANG Xueqin, YANG Pengju, ZHAO Yao, et al. Wind power [19] VLADISLAVLEVA E, FRIEDRICH T, NEUMANN F, et al.
interval forecasting based on multidimensional meteorological data Predicting the energy output of wind farms based on weather data:
and temporal effects[J]. Zhejiang Electric Power, 2026, 45(1): 66–77. Important variables and their correlation[J]. Renewable Energy,
[12] 孟丹, 陈正洪, 许杨, 等. 极端天气对风电开发全过程的影响及应对 2013, 50: 236–243.
策略 [J]. 南方能源建设, 2025, 12(2): 1–14. [20] FENG C, CUI M J, HODGE B M, et al. A data-driven multi-model
MENG Dan, CHEN Zhenghong, XU Yang, et al. The impact of methodology with deep feature selection for short-term wind
extreme weather on the entire process of wind power development forecasting[J]. Applied Energy, 2017, 190: 1245–1257.
and response strategies[J]. Southern Energy Construction, 2025, [21] 屈伯阳, 付立思. 基于 NWP 风速修正与 VMD-DBO-DELM 残差
12(2): 1–14. 建模的风电功率预测研究 [J]. 山东电力技术, 2025, 52(2): 32–45.
[13] 彭穗, 李峰, 王彦峰, 等. 考虑极热极寒日的高比例风电电力系统备 QU Boyang, FU Lisi. Research on wind power prediction based on
用容量规划 [J]. 广东电力, 2025, 38(10): 1–13. NWP wind speed correction and VMD-DBO-DELM residual

181