基于EEMD-GA-BP模型的风电功率短期预测研究

doi:10.16088/j.issn.1001-6600.2021060912

广西师范大学学报（自然科学版） ›› 2022, Vol. 40 ›› Issue (1): 166-174.doi: 10.16088/j.issn.1001-6600.2021060912

基于EEMD-GA-BP模型的风电功率短期预测研究

朱恩文^*, 朱安麒, 王洁丹, 刘玉娇

长沙理工大学数学与统计学院, 湖南长沙 410114

收稿日期:2021-06-09 修回日期:2021-08-05 出版日期:2022-01-25 发布日期:2022-01-24
通讯作者: 朱恩文(1976—), 男, 湖南湘阴人, 长沙理工大学教授,博士。E-mail: engwenzhu@126.com
基金资助:
国家统计局科学研究项目(2019LY21); 长沙理工大学研究生创新基金(CX2020SS86, CX2020SS87)

Research on Wind Power Short-term Prediction Based on EEMD-GA-BP Model

ZHU Enwen^*, ZHU Anqi, WANG Jiedan, LIU Yujiao

School of Mathematics and Statistics, Changsha University of Science and Technology, Changsha Hunan 410114, China

Received:2021-06-09 Revised:2021-08-05 Online:2022-01-25 Published:2022-01-24

摘要/Abstract

摘要： 随着我国风电产业迅速发展,风电并网规模不断扩大,准确预测风电场输出功率是降低风电波动对电网影响、提高电能质量、保证电网稳定运行的有效途径。本文采用箱型分析及热卡填充的方法对数据集中的异常数据进行清洗与重构。采用遗传算法与EEMD分解算法相结合的方式改进BP算法,并且根据不同时间尺度预测结果对比,相对于传统预测模型而言,本文EEMD-GA-BP模型具有预测精度高,预测效果更为稳定等特点。

关键词: 风电功率短期预测, 反向传播神经网络, 集成经验模态分解, 遗传算法

Abstract: With the rapid development of China’s wind power industry, the scale of wind power grid integration is constantly expanding. Accurate prediction of wind farm output power is an effective way to reduce the impact of wind power fluctuations on the power grid, which can improve power quality, and ensure the stable operation of the power grid. In this paper, the method of box analysis and hot card filling is used to clean and reconstruct the abnormal data in the data set. The BP algorithm is improved by combining genetic algorithm and EEMD decomposition algorithm. According to the comparison of prediction results with different time scales, the EEMD-GA-BP model has higher prediction accuracy and more stable prediction effect compared with the traditional prediction model.

Key words: wind power short-term prediction, back propagation neural network, integrated empirical mode decomposition, genetic algorithm

中图分类号:

O212.1

朱恩文, 朱安麒, 王洁丹, 刘玉娇. 基于EEMD-GA-BP模型的风电功率短期预测研究[J]. 广西师范大学学报（自然科学版）, 2022, 40(1): 166-174.

ZHU Enwen, ZHU Anqi, WANG Jiedan, LIU Yujiao. Research on Wind Power Short-term Prediction Based on EEMD-GA-BP Model[J]. Journal of Guangxi Normal University(Natural Science Edition), 2022, 40(1): 166-174.

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基于EEMD-GA-BP模型的风电功率短期预测研究

Research on Wind Power Short-term Prediction Based on EEMD-GA-BP Model

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