
为有效检测光伏系统发电异常,文中提出了一种融合量子粒子群优化算法(quantum particle swarm optimization
QPSO)与长短期记忆神经网络(long short-term memory
LSTM)的光伏功率异常检测方法。首先,进行光伏系统数据的预处理,剔除异常值以确保数据质量,运用相关性分析,确定对光伏输出功率影响显著的气象参数,并将其作为模型的输入特征;接着,采用QPSO算法,优化LSTM网络的超参数,构建一个高效且精准的预测模型;最后,通过实际值与模型预测值对比,检测光伏系统异常情况。实验结果表明,构建的QPSO-LSTM模型可以增强预测的准确性,通过分析实际功率输出与模型预测值之间的差异,可以有效识别光伏系统中的发电异常情况,为系统的稳定运行提供了坚实的技术支持。
Ning Zhou,Bowen Shang,Mingming Xu,Lei Peng,Yafei Zhang.Enhancing photovoltaic power prediction using a CNN-LSTM-attention hybrid model with Bayesian hyperparameter optimization[J].Global Energy Interconnection,2024(05).
林维修,李峰,王海峰,许育燕,金科扬.基于图像处理的光伏组件热斑缺陷检测方法[J].计算技术与自动化,2024(03).
秦宇,许野,王鑫鹏,王涛,李薇.基于改进FCM-LSTM的光伏出力短期预测研究[J].太阳能学报,2024(08).
周晓东,肖正江,杨坤鹏,牛保佳.基于改进量子粒子群算法的叶片延长翼型厚度优化设计[J].节能技术,2024(04).
周勤勇,李根兆,秦晓辉,施浩波,陈文静,龚浩岳.能源革命下的电力系统范式转换分析[J].中国电力,2024(03).
梁健锋,胡振球,黄灿,许长盛,曾飞,黄浩锋.基于红外热成像检测的光伏电站异常分析[J].太阳能,2024(01).
谭才兴,岳雨霏,汤赐.基于QPSO-LSTM的短期风电负荷预测模型[J].中阿科技论坛(中英文),2023(12).
薛阳,李金星,杨江天,李清,丁凯.基于相似日分析和改进鲸鱼算法优化LSTM网络模型的光伏功率短期预测[J].南方电网技术,2024(11).
王涛,王旭,许野,李薇.计及相似日的LSTM光伏出力预测模型研究[J].太阳能学报,2023(08).
李斌,高鹏,郭自强.改进蜣螂算法优化LSTM的光伏阵列故障诊断[J].电力系统及其自动化学报,2024(08).
赵博超,马嘉骏,崔磊,栾文鹏,朱静.基于改进VMD-XGBoost-BiLSTM组合模型的光伏发电异常检测[J].计算机工程,2024(03).
朱润泽,王德军.基于LSTM神经网络的光伏系统功率预测[J].电力科技与环保,2023(03).
吉兴全,刘健,叶平峰,张玉敏,杨明,于一潇.计及灵活性与可靠性的综合能源系统优化调度[J].电力系统自动化,2023(08).
丛伟伦,张博,夏亚东,邢朝路.基于马尔可夫链的光伏电站遮挡实时诊断算法[J].太阳能学报,2020(04).
Shiue Der Lu,Hwa Dong Liu,Meng Hui Wang,Chia Chun Wu.A novel strategy for multitype fault diagnosis in photovoltaic systems using multiple regression analysis and support vector machines[J].Energy Reports,2024.
E.A. Ramadan,Nada M. Moawad,Belal A. Abouzalm,Ali A. Sakr,Wessam F. Abouzaid,Ghada M. El Banby.An innovative transformer neural network for fault detection and classification for photovoltaic modules[J].Energy Conversion and Management,2024.
Satpathy Priya Ranjan,Aljafari Belqasem,Thanikanti Sudhakar Babu,Madeti Siva Rama Krishna.Electrical fault tolerance of photovoltaic array configurations: Experimental investigation, performance analysis, monitoring and detection[J].Renewable Energy,2023.
Mellit Adel.An embedded solution for fault detection and diagnosis of photovoltaic modules using thermographic images and deep convolutional neural networks[J].Engineering Applications of Artificial Intelligence,2022.
Qu Jiaqi,Qian Zheng,Pei Yan,Wei Lu,Zareipour Hamidreza,Sun Qiang.An unsupervised hourly weather status pattern recognition and blending fitting model for PV system fault detection[J].Applied Energy,2022.
aff > .Application of Artificial Neural Networks to photovoltaic fault detection and diagnosis: A review[J].Renewable and Sustainable Energy Reviews,2020.
Zhao Xin-gang,Zhang Ze-qi,Xie Yi-min,Meng Jin.Economic-environmental dispatch of microgrid based on improved quantum particle swarm optimization[J].Energy,2020(C).
Solar Energy Research Cell, School of Electrical Engineering, VIT University, Vellore, India,Solar Energy Research Cell, School of Electrical Engineering, VIT University, Vellore, India.A comprehensive review on protection challenges and fault diagnosis in PV systems[J].Renewable and Sustainable Energy Reviews,2018.
Fouzi Harrou,Ying Sun,Bilal Taghezouit,Ahmed Saidi,Mohamed-Elkarim Hamlati.Reliable fault detection and diagnosis of photovoltaic systems based on statistical monitoring approaches[J].Renewable Energy,2018.
0
浏览量
0
下载量
0
CSCD
关联资源
相关文章
相关作者
相关机构
京公网安备11010802024621