A Novel Hybrid CNN-XGBoost Model for Photovoltaic System Power Forecasting

被引：0
|
作者：
Bashir, Safia Babikir [1 ]
Farag, Mena Maurice [1 ]
Hamid, Abdul Kadir [1 ]
Adam, Ali Ahmed [1 ]
Abo-Khalil, Ahmed Galal [1 ]
Bansal, Ramesh [1 ]
机构：
[1] Sustainable Energy and Power Systems Research Center, Research Institute of Sciences and Engineering, University of Sharjah, Smart Grid and Power Systems Research Group, Department of Electrical Engineering, Sharjah, United Arab Emirates
来源：
Proceedings of the 2024 6th International Youth Conference on Radio Electronics, Electrical and Power Engineering, REEPE 2024 | 2024年
关键词：
Compilation and indexing terms; Copyright 2024 Elsevier Inc;
D O I：
暂无
中图分类号：
学科分类号：
摘要：
Convolution - Meteorology - Neural network models - Solar power generation - Weather forecasting
引用
收藏
相关论文
共 50 条
  • [31] Hybrid Models Based on LSTM and CNN Architecture with Bayesian Optimization for Short-Term Photovoltaic Power Forecasting
    Chen, Yaobang
    Shi, Jie
    Cheng, Xingong
    Ma, Xiaoyi
    2021 IEEE IAS INDUSTRIAL AND COMMERCIAL POWER SYSTEM ASIA (IEEE I&CPS ASIA 2021), 2021, : 1415 - 1422
  • [32] Power Load Forecasting Based on the Combined Model of LSTM and XGBoost
    Li, Chen
    Chen, Zhenyu
    Liu, Jinbo
    Li, Dapeng
    Gao, Xingyu
    Di, Fangchun
    Li, Lixin
    Ji, Xiaohui
    PROCEEDINGS OF 2019 INTERNATIONAL CONFERENCE ON PATTERN RECOGNITION AND ARTIFICIAL INTELLIGENCE (PRAI 2019), 2019, : 46 - 51
  • [33] Comparing the Johansen VECM model to an AI hybrid model for the short term photovoltaic power forecasting
    Coya, Zahiir
    Khoodaruth, Abdel
    Ramenah, Harry
    Oree, Vishwamitra
    Murdan, Anshu Prakash
    Bessafi, Miloud
    2024 1ST INTERNATIONAL CONFERENCE ON SMART ENERGY SYSTEMS AND ARTIFICIAL INTELLIGENCE, SESAI 2024, 2024, : 51 - 56
  • [34] A Novel Power Output Model for Photovoltaic System.
    Kittisontirak, Songkiate
    Dawan, Promphak
    Atiwongsangthong, Narin
    Titiroongruang, Wisut
    Chinnavornrungsee, Perawut
    Hongsingthong, Aswin
    Sriprapha, Kobsak
    Manosukritkul, Phasapon
    2017 INTERNATIONAL ELECTRICAL ENGINEERING CONGRESS (IEECON), 2017,
  • [35] Photovoltaic Power Forecasting With a Hybrid Deep Learning Approach
    Li, Gangqiang
    Xie, Sen
    Wang, Bozhong
    Xin, Jiantao
    Li, Yunfeng
    Du, Shengnan
    IEEE ACCESS, 2020, 8 (08) : 175871 - 175880
  • [36] Short-Term Photovoltaic Power Forecasting Based on a Novel Autoformer Model
    Huang, Yuanshao
    Wu, Yonghong
    SYMMETRY-BASEL, 2023, 15 (01):
  • [37] XGBoost-SFS and Double Nested Stacking Ensemble Model for Photovoltaic Power Forecasting under Variable Weather Conditions
    Zhou, Bowen
    Chen, Xinyu
    Li, Guangdi
    Gu, Peng
    Huang, Jing
    Yang, Bo
    SUSTAINABILITY, 2023, 15 (17)
  • [38] Photovoltaic power forecasting: A hybrid deep learning model incorporating transfer learning strategy
    Tang, Yugui
    Yang, Kuo
    Zhang, Shujing
    Zhang, Zhen
    RENEWABLE & SUSTAINABLE ENERGY REVIEWS, 2022, 162
  • [39] Power Forecasting in Photovoltaic System using Hybrid ANN and Wavelet Transform based Method
    Singh, Pooja
    Mandpura, Anup Kumar
    Yadav, Vinod Kumar
    JOURNAL OF SCIENTIFIC & INDUSTRIAL RESEARCH, 2023, 82 (01): : 63 - 74
  • [40] Exponential Smoothing Model for Photovoltaic Power Forecasting
    De Falco, Pasquale
    Di Noia, Luigi Pio
    Rizzo, Renato
    PROCEEDINGS OF 9TH INTERNATIONAL CONFERENCE ON MODERN POWER SYSTEMS (MPS 2021), 2021,
12345