IDEAS home Printed from https://ideas.repec.org/r/eee/appene/v137y2015icp588-602.html
   My bibliography  Save this item

A load predictive energy management system for supercapacitor-battery hybrid energy storage system in solar application using the Support Vector Machine

Citations

Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
as


Cited by:

  1. Shen, Meng & Lu, Yujie & Wei, Kua Harn & Cui, Qingbin, 2020. "Prediction of household electricity consumption and effectiveness of concerted intervention strategies based on occupant behaviour and personality traits," Renewable and Sustainable Energy Reviews, Elsevier, vol. 127(C).
  2. Gabriel de Freitas Viscondi & Solange N. Alves-Souza, 2021. "Solar Irradiance Prediction with Machine Learning Algorithms: A Brazilian Case Study on Photovoltaic Electricity Generation," Energies, MDPI, vol. 14(18), pages 1-15, September.
  3. Hemmati, Reza & Saboori, Hedayat, 2016. "Emergence of hybrid energy storage systems in renewable energy and transport applications – A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 65(C), pages 11-23.
  4. Jing, Wenlong & Lai, Chean Hung & Wong, Wallace S.H. & Wong, M.L. Dennis, 2018. "A comprehensive study of battery-supercapacitor hybrid energy storage system for standalone PV power system in rural electrification," Applied Energy, Elsevier, vol. 224(C), pages 340-356.
  5. Athanasios Anagnostis & Serafeim Moustakidis & Elpiniki Papageorgiou & Dionysis Bochtis, 2022. "A Hybrid Bimodal LSTM Architecture for Cascading Thermal Energy Storage Modelling," Energies, MDPI, vol. 15(6), pages 1-24, March.
  6. Piotr Piórkowski & Adrian Chmielewski & Krzysztof Bogdziński & Jakub Możaryn & Tomasz Mydłowski, 2018. "Research on Ultracapacitors in Hybrid Systems: Case Study," Energies, MDPI, vol. 11(10), pages 1-13, September.
  7. Duan, Jiandong & Liu, Junjie & Xiao, Qian & Fan, Shaogui & Sun, Li & Wang, Guanglin, 2019. "Cooperative controls of micro gas turbine and super capacitor hybrid power generation system for pulsed power load," Energy, Elsevier, vol. 169(C), pages 1242-1258.
  8. Ma, Jun & Cheng, Jack C.P., 2016. "Identifying the influential features on the regional energy use intensity of residential buildings based on Random Forests," Applied Energy, Elsevier, vol. 183(C), pages 193-201.
  9. Chmielewski, Adrian & Gumiński, Robert & Mączak, Jędrzej & Radkowski, Stanisław & Szulim, Przemysław, 2016. "Aspects of balanced development of RES and distributed micro-cogeneration use in Poland: Case study of a µCHP with Stirling engine," Renewable and Sustainable Energy Reviews, Elsevier, vol. 60(C), pages 930-952.
  10. Meenal, R. & Selvakumar, A. Immanuel, 2018. "Assessment of SVM, empirical and ANN based solar radiation prediction models with most influencing input parameters," Renewable Energy, Elsevier, vol. 121(C), pages 324-343.
  11. Chong, Lee Wai & Wong, Yee Wan & Rajkumar, Rajprasad Kumar & Rajkumar, Rajpartiban Kumar & Isa, Dino, 2016. "Hybrid energy storage systems and control strategies for stand-alone renewable energy power systems," Renewable and Sustainable Energy Reviews, Elsevier, vol. 66(C), pages 174-189.
  12. Li, Yanying & Che, Jinxing & Yang, Youlong, 2018. "Subsampled support vector regression ensemble for short term electric load forecasting," Energy, Elsevier, vol. 164(C), pages 160-170.
  13. Noorollahi, Younes & Golshanfard, Aminabbas & Ansaripour, Shiva & Khaledi, Arian & Shadi, Mehdi, 2021. "Solar energy for sustainable heating and cooling energy system planning in arid climates," Energy, Elsevier, vol. 218(C).
  14. Wakui, Tetsuya & Kawayoshi, Hiroki & Yokoyama, Ryohei & Aki, Hirohisa, 2016. "Operation management of residential energy-supplying networks based on optimization approaches," Applied Energy, Elsevier, vol. 183(C), pages 340-357.
  15. Ma, Weiwu & Fang, Song & Liu, Gang & Zhou, Ruoyu, 2017. "Modeling of district load forecasting for distributed energy system," Applied Energy, Elsevier, vol. 204(C), pages 181-205.
  16. Wang, Bin & Xu, Jun & Cao, Binggang & Ning, Bo, 2017. "Adaptive mode switch strategy based on simulated annealing optimization of a multi-mode hybrid energy storage system for electric vehicles," Applied Energy, Elsevier, vol. 194(C), pages 596-608.
  17. Noah Lee & Chen Hon Nee & Seong Shan Yap & Kwong Keong Tham & Ah Heng You & Seong Ling Yap & Abdul Kariem Bin Mohd Arof, 2022. "Capacity Sizing of Embedded Control Battery–Supercapacitor Hybrid Energy Storage System," Energies, MDPI, vol. 15(10), pages 1-14, May.
  18. Zhu, Wenhua H. & Tatarchuk, Bruce J., 2016. "Characterization of asymmetric ultracapacitors as hybrid pulse power devices for efficient energy storage and power delivery applications," Applied Energy, Elsevier, vol. 169(C), pages 460-468.
  19. Mohammadi, Kasra & Shamshirband, Shahaboddin & Yee, Por Lip & Petković, Dalibor & Zamani, Mazdak & Ch, Sudheer, 2015. "Predicting the wind power density based upon extreme learning machine," Energy, Elsevier, vol. 86(C), pages 232-239.
  20. Adrian Chmielewski & Jakub Możaryn & Piotr Piórkowski & Krzysztof Bogdziński, 2018. "Comparison of NARX and Dual Polarization Models for Estimation of the VRLA Battery Charging/Discharging Dynamics in Pulse Cycle," Energies, MDPI, vol. 11(11), pages 1-28, November.
  21. Ruijin Zhu & Weilin Guo & Xuejiao Gong, 2019. "Short-Term Load Forecasting for CCHP Systems Considering the Correlation between Heating, Gas and Electrical Loads Based on Deep Learning," Energies, MDPI, vol. 12(17), pages 1-18, August.
  22. Li, Jianwei & Yang, Qingqing & Robinson, Francis. & Liang, Fei & Zhang, Min & Yuan, Weijia, 2017. "Design and test of a new droop control algorithm for a SMES/battery hybrid energy storage system," Energy, Elsevier, vol. 118(C), pages 1110-1122.
  23. Muhammad Khalid, 2019. "A Review on the Selected Applications of Battery-Supercapacitor Hybrid Energy Storage Systems for Microgrids," Energies, MDPI, vol. 12(23), pages 1-34, November.
  24. Haris, Muhammad & Hasan, Muhammad Noman & Qin, Shiyin, 2021. "Early and robust remaining useful life prediction of supercapacitors using BOHB optimized Deep Belief Network," Applied Energy, Elsevier, vol. 286(C).
  25. Liyuan Shao & Yong Zhang & Xiujuan Zheng & Xin He & Yufeng Zheng & Zhiwei Liu, 2023. "A Review of Remaining Useful Life Prediction for Energy Storage Components Based on Stochastic Filtering Methods," Energies, MDPI, vol. 16(3), pages 1-22, February.
  26. Yang, YouLong & Che, JinXing & Li, YanYing & Zhao, YanJun & Zhu, SuLing, 2016. "An incremental electric load forecasting model based on support vector regression," Energy, Elsevier, vol. 113(C), pages 796-808.
  27. Fan, Feilong & Huang, Wentao & Tai, Nengling & Zheng, Xiaodong & Hu, Yan & Ma, Zhoujun, 2018. "A conditional depreciation balancing strategy for the equitable operation of extended hybrid energy storage systems," Applied Energy, Elsevier, vol. 228(C), pages 1937-1952.
  28. Wang, Jing & Kang, Lixia & Liu, Yongzhong, 2020. "Optimal scheduling for electric bus fleets based on dynamic programming approach by considering battery capacity fade," Renewable and Sustainable Energy Reviews, Elsevier, vol. 130(C).
  29. Duan, Jiandong & Fan, Shaogui & Wu, Fengjiang & Sun, Li & Wang, Guanglin, 2017. "Power balance control of micro gas turbine generation system based on supercapacitor energy storage," Energy, Elsevier, vol. 119(C), pages 442-452.
  30. Adrian Chmielewski & Piotr Piórkowski & Krzysztof Bogdziński & Jakub Możaryn, 2023. "Application of a Bidirectional DC/DC Converter to Control the Power Distribution in the Battery–Ultracapacitor System," Energies, MDPI, vol. 16(9), pages 1-40, April.
  31. Muhammad Muhitur Rahman & Syed Masiur Rahman & Md Shafiullah & Md Arif Hasan & Uneb Gazder & Abdullah Al Mamun & Umer Mansoor & Mohammad Tamim Kashifi & Omer Reshi & Md Arifuzzaman & Md Kamrul Islam &, 2022. "Energy Demand of the Road Transport Sector of Saudi Arabia—Application of a Causality-Based Machine Learning Model to Ensure Sustainable Environment," Sustainability, MDPI, vol. 14(23), pages 1-21, December.
IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.