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ANFIS-based modelling for photovoltaic power supply system: A case study

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  1. Qamar Navid & Ahmed Hassan & Abbas Ahmad Fardoun & Rashad Ramzan & Abdulrahman Alraeesi, 2021. "Fault Diagnostic Methodologies for Utility-Scale Photovoltaic Power Plants: A State of the Art Review," Sustainability, MDPI, vol. 13(4), pages 1-22, February.
  2. A. Bassam & O. May Tzuc & M. Escalante Soberanis & L. J. Ricalde & B. Cruz, 2017. "Temperature Estimation for Photovoltaic Array Using an Adaptive Neuro Fuzzy Inference System," Sustainability, MDPI, vol. 9(8), pages 1-16, August.
  3. Selimefendigil, Fatih & Öztop, Hakan F., 2020. "Identification of pulsating flow effects with CNT nanoparticles on the performance enhancements of thermoelectric generator (TEG) module in renewable energy applications," Renewable Energy, Elsevier, vol. 162(C), pages 1076-1086.
  4. Messalti, Sabir & Harrag, Abdelghani & Loukriz, Abdelhamid, 2017. "A new variable step size neural networks MPPT controller: Review, simulation and hardware implementation," Renewable and Sustainable Energy Reviews, Elsevier, vol. 68(P1), pages 221-233.
  5. Ceylin Şirin & Fatih Selimefendigil & Hakan Fehmi Öztop, 2023. "Performance Analysis and Identification of an Indirect Photovoltaic Thermal Dryer with Aluminum Oxide Nano-Embedded Thermal Energy Storage Modification," Sustainability, MDPI, vol. 15(3), pages 1-27, January.
  6. Zaher Mundher Yaseen & Mazen Ismaeel Ghareb & Isa Ebtehaj & Hossein Bonakdari & Ridwan Siddique & Salim Heddam & Ali A. Yusif & Ravinesh Deo, 2018. "Rainfall Pattern Forecasting Using Novel Hybrid Intelligent Model Based ANFIS-FFA," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 32(1), pages 105-122, January.
  7. Vineet Jain & Tilak Raj, 2018. "An adaptive neuro-fuzzy inference system for makespan estimation of flexible manufacturing system assembly shop: a case study," International Journal of System Assurance Engineering and Management, Springer;The Society for Reliability, Engineering Quality and Operations Management (SREQOM),India, and Division of Operation and Maintenance, Lulea University of Technology, Sweden, vol. 9(6), pages 1302-1314, December.
  8. Jun-Hyun Shin & Jin-O Kim, 2020. "On-Line Diagnosis and Fault State Classification Method of Photovoltaic Plant," Energies, MDPI, vol. 13(17), pages 1-12, September.
  9. Mellit, A. & Sağlam, S. & Kalogirou, S.A., 2013. "Artificial neural network-based model for estimating the produced power of a photovoltaic module," Renewable Energy, Elsevier, vol. 60(C), pages 71-78.
  10. Enany, Mohamed A. & Farahat, Mohamed A. & Nasr, Ahmed, 2016. "Modeling and evaluation of main maximum power point tracking algorithms for photovoltaics systems," Renewable and Sustainable Energy Reviews, Elsevier, vol. 58(C), pages 1578-1586.
  11. Sankara kumar, Sundarapandian & Karthick, Alagar & Shankar, R. & Dharmaraj, Ganeshaperumal, 2024. "Energy forecasting of the building integrated photovoltaic system based on deep learning dragonfly-firefly algorithm," Energy, Elsevier, vol. 308(C).
  12. Silvestre, Santiago & Kichou, Sofiane & Chouder, Aissa & Nofuentes, Gustavo & Karatepe, Engin, 2015. "Analysis of current and voltage indicators in grid connected PV (photovoltaic) systems working in faulty and partial shading conditions," Energy, Elsevier, vol. 86(C), pages 42-50.
  13. Kaloop, Mosbeh R. & Bardhan, Abidhan & Kardani, Navid & Samui, Pijush & Hu, Jong Wan & Ramzy, Ahmed, 2021. "Novel application of adaptive swarm intelligence techniques coupled with adaptive network-based fuzzy inference system in predicting photovoltaic power," Renewable and Sustainable Energy Reviews, Elsevier, vol. 148(C).
  14. Suganthi, L. & Iniyan, S. & Samuel, Anand A., 2015. "Applications of fuzzy logic in renewable energy systems – A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 48(C), pages 585-607.
  15. Selimefendigil, Fatih & Bayrak, Fatih & Oztop, Hakan F., 2018. "Experimental analysis and dynamic modeling of a photovoltaic module with porous fins," Renewable Energy, Elsevier, vol. 125(C), pages 193-205.
  16. Fatih Selimefendigil & Hakan F. Oztop & Ali J. Chamkha, 2021. "Jet Impingement Heat Transfer of Confined Single and Double Jets with Non-Newtonian Power Law Nanofluid under the Inclined Magnetic Field Effects for a Partly Curved Heated Wall," Sustainability, MDPI, vol. 13(9), pages 1-23, May.
  17. Arsalan Masood & Ubaid Ahmed & Syed Zulqadar Hassan & Ahsan Raza Khan & Anzar Mahmood, 2025. "Economic Value Creation of Artificial Intelligence in Supporting Variable Renewable Energy Resource Integration to Power Systems: A Systematic Review," Sustainability, MDPI, vol. 17(6), pages 1-42, March.
  18. Ridha, Hussein Mohammed & Gomes, Chandima & Hizam, Hashim & Ahmadipour, Masoud & Heidari, Ali Asghar & Chen, Huiling, 2021. "Multi-objective optimization and multi-criteria decision-making methods for optimal design of standalone photovoltaic system: A comprehensive review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 135(C).
  19. Dizqah, Arash M. & Maheri, Alireza & Busawon, Krishna, 2014. "An accurate method for the PV model identification based on a genetic algorithm and the interior-point method," Renewable Energy, Elsevier, vol. 72(C), pages 212-222.
  20. Mehrbakhsh Nilashi & Fausto Cavallaro & Abbas Mardani & Edmundas Kazimieras Zavadskas & Sarminah Samad & Othman Ibrahim, 2018. "Measuring Country Sustainability Performance Using Ensembles of Neuro-Fuzzy Technique," Sustainability, MDPI, vol. 10(8), pages 1-20, August.
  21. Jha, Sunil Kr. & Bilalovic, Jasmin & Jha, Anju & Patel, Nilesh & Zhang, Han, 2017. "Renewable energy: Present research and future scope of Artificial Intelligence," Renewable and Sustainable Energy Reviews, Elsevier, vol. 77(C), pages 297-317.
  22. Selimefendigil, Fatih & Öztop, Hakan F., 2021. "Thermoelectric generation in bifurcating channels and efficient modeling by using hybrid CFD and artificial neural networks," Renewable Energy, Elsevier, vol. 172(C), pages 582-598.
  23. Yea-Kuang Chan & Jyh-Cherng Gu, 2012. "Modeling of Turbine Cycles Using a Neuro-Fuzzy Based Approach to Predict Turbine-Generator Output for Nuclear Power Plants," Energies, MDPI, vol. 5(1), pages 1-18, January.
  24. Fernandez-Jimenez, L. Alfredo & Muñoz-Jimenez, Andrés & Falces, Alberto & Mendoza-Villena, Montserrat & Garcia-Garrido, Eduardo & Lara-Santillan, Pedro M. & Zorzano-Alba, Enrique & Zorzano-Santamaria,, 2012. "Short-term power forecasting system for photovoltaic plants," Renewable Energy, Elsevier, vol. 44(C), pages 311-317.
  25. repec:plo:pone00:0173966 is not listed on IDEAS
  26. Zendehboudi, Sohrab & Rezaei, Nima & Lohi, Ali, 2018. "Applications of hybrid models in chemical, petroleum, and energy systems: A systematic review," Applied Energy, Elsevier, vol. 228(C), pages 2539-2566.
  27. Yaïci, Wahiba & Entchev, Evgueniy, 2016. "Adaptive Neuro-Fuzzy Inference System modelling for performance prediction of solar thermal energy system," Renewable Energy, Elsevier, vol. 86(C), pages 302-315.
  28. Yang, L. & Entchev, E., 2014. "Performance prediction of a hybrid microgeneration system using Adaptive Neuro-Fuzzy Inference System (ANFIS) technique," Applied Energy, Elsevier, vol. 134(C), pages 197-203.
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