Abstract
Development of various maximum power point tracking (MPPT) control techniques for proposed systems such as solar photo-voltaic (PV), wind turbine (WT), fuel cell (FC) and hybrid renewable energy system (HRES). HRES is the combination of PV, WT and FC which is connected parallelly by DC link. It is implemented in real-time using OPAL-RT system. In this research article, the MPPT algorithms viz. Perturb and Observe (P&O), Fuzzy Logic (FL), Artificial Neural Network and Adaptive Neuro-Fuzzy Inference System (ANFIS) have been analyzed and compared. Results have been carried out to record tracking performance of MPPT controllers by introducing changes in the radiation, wind speed hydrogen fuel rate. It has been observed that the proposed HRES using ANFIS-based MPPT controller provides better response as compared to other specified MPPT controllers.
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Algazar MM, Al-Monier H, El-Halim HA, Salem MEE (2012) Maximum power point tracking using fuzzy logic control. Electrical Power Energy Syst 39:21–28
Ali AN (2014) An ANFIS based advanced MPPT control of a wind-solar hybrid power generation system. Int Rev Modelling Simul 7(4):638–643
Entchev E, Yang L (2007) Application of adaptive neuro-fuzzy inference system techniques and artificial neural networks to predict solid oxide fuel cell performance in residential microgeneration installation. J Power Sources 170(1):122–129
Giraud F, Salameh ZM (2001) Steady-state performance of a grid-connected rooftop hybrid wind-photovoltaic power system with battery storage. IEEE Trans Energy Convers 16(1):1–7
Hasikos J, Sarimveis H, Zervas PL, Markatos NC (2009) Operational optimization and real-time control of fuel-cell systems. J Power Sources 193(1):258–268
Kamal E, Koutb M, Sobaih AA, Abozalam B (2010) An intelligent maximum power extraction algorithm for hybrid wind–diesel-storage system. Int J Electr Power Energy Syst 32(3):170–177
Karanjkar DS, Chatterji S, Kumar A, Shimi SL (2014) Fuzzy adaptive proportional-integral-derivative controller with dynamic set-point adjustment for maximum power point tracking in solar photovoltaic system. Syst Sci Control Eng An Open Access J 2(1):562–582
Karanjkar DS, Chatterji S, Shimi SL, Kumar, A. (2014, March). Real time simulation and analysis of maximum power point tracking (MPPT) techniques for solar photo-voltaic system. In IEEE conference on Recent Advances in Engineering and Computational Sciences (RAECS), pp. 1–6
Karanjkar DS, Chatterji S, Shimi SL, Kumar A (2014) Real time simulation and analysis of maximum power point tracking (MPPT) techniques for solar photo-voltaic system. In IEEE, Recent Advances Engineering and Computational Sciences (RAECS), Chandigarh, India (pp. 1–6)
Kewat S, Singh B, Hussain I (2018) Power management in PV-battery-hydro based standalone microgrid. IET Renew Power Gener 12(4):391–398
Khan MJ (2020) Review of recent trends in optimization techniques for hybrid renewable energy system. Arch Comput Methods Eng. https://doi.org/10.1007/s11831-020-09424-2
Khan MJ, Mathew L (2018) Comparative analysis of maximum power point tracking controller for wind energy system. Int J Electron 105(9):1535–1550
Khan MJ, Yadav AK, Mathew L (2017) Techno economic feasibility analysis of different combinations of PV-Wind-Diesel-Battery hybrid system for telecommunication applications in different cities of Punjab, India. Renew Sust Energy Rev 76:577–607
Leedy AW, Guo L, Aganah KA (2012) A constant voltage MPPT method for a solar powered boost converter with DC motor load. In Proceedings of IEEE Conference on South east con, (pp. 1–6)
Masoum MA, Dehbonei H, Fuchs EF (2002) Theoretical and experimental analyses of photovoltaic systems with voltageand current-based maximum power-point tracking. IEEE Trans Energy Convers 17(4):514–522
Meiqin M, Jianhui S, Chang L, Guorong Z, Yuzhu Z (2008) Controller for 1kW-5kW wind-solar hybrid generation systems. In IEEE Canadian Conference on Electrical and Computer Engineering (CCECE), (pp. 001175–001178)
Mousavi SM, Fathi SH, Riahy GH (2009) Energy management of wind/PV and battery hybrid system with consideration of memory effect in battery. In IEEE Conference on Clean Electrical Power, (pp. 630–633)
Pak L, Faruque MO, Nie X, Dinavahi V (2006) A versatile cluster-based real-time digital simulator for power engineering research. IEEE Trans Power Syst Powers 21(2):455–465
Rowe A, Li X (2001) Mathematical modeling of proton exchange membrane fuel cells. J Power Sources 102(1):82–96
Shankar K, Thangaraj M, Abudhahir A (2013). Performance analysis of MPPT algorithms for enhancing the efficiency of SPV power generation system: a simulation study. In IEEE Conference on Emerging Trends in VLSI, Embedded System, Nano Electronics and Telecommunication System (ICEVENT), (pp. 1–5)
Sharma MK, Soni SU (2016) Performance analysis of a standalone PV-Wind-diesel hybrid system using ANFIS based controller. Int J Comput Appl 147(13):18–23
Tudorache T, Kisck D, Rădulescu B, Popescu M (2012) Design and implementation of an autonomous Wind/PV/Diesel/Battery power system. In IEEE Conference on Optimization of Electrical and Electronic Equipment (OPTIM), (pp. 987–992)
Valenciaga F, Puleston PF (2005) Supervisor control for a stand-alone hybrid generation system using wind and photovoltaic energy. IEEE Trans Energy Convers 20(2):398–405
Yadav AK, Malik H, Arif MSB (2018) Techno economic feasibility analysis of different combination of PV–wind–diesel–battery hybrid system. In Hybrid-Renewable Energy Systems in Microgrids (pp. 203–218)
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Khan, M.J., Mathew, L. Artificial neural network-based maximum power point tracking controller for real-time hybrid renewable energy system. Soft Comput 25, 6557–6575 (2021). https://doi.org/10.1007/s00500-021-05653-0
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DOI: https://doi.org/10.1007/s00500-021-05653-0