Boosting Energy for Building-Integrated Photovoltaic Cells using Novel Boost Converter with Voltage Multiplier Cell and ANN-MPPT
DOI:
https://doi.org/10.18196/jrc.v6i5.26854Keywords:
Photovoltaic (PV) Systems, Maximum Power Point Tracking (MPPT), Artificial Neural Network (ANN), Advance Boost Converter, Boost Voltage Multiplier Stage (VMS) ConverterAbstract
This study investigates optimizing photovoltaic (PV) energy delivery to building lighting loads by proposing a novel boost converter with a voltage multiplier stage (VMS) and an intelligent maximum power point tracking (MPPT) system. The research contribution is the design and comparative analysis of this advanced converter topology against a traditional boost converter to demonstrate enhanced performance under diverse operating conditions. The methodology involves simulating the PV system under four distinct scenarios including variations in load resistance, desired output voltage, and dynamic solar irradiance. The performance of three MPPT algorithms namely artificial neural network (ANN), particle swarm optimization (PSO), and perturb and observe (P&O), was evaluated to identify the most effective control strategy. The results by using MATLAB/Simulink show that the proposed boost VMS converter consistently outperforms the traditional boost converter by exhibiting improved power extraction and enhanced stability in output voltage and current. For example in a scenario with a 50 V output and 1000 W/m² irradiance the boost VMS converter achieved a more stable output power of approximately (961.52W) compared to (941.543W) from the traditional converter. Furthermore the ANN-based MPPT demonstrated superior stability and power tracking accuracy especially under dynamic irradiance conditions, where it maintained a stable output while PSO and P&O experienced significant power drops. Integrating the boost VMS converter with an ANN-based MPPT provides a superior, robust solution for optimizing PV energy utilization in building lighting applications, ensuring efficient and stable power delivery under fluctuating environmental and load conditions.
References
F. Rosa, “Building-integrated photovoltaics (BIPV) in historical buildings: opportunities and constraints,” Energies, vol. 13, no. 14, p. 3628, 2020.
T. E. Kuhn, C. Erban, M. Heinrich, J. Eisenlohr, F. Ensslen, and D. H. Neuhaus, “Review of technological design options for building integrated photovoltaics (BIPV),” Energy and Buildings, vol. 231, p. 110381, 2021, doi: 10.1016/j.enbuild.2020.110381.
A. El Hammoumi, S. Chtita, S. Motahhir, and A. El Ghzizal, “Solar PV energy: From material to use, and the most commonly used techniques to maximize the power output of PV systems: A focus on solar trackers and floating solar panels,” Energy Reports, vol. 8, pp. 11992–12010, 2022, doi: 10.1016/j.egyr.2022.09.054.
A. Aslam, N. Ahmed, S. A. Qureshi, M. Assadi, and N. Ahmed, “Advances in Solar PV Systems; A Comprehensive Review of PV Performance, Influencing Factors, and Mitigation Techniques,” Energies, vol. 15, no. 20, p. 7595, Oct. 2022, doi: 10.3390/en15207595.
K. Hasan, S. B. Yousuf, M. S. H. K. Tushar, B. K. Das, P. Das, and M. S. Islam, “Effects of different environmental and operational factors on the PV performance: A comprehensive review,” Energy Science and Engineering, vol. 10, no. 2, pp. 656–675, 2022, doi: 10.1002/ese3.1043.
D. S. Shanan and S. K. Kadhim, “Comparative Analysis of Airflow Regulation in Ventilator Systems Using Various Control Strategies,” Journal Europeen des Systemes Automatises, vol. 56, no. 5, pp. 811–821, 2023, doi: 10.18280/jesa.560512.
S. Gorjian, R. Singh, A. Shukla, and A. R. Mazhar, “On-farm applications of solar PV systems,” in Photovoltaic Solar Energy Conversion: Technologies, Applications and Environmental Impacts, pp. 147–190, 2020, doi: 10.1016/B978-0-12-819610-6.00006-5.
R. Khilar et al., “Improving the Efficiency of Photovoltaic Panels Using Machine Learning Approach,” International Journal of Photoenergy, vol. 2022, 2022, doi: 10.1155/2022/4921153.
K. R. Hameed, A. L. Suraiji, and A. O. Hanfesh, “Comparative the effect of distribution transformer coil shape on electromagnetic forces and their distribution using the FEM,” Open Engineering, vol. 13, no. 1, 2023, doi: 10.1515/eng-2022-0503.
A. Narendra, N. Venkataramana Naik, A. K. Panda, and N. Tiwary, “A Comprehensive Review of PV Driven Electrical Motors,” Solar Energy, vol. 195, pp. 278–303, 2020, doi: 10.1016/j.solener.2019.09.078.
D. Sheltag and S. K. Kadhim, “Enhancing Artificial Ventilator Systems: A Comparative Analysis of Traditional and Nonlinear PID Controllers,” Mathematical Modelling of Engineering Problems, vol. 11, no. 3, pp. 599–610, 2024, doi: 10.18280/mmep.110303.
E. Hegazy, W. Saad, and M. Shokair, “Studying the Effect of Using a Low Power PV and DC-DC Boost Converter on the Performance of the Solar Energy PV System,” Proceedings of ICCES 2020 - 2020 15th International Conference on Computer Engineering and Systems, pp. 1-8, 2020, doi: 10.1109/ICCES51560.2020.9334581.
L. J. Jeremy, C. A. Ooi, and J. Teh, “Non-isolated conventional DC-DC converter comparison for a photovoltaic system: A review,” Journal of Renewable and Sustainable Energy, vol. 12, no. 1, 2020, doi: 10.1063/1.5095811.
T. W. Hariyadi and A. Adriansyah, “Comparison of DC-DC Converters Boost Type in Optimizing the Use of Solar Panels,” 2020 2nd International Conference on Broadband Communications, Wireless Sensors and Powering, BCWSP 2020, pp. 189–194, 2020, doi: 10.1109/BCWSP50066.2020.9249464.
M. S. Simoiu, V. Calofir, S. S. Iliescu, I. Fagarasan, and N. Arghira, “BOOST converter modelling as a subsystem of a photovoltaic panel control system,” 2020 22nd IEEE International Conference on Automation, Quality and Testing, Robotics - THETA, AQTR 2020 - Proceedings, pp. 1-6, 2020, doi: 10.1109/AQTR49680.2020.9129963.
J. López Seguel, S. I. Seleme, and L. M. F. Morais, “Comparison of the performance of MPPT methods applied in converters buck and buck-boost for autonomous photovoltaic systems,” Ingeniare, vol. 29, no. 2, pp. 229–244, 2021, doi: 10.4067/S0718-33052021000200229.
I. Achmad and Anggara Trisna Nugraha, “Implementation of Voltage Stabilizers on Solar Cell System Using Buck-Boost Converter,” in Journal of Electronics, Electromedical Engineering, and Medical Informatics, vol. 4, no. 3, pp. 154–160, 2022, doi: 10.35882/jeeemi.v4i3.246.
A. J. O. Hanfesh, J. Mohammed, I. Salman, H. Mohammed, and M. Ali, “Design and implementation of a solar tracking system using a hydraulic system,” AIP Conference Proceedings, vol. 3002, no. 1, 2024, doi: 10.1063/5.0205799.
A. Baimyshev, A. Zhakatayev, and H. A. Varol, “Augmenting variable stiffness actuation using reaction wheels,” IEEE Access, vol. 4, pp. 4618–4628, 2016, doi: 10.1109/ACCESS.2016.2602704.
S. Motahhir, A. El Hammoumi, and A. El Ghzizal, “The most used MPPT algorithms: Review and the suitable low-cost embedded board for each algorithm,” Journal of Cleaner Production, vol. 246, 2020, doi: 10.1016/j.jclepro.2019.118983.
R. B. Bollipo, S. Mikkili, and P. K. Bonthagorla, “Critical Review on PV MPPT Techniques: Classical, Intelligent and Optimisation,” IET Renewable Power Generation, vol. 14, no. 9, pp. 1433–1452, 2020, doi: 10.1049/iet-rpg.2019.1163.
M. L. Katche, A. B. Makokha, S. O. Zachary, and M. S. Adaramola, “A Comprehensive Review of Maximum Power Point Tracking (MPPT) Techniques Used in Solar PV Systems,” Energies, vol. 16, no. 5, 2023, doi: 10.3390/en16052206.
S. Bhattacharyya, D. S. Kumar P, S. Samanta, and S. Mishra, “Steady output and fast tracking MPPT (SOFT-MPPT) for P&O and InC algorithms,” IEEE Transactions on Sustainable Energy, vol. 12, no. 1, pp. 293–302, 2021, doi: 10.1109/TSTE.2020.2991768.
P. T. Szemes and M. Melhem, “Analyzing and modeling PV with ‘P&O’ MPPT Algorithm by MATLAB/Simulink,” 2020 3rd International Symposium on Small-Scale Intelligent Manufacturing Systems, SIMS 2020, pp. 1-6, 2020, doi: 10.1109/SIMS49386.2020.9121579.
N. F. Ibrahim et al., “A new adaptive MPPT technique using an improved INC algorithm supported by fuzzy self-tuning controller for a grid-linked photovoltaic system,” PLoS ONE, vol. 18, no. 11, pp. 1–22, 2023, doi: 10.1371/journal.pone.0293613.
M. Jain, V. Saihjpal, N. Singh, and S. B. Singh, “An Overview of Variants and Advancements of PSO Algorithm,” Applied Sciences (Switzerland), vol. 12, no. 17, pp. 1–21, 2022, doi: 10.3390/app12178392.
M. Periasamy, T. Kaliannan, S. Selvaraj, V. Manickam, S. A. Joseph, and J. R. Albert, “Various PSO methods investigation in renewable and nonrenewable sources,” International Journal of Power Electronics and Drive Systems, vol. 13, no. 4, pp. 2498–2505, 2022, doi: 10.11591/ijpeds.v13.i4.pp2498-2505.
S. R. Revathy et al., “Design and Analysis of ANFIS - Based MPPT Method for Solar Photovoltaic Applications,” International Journal of Photoenergy, vol. 2022, 2022, doi: 10.1155/2022/9625564.
M. R. Javed, A. Waleed, U. S. Virk, and S. Z. Ul Hassan, “Comparison of the Adaptive Neural-Fuzzy Interface System (ANFIS) based Solar Maximum Power Point Tracking (MPPT) with other Solar MPPT Methods,” Proceedings - 2020 23rd IEEE International Multi-Topic Conference, INMIC 2020, pp. 1-5, 2020, doi: 10.1109/INMIC50486.2020.9318178.
C. G. Villegas-Mier, J. Rodriguez-Resendiz, J. M. Álvarez-Alvarado, H. Rodriguez-Resendiz, A. M. Herrera-Navarro, and O. Rodríguez-Abreo, “Artificial neural networks in mppt algorithms for optimization of photovoltaic power systems: A review,” Micromachines, vol. 12, no. 10, pp. 1–19, 2021, doi: 10.3390/mi12101260.
A. Gündoğdu and R. Çelikel, “ANN-Based MPPT Algorithm for Photovoltaic Systems,” Turkish Journal of Science & Technology, vol. 15, no. 2, pp. 101–110, 2020.
M. N. Ali, K. Mahmoud, M. Lehtonen, and M. M. F. Darwish, “Promising mppt methods combining metaheuristic, fuzzy-logic and ann techniques for grid-connected photovoltaic,” Sensors (Switzerland), vol. 21, no. 4, pp. 1–18, 2021, doi: 10.3390/s21041244.
S. A. Sarang et al., “Maximizing solar power generation through conventional and digital MPPT techniques: a comparative analysis,” Scientific Reports, vol. 14, no. 1, pp. 1–18, 2024, doi: 10.1038/s41598-024-59776-z.
R. J. Yang et al., “Digitalizing building integrated photovoltaic (BIPV) conceptual design: A framework and an example platform,” Building and Environment, vol. 243, p. 110675, 2023, doi: 10.1016/j.buildenv.2023.110675.
McKinsey, “Quantum Computing: Potential and Challenges ahead,” Plain concepts, 2024, https://www.plainconcepts.com/quantum-computing-potential-challenges/.
A. A. Jadallah, A. O. Hanfesh, and T. H. Jebur, “Design, fabrication, testing and simulation of a modern glass to glass photovoltaic module in Iraq,” Journal of Engineering Science and Technology, vol. 13, no. 9, pp. 2750–2764, 2018.
M. Albaker Najm abed, A. Abdul Razzaq Altahir, and A. Abdulhadi ِAl-Moadhen, “A Review of Hybrid Electric Vehicle Configurations: Advances and Challenges,” Kerbala Journal for Engineering Sciences, vol. 4, no. 3, pp. 259–282, 2024, doi: 10.63463/kjes1155.
I. Kaaya et al., “A physics-based framework for modelling the performance and reliability of BIPV systems,” Solar Energy, vol. 277, p. 112730, 2024, doi: 10.1016/j.solener.2024.112730.
D. Sarkar, A. Kumar, and P. K. Sadhu, “A Survey on Development and Recent Trends of Renewable Energy Generation from BIPV Systems,” IETE Technical Review (Institution of Electronics and Telecommunication Engineers, India), vol. 37, no. 3, pp. 258–280, 2020, doi: 10.1080/02564602.2019.1598294.
Z. Liu et al., “A comprehensive study of feasibility and applicability of building integrated photovoltaic (BIPV) systems in regions with high solar irradiance,” Journal of Cleaner Production, vol. 307, p. 127240, 2021, doi: 10.1016/j.jclepro.2021.127240.
K. Ishaque, Z. Salam, and H. Taheri, “Accurate MATLAB simulink PV system simulator based on a two-diode model,” Journal of Power Electronics, vol. 11, no. 2, pp. 179–187, 2011, doi: 10.6113/JPE.2011.11.2.179.
V. Stornelli, M. Muttillo, T. de Rubeis, and I. Nardi, “A new simplified five-parameter estimation method for single-diode model of photovoltaic panels,” Energies, vol. 12, no. 22, 2019, doi: 10.3390/en12224271.
M. A. Najm Abed, A. Abdul Razzaq Altahir, A. O. Hanfesh, and A. A. Ahmed, “Performance Evaluation of PMSM and BLDC Motors in Different Operating Scenarios Based Slide Mode Control,” 2024 4th International Conference on Electrical Machines and Drives, ICEMD 2024, pp. 24–25, 2024, doi: 10.1109/ICEMD64575.2024.10963593.
I. A. R. Hameed, A. A. R. Altahir, and H. S. Hameed, “An investigation of solar PV systems coupled with diesel generators: Opportunities and challenges,” in AIP Conference Proceedings, vol. 2631, 2023, doi: 10.1063/5.0133658.
A. Pradhan and B. Panda, “A simplified design and modeling of boost converter for photovoltaic sytem,” International Journal of Electrical and Computer Engineering, vol. 8, no. 1, pp. 141–149, 2018, doi: 10.11591/ijece.v8i1.pp141-149.
M. N. Huynh, H. N. Duong, and V. H. Nguyen, “A Passivity-based Control Combined with Sliding Mode Control for a DC-DC Boost Power Converter,” Journal of Robotics and Control (JRC), vol. 4, no. 6, pp. 780–790, 2023, doi: 10.18196/jrc.v4i6.20071.
D. Yan et al., "Review of general modeling approaches of power converters," in Chinese Journal of Electrical Engineering, vol. 7, no. 1, pp. 27-36, March 2021, doi: 10.23919/CJEE.2021.000002.
M. F. Guepfrih, G. Waltrich, and T. B. Lazzarin, “High Step-Up DC-DC Converter Using Built-In Transformer Voltage Multiplier Cell and Dual Boost Concepts,” IEEE Journal of Emerging and Selected Topics in Power Electronics, vol. 9, no. 6, pp. 6700–6712, 2021, doi: 10.1109/JESTPE.2021.3063060.
M. Meraj, M. S. Bhaskar, A. Iqbal, N. Al-Emadi, and S. Rahman, “Interleaved Multilevel Boost Converter with Minimal Voltage Multiplier Components for High-Voltage Step-Up Applications,” IEEE Transactions on Power Electronics, vol. 35, no. 12, pp. 12816–12833, 2020, doi: 10.1109/TPEL.2020.2992602.
M. Rezaie and V. Abbasi, “Ultrahigh Step-Up DC-DC Converter Composed of Two Stages Boost Converter, Coupled Inductor, and Multiplier Cell,” IEEE Transactions on Industrial Electronics, vol. 69, no. 6, pp. 5867–5878, 2022, doi: 10.1109/TIE.2021.3091916.
R. Saravanan and N. Jaya, “Multistage Boost Converter with Modified Voltage Multiplier for Contemporary Applications,” Journal of Electrical Engineering and Technology, vol. 19, no. 7, pp. 4323–4333, 2024, doi: 10.1007/s42835-024-01857-0.
X. Fan, H. Sun, Z. Yuan, Z. Li, R. Shi, and N. Ghadimi, “High Voltage Gain DC/DC Converter Using Coupled Inductor and VM Techniques,” IEEE Access, vol. 8, pp. 131975–131987, 2020, doi: 10.1109/ACCESS.2020.3002902.
T. Sutikno, A. S. Samosir, R. A. Aprilianto, H. S. Purnama, W. Arsadiando, and S. Padmanaban, “Advanced DC-DC converter topologies for solar energy harvesting applications: A review,” Clean Energy, vol. 7, no. 3, pp. 555–570, 2023, doi: 10.1093/ce/zkad003.
S. Shao et al., “Modeling and Advanced Control of Dual-Active-Bridge DC-DC Converters: A Review,” IEEE Transactions on Power Electronics, vol. 37, no. 2, pp. 1524–1547, 2022, doi: 10.1109/TPEL.2021.3108157.
Q. Xu, N. Vafamand, L. Chen, T. Dragicevic, L. Xie, and F. Blaabjerg, “Review on Advanced Control Technologies for Bidirectional DC/DC Converters in DC Microgrids,” IEEE Journal of Emerging and Selected Topics in Power Electronics, vol. 9, no. 2, pp. 1205–1221, 2021, doi: 10.1109/JESTPE.2020.2978064.
I. N. Issa, A. A. R. Altahir, and F. M. Tuaimah, “Choosing PSO under Different Overloads to Provide Best Power Flow for IEEE - 57 Bus,” Al-Iraqia Journal for Scientific Engineering Research, vol. 2, no. 3, pp. 64–73, 2023, doi: 10.58564/ijser.2.3.2023.88.
P. Mohseni, S. Mohammadsalehian, M. R. Islam, K. M. Muttaqi, D. Sutanto, and P. Alavi, “Ultrahigh Voltage Gain DC-DC Boost Converter with ZVS Switching Realization and Coupled Inductor Extendable Voltage Multiplier Cell Techniques,” IEEE Transactions on Industrial Electronics, vol. 69, no. 1, pp. 323–335, 2022, doi: 10.1109/TIE.2021.3050385.
A. Wong, D. Rexachs, and E. Luque, “Parallel Application Signature for Performance Analysis and Prediction,” IEEE Transactions on Parallel and Distributed Systems, vol. 26, no. 7, pp. 2009–2019, 2015, doi: 10.1109/TPDS.2014.2329688.
N. J. Hadi and A. A. R. A.- Tahir, “Study Of Thermal Solar Energy Storage Using Stationary Batterirs and Melting Salts Technique,” Repository of Open Acces Papers, no. 2, 2006.
Q. A. Mahdi et al., “Development of Estimation and Forecasting Method in Intelligent Decision Support Systems,” Eastern-European Journal of Enterprise Technologies, vol. 3, pp. 51–62, 2021, doi: 10.15587/1729-4061.2021.232718.
B. Zhu, S. Hu, G. Liu, Y. Huang, and X. She, “Low-Voltage Stress Buck-Boost Converter with a High-Voltage Conversion Gain,” IEEE Access, vol. 8, pp. 95188–95196, 2020, doi: 10.1109/ACCESS.2020.2995889.
A. M. S. S. Andrade, E. Mattos, L. Schuch, H. L. Hey, and M. L. Da Silva Martins, “Synthesis and Comparative Analysis of Very High Step-Up DC-DC Converters Adopting Coupled-Inductor and Voltage Multiplier Cells,” IEEE Transactions on Power Electronics, vol. 33, no. 7, pp. 5880–5897, 2018, doi: 10.1109/TPEL.2017.2742900.
N. Ncir and N. El Akchioui, “An advanced intelligent MPPT control strategy based on the imperialist competitive algorithm and artificial neural networks,” Evolutionary Intelligence, vol. 17, no. 3, pp. 1437–1461, 2024, doi: 10.1007/s12065-023-00838-y.
R. B. Bollipo, S. Mikkili, and P. K. Bonthagorla, “Critical Review on PV MPPT Techniques: Classical, Intelligent and Optimisation,” IET Renewable Power Generation, vol. 14, no. 9, pp. 1433–1452, 2020, doi: 10.1049/iet-rpg.2019.1163.
M. Fathi and J. A. Parian, “Intelligent MPPT for photovoltaic panels using a novel fuzzy logic and artificial neural networks based on evolutionary algorithms,” Energy Reports, vol. 7, pp. 1338–1348, 2021, doi: 10.1016/j.egyr.2021.02.051.
R. B. Bollipo, S. Mikkili, and P. K. Bonthagorla, “Hybrid, optimal, intelligent and classical PV MPPT techniques: A review,” CSEE Journal of Power and Energy Systems, vol. 7, no. 1, pp. 9–33, 2021, doi: 10.17775/CSEEJPES.2019.02720.
K. Y. Yap, C. R. Sarimuthu, and J. M. Y. Lim, “Artificial Intelligence Based MPPT Techniques for Solar Power System: A review,” Journal of Modern Power Systems and Clean Energy, vol. 8, no. 6, pp. 1043–1059, 2020, doi: 10.35833/MPCE.2020.000159.
N. S. Abu, W. M. Bukhari, M. H. Adli, H. Maghfiroh, and A. Ma’arif, “Advancements, Challenges and Safety Implications of AI in Autonomous Vehicles: A Comparative Analysis of Urban vs. Highway Environments,” Journal of Robotics and Control (JRC), vol. 5, no. 3, pp. 613–635, 2024, doi: 10.18196/jrc.v5i3.21114.
A. S. T. Hussain et al., “Unlocking Solar Potential: Advancements in Automated Solar Tracking Systems for Enhanced Energy Utilization,” Journal of Robotics and Control (JRC), vol. 5, no. 4, pp. 1018–1027, 2024, doi: 10.18196/jrc.v5i4.19931.
A. Saleh, K. S. F. Azmi, T. Hardianto, and W. Hadi, “Comparison of MPPT fuzzy logic controller based on perturb and observe (P&O) and incremental conductance (InC) algorithm on buck-boost converter,” in Proceedings - 2018 2nd International Conference on Electrical Engineering and Informatics: Toward the Most Efficient Way of Making and Dealing with Future Electrical Power System and Big Data Analysis, ICon EEI 2018, pp. 154–158, 2018, doi: 10.1109/ICon-EEI.2018.8784324.
O. N. Rajab Al-Jaboury, Z. Hamodat, and R. W. Daoud, “Design of Power Control Circuit for Grid-Connected PV System-Based Neural Network,” Journal of Robotics and Control (JRC), vol. 5, no. 3, pp. 821–828, 2024, doi: 10.18196/jrc.v5i3.20751.
A. P. Yoganandini and G. S. Anitha, “A modified particle swarm optimization algorithm to enhance MPPT in the PV array,” International Journal of Electrical and Computer Engineering, vol. 10, no. 5, pp. 5001–5008, 2020, doi: 10.11591/IJECE.V10I5.PP5001-5008.
Q. A. Mahdi et al., “Development of a Method for Training Artificial Neural Networks for Intelligent Decision Support Systems,” Eastern-European Journal of Enterprise Technologies, vol. 1, no. 9–115, pp. 35–44, 2022, doi: 10.15587/1729-4061.2022.251637.
S. Abboud et al., “Optimizing Solar Energy Production in Partially Shaded PV Systems with PSO-INC Hybrid Control,” Journal of Robotics and Control (JRC), vol. 5, no. 2, pp. 312–320, 2024, doi: 10.18196/jrc.v5i2.20896.
A. A. Mutlag, M. K. Abd, and S. W. Shneen, “Power Management and Voltage Regulation in DC Microgrid with Solar Panels and Battery Storage System,” Journal of Robotics and Control (JRC), vol. 5, no. 2, pp. 397–407, 2024, doi: 10.18196/jrc.v5i2.20581.
S. W. Shneen, M. K. Abd, and A. A. Mutlag, “Voltage Regulation and Power Management of DC Microgrid with Photovoltaic/Battery Storage System Using Flatness Control Method,” Journal of Robotics and Control (JRC), vol. 5, no. 6, pp. 1664–1672, 2024, doi: 10.18196/jrc.v5i6.22530.
M. Q. Yu, “Parameter Identification of Photovoltaic Cell Model Based on Perturbation and Observation and Modified Gauss-Newton Method,” in Chinese Control Conference, CCC, pp. 6127–6131, 2018, doi: 10.23919/ChiCC.2018.8483101.
K. Amara et al., “Improved Performance of a PV Solar Panel with Adaptive Neuro Fuzzy Inference System ANFIS based MPPT,” in 7th International IEEE Conference on Renewable Energy Research and Applications, ICRERA 2018, pp. 1098–1101, 2018, doi: 10.1109/ICRERA.2018.8566818.
A. S. Mahdi, A. K. Mahamad, S. Saon, T. Tuwoso, H. Elmunsyah, and S. W. Mudjanarko, “Maximum power point tracking using perturb and observe, fuzzy logic and ANFIS,” SN Applied Sciences, vol. 2, no. 1, p. 89, 2020, doi: 10.1007/s42452-019-1886-1.
K. H. Tajaldin and H. J. Motlak, “Enhancement of DC-DC Luo Converter Using Adaptive PI MPPT and P&O MPPT for Photovoltaic System,” Journal Europeen des Systemes Automatises, vol. 57, no. 3, pp. 921–933, 2024, doi: 10.18280/jesa.570330.
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