(1) Department of Electrical Engineering, College of Engineering, Prince Sattam Bin Abdulaziz University, Al-Kharj 11942, Saudi Arabia. 2) Department of Electrical Power and Machines Engineering, Faculty of Engineering, Helwan University, Helwan 11795, Egypt)*corresponding author
AbstractOne of the most important and desirable options for moving toward clean electric energy sources is solar energy. Therefore, a PV system's characteristics play a significant role in determining how effective it is across a range of temperature and radiation scenarios. One can consider the PV model's parameter estimation to be a nonlinear optimization situation. This work makes use of a novel application of the smell agent optimizer (SAO) created to forecast the undefined parameters of the PV model's single- and two-diode equivalent circuits. The goal of this effort is to create an accurate photovoltaic model that can accurately represent its performance under variable operating conditions. The square of the mean squared error between the actual measured curve and the current-voltage curve derived from the model defines the intended objective function. The suggested system is constructed and tested experimentally in a range of temperature and light conditions. Next, the MATLAB software is used to create the simulated PV model integrated with the SAO. The PV parameters are then predicted by comparing the experimental data with the convergence of the SAO based on the PV model. Based on the observed properties, the suggested approach for determining the parameters of an actual solar cell has been put into practice and contrasted with eight other optimization techniques. The outstanding efficacy of the method utilized compared with alternate methods is demonstrated by the statistical comparison of the ideal objective function resulting from the difference in the current-voltage curve produced from the optimized circuit model and the measurement.
KeywordsNonlinear Optimization; Single-Diode PV Model; Two-Diode PV Model; MATLAB Simulation; Green Energy
|
DOIhttps://doi.org/10.31763/ijrcs.v4i3.1490 |
Article metrics10.31763/ijrcs.v4i3.1490 Abstract views : 379 | PDF views : 174 |
Cite |
Full Text Download
|
References
[1] M. Awad et al., “A review of water electrolysis for green hydrogen generation considering PV/wind/hybrid/hydropower/geothermal/tidal and wave/biogas energy systems, economic analysis, and its application,†Alexandria Engineering Journal, vol. 87, pp. 213–239, 2024, https://doi.org/10.1016/j.aej.2023.12.032.
[2] M. M. Mahmoud, “Improved current control loops in wind side converter with the support of wild horse optimizer for enhancing the dynamic performance of PMSG-based wind generation system,†International Journal of Modelling and Simulation, vol. 43, no. 6, pp. 952-966, 2023, https://doi.org/10.1080/02286203.2022.2139128.
[3] O. M. Lamine et al., “A Combination of INC and Fuzzy Logic-Based Variable Step Size for Enhancing MPPT of PV Systems,†International Journal of Robotics and Control Systems, vol. 4, no. 2, pp. 877-892, 2024, https://doi.org/10.31763/ijrcs.v4i2.1428.
[4] R. Kassem et al., “A Techno-Economic-Environmental Feasibility Study of Residential Solar Photovoltaic / Biomass Power Generation for Rural Electrification : A Real Case Study,†Sustainability, vol. 16, no. 5, p. 2036, 2024, https://doi.org/10.3390/su16052036.
[5] R. Benkercha, S. Moulahoum, and B. Taghezouit, “Extraction of the PV modules parameters with MPP estimation using the modified flower algorithm,†Renewable Energy, vol. 143, pp. 1698-1709, 2019, https://doi.org/10.1016/j.renene.2019.05.107.
[6] 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, p. e0293613, 2023, https://doi.org/10.1371/journal.pone.0293613.
[7] A. A. Tarabsheh, M. Akmal, and M. Ghazal, “Series connected photovoltaic cells-Modelling and analysis,†Sustainability, vol. 9, no. 3, p. 371, 2017, https://doi.org/10.3390/su9030371.
[8] V. P. Gantasala, “Solar augmentation of power plants in the UAE,†Applied Solar Energy, vol. 52, pp. 271-277, 2016, https://doi.org/10.3103/S0003701X16040095.
[9] S. H. Hakmi, “Applications of Multi-Objective OPF Solutions with Optimal Placement of Multiple and Multi-Type FACTS Units to IEEE System: Comparison of Different Approaches,†International Journal of Robotics and Control Systems, vol. 4, no. 3, pp. 1075-1091, 2024, https://doi.org/10.31763/ijrcs.v4i3.1472
[10] B. S. Atia et al., “Applications of Kepler Algorithm-Based Controller for DC Chopper: Towards Stabilizing Wind Driven PMSGs under Nonstandard Voltages,†Sustainability, vol. 16, no. 7, p. 2952, 2024, https://doi.org/10.3390/su16072952.
[11] W. Yang, R. R. Prabhakar, J. Tan, S. D. Tilley, and J. Moon, “Strategies for enhancing the photocurrent, photovoltage, and stability of photoelectrodes for photoelectrochemical water splitting,†Chemical Society Reviews, vol. 48, no. 19, pp. 4979-5015, 2019, https://doi.org/10.1039/C8CS00997J.
[12] F. Menzri, T. Boutabba, I. Benlaloui, H. Bawayan, M. I. Mosaad, and M. M. Mahmoud, “Applications of hybrid SMC and FLC for augmentation of MPPT method in a wind-PV-battery configuration,†Wind Engineering, 2024, https://doi.org/10.1177/0309524X241254364.
[13] N. F. Ibrahim et al., “Operation of Grid-Connected PV System With ANN-Based MPPT and an Optimized LCL Filter Using GRG Algorithm for Enhanced Power Quality,†IEEE Access, vol. 11, pp. 106859-106876, 2023, https://doi.org/10.1109/ACCESS.2023.3317980.
[14] N. F. Ibrahim et al., “Multiport Converter Utility Interface with a High-Frequency Link for Interfacing Clean Energy Sources (PVWindFuel Cell) and Battery to the Power System: Application of the HHA Algorithm,†Sustainability, vol. 15, no. 18, p. 13716, 2023, https://doi.org/10.3390/su151813716.
[15] A. H. Elmetwaly et al., “Modeling, Simulation, and Experimental Validation of a Novel MPPT for Hybrid Renewable Sources Integrated with UPQC: An Application of Jellyfish Search Optimizer,†Sustainability, vol. 15, no. 6, p. 5209, 2023, https://doi.org/10.3390/su15065209.
[16] O. M. Kamel, A. A. Z. Diab, M. M. Mahmoud, A. S. Al-Sumaiti, and H. M. Sultan, “Performance Enhancement of an Islanded Microgrid with the Support of Electrical Vehicle and STATCOM Systems,†Energies, vol. 16, no. 4, p. 1577, 2023, https://doi.org/10.3390/en16041577.
[17] A. Gholami, M. Ameri, M. Zandi, and R. Gavagsaz Ghoachani, “A single-diode model for photovoltaic panels in variable environmental conditions: Investigating dust impacts with experimental evaluation,†Sustainable Energy Technologies and Assessments, vol. 47, p. 101392, 2021, https://doi.org/10.1016/j.seta.2021.101392.
[18] A. K. Podder, K. Ahmed, N. K. Roy and M. Habibullah, “Design and Simulation of a Photovoltaic and Fuel Cell Based Micro-grid System,†2019 International Conference on Energy and Power Engineering (ICEPE), pp. 1-6, 2019, https://doi.org/10.1109/CEPE.2019.8726694.
[19] A. Gholami, M. Ameri, M. Zandi, R. Gavagsaz Ghoachani, and M. Gholami, “A fast and precise double-diode model for predicting photovoltaic panel electrical behavior in variable environmental conditions,†International Journal of Ambient Energy, vol. 44, no. 1, pp. 1298-1315, 2023, https://doi.org/10.1080/01430750.2023.2173290.
[20] M. Khursheed et al., “Review of Flower Pollination Algorithm: Applications and Variants,†2020 International Conference on Engineering and Emerging Technologies (ICEET), pp. 1-6, 2020, https://doi.org/10.1109/ICEET48479.2020.9048215.
[21] M. Dashtdar and M. Dashtdar, “Voltage-Frequency Control (v-f) of Islanded Microgrid Based on Battery and MPPT Control,†American Journal of Electrical and Computer Engineering, vol. 4, no. 2, pp. 35-48, 2020, https://doi.org/10.11648/j.ajece.20200402.12.
[22] J. P. Ram, T. S. Babu, T. Dragicevic, and N. Rajasekar, “A new hybrid bee pollinator flower pollination algorithm for solar PV parameter estimation,†Energy Conversion and Management, vol. 135, pp. 463-476, 2017, https://doi.org/10.1016/j.enconman.2016.12.082.
[23] L. Sandrolini, M. Artioli, and U. Reggiani, “Numerical method for the extraction of photovoltaic module double-diode model parameters through cluster analysis,†Applied Energy, vol. 87, no. 2, pp. 442–451, 2010, https://doi.org/10.1016/j.apenergy.2009.07.022.
[24] C. Kumar and D. M. Mary, “Parameter estimation of three-diode solar photovoltaic model using an Improved-African Vultures optimization algorithm with Newton–Raphson method,†Journal of Computational Electronics, vol. 20, pp. 2563-2593, 2021, https://doi.org/10.1007/s10825-021-01812-6.
[25] M. T. Benmessaoud, P. Vasant, A. B. Stambouli, and M. Tioursi, “Modeling and parameters extraction of photovoltaic cell and modules using the genetic algorithms with lambert W-function as objective function,†Intelligent Decision Technologies, vol. 14, no. 2, pp. 143-151, 2020, https://doi.org/10.3233/IDT-180015.
[26] J. Ma, Z. Bi, T. O. Ting, S. Hao, and W. Hao, “Comparative performance on photovoltaic model parameter identification via bio-inspired algorithms,†Solar Energy, vol. 132, pp. 606-616, 2016, https://doi.org/10.1016/j.solener.2016.03.033.
[27] A. R. Jordehi, “Time varying acceleration coefficients particle swarm optimisation (TVACPSO): A new optimisation algorithm for estimating parameters of PV cells and modules,†Energy Conversion and Management, vol. 129, pp. 262-274, 2016, https://doi.org/10.1016/j.enconman.2016.09.085.
[28] N. Hamid, R. Abounacer, M. Idali Oumhand, M. Feddaoui, and D. Agliz, “Parameters identification of photovoltaic solar cells and module using the genetic algorithm with convex combination crossover,†International Journal of Ambient Energy, vol. 40, no. 5, pp. 517-524, 2019, https://doi.org/10.1080/01430750.2017.1421577.
[29] M. Merchaoui, A. Sakly, and M. F. Mimouni, “Particle swarm optimisation with adaptive mutation strategy for photovoltaic solar cell/module parameter extraction,†Energy Conversion and Management, vol. 175, pp. 151-163, 2018, https://doi.org/10.1016/j.enconman.2018.08.081.
[30] A. Askarzadeh and A. Rezazadeh, “Parameter identification for solar cell models using harmony search-based algorithms,†Solar Energy, vol. 86, no. 11, pp. 3241-3249, 2012, https://doi.org/10.1016/j.solener.2012.08.018.
[31] R. Bendaoud et al., “New method for extracting physical parameters of PV generators combining an implemented genetic algorithm and the simulated annealing algorithm,†Solar Energy, vol. 194, pp. 239-247, 2019, https://doi.org/10.1016/j.solener.2019.10.040.
[32] B. Jacob, K. Balasubramanian, T. S. Babu and N. Rajasekar, “Parameter extraction of solar PV double diode model using artificial immune system,†2015 IEEE International Conference on Signal Processing, Informatics, Communication and Energy Systems (SPICES), pp. 1-5, 2015, https://doi.org/10.1109/SPICES.2015.7091390.
[33] S. Li, Q. Gu, W. Gong, and B. Ning, “An enhanced adaptive differential evolution algorithm for parameter extraction of photovoltaic models,†Energy Conversion and Management, vol. 205, p. 112443, 2020, https://doi.org/10.1016/j.enconman.2019.112443.
[34] L. Guo, Z. Meng, Y. Sun, and L. Wang, “Parameter identification and sensitivity analysis of solar cell models with cat swarm optimization algorithm,†Energy Conversion and Management, vol. 108, pp. 520-528, 2016, https://doi.org/10.1016/j.enconman.2015.11.041.
[35] L. Xu, L. Bai, H. Bao and J. Jiang, “Parameter Identification of Solar Cell Model Based on Improved Artificial Bee Colony Algorithm,†2021 13th International Conference on Advanced Computational Intelligence (ICACI), pp. 239-244, 2021, https://doi.org/10.1109/ICACI52617.2021.9435902.
[36] A. R. Jordehi, “Enhanced leader particle swarm optimisation (ELPSO): An efficient algorithm for parameter estimation of photovoltaic (PV) cells and modules,†Solar Energy, vol. 159, pp. 78-87, 2018, https://doi.org/10.1016/j.solener.2017.10.063.
[37] A. M. Shaheen, A. R. Ginidi, R. A. El-Sehiemy and S. S. M. Ghoneim, “A Forensic-Based Investigation Algorithm for Parameter Extraction of Solar Cell Models,†IEEE Access, vol. 9, pp. 1-20, 2021, https://doi.org/10.1109/ACCESS.2020.3046536.
[38] C. Kumar, T. D. Raj, M. Premkumar, and T. D. Raj, “A new stochastic slime mould optimization algorithm for the estimation of solar photovoltaic cell parameters,†Optik, vol. 223, p. 165277, 2020, https://doi.org/10.1016/j.ijleo.2020.165277.
[39] X. Chen and K. Yu, “Hybridizing cuckoo search algorithm with biogeography-based optimization for estimating photovoltaic model parameters,†Solar Energy, vol. 180, pp. 192-206, 2019, https://doi.org/10.1016/j.solener.2019.01.025.
[40] A. Askarzadeh and A. Rezazadeh, “Extraction of maximum power point in solar cells using bird mating optimizer-based parameters identification approach,†Solar Energy, vol. 90, pp. 123-133, 2013, https://doi.org/10.1016/j.solener.2013.01.010.
[41] A. A. Z. Diab, H. M. Sultan, T. D. Do, O. M. Kamel and M. A. Mossa, “Coyote Optimization Algorithm for Parameters Estimation of Various Models of Solar Cells and PV Modules,†IEEE Access, vol. 8, pp. 111102-111140, 2020, https://doi.org/10.1109/ACCESS.2020.3000770.
[42] A. T. Kiani, M. Faisal Nadeem, A. Ahmed, I. A. Sajjad, A. Raza and I. A. Khan, “Chaotic Inertia Weight Particle Swarm Optimization (CIWPSO): An Efficient Technique for Solar Cell Parameter Estimation,†2020 3rd International Conference on Computing, Mathematics and Engineering Technologies (iCoMET), pp. 1-6, 2020, https://doi.org/10.1109/iCoMET48670.2020.9074085.
[43] A. Vinod and A. K. Sinha, “Estimation of parameters for one diode solar PV cell using grey Wolf optimizer to obtain exact V-I characteristics,†Journal of Engineering Research, vol. 7, no. 1, pp. 1-19, 2019, https://kuwaitjournals.org/jer/index.php/JER/article/view/4223.
[44] X. Chen, K. Yu, W. Du, W. Zhao, and G. Liu, “Parameters identification of solar cell models using generalized oppositional teaching learning based optimization,†Energy, vol. 99, pp. 170-180, 2016, https://doi.org/10.1016/j.energy.2016.01.052.
[45] J. Zhao, D. Zhang, Q. He, and L. Li, “A Hybrid-Strategy-Improved Dragonfly Algorithm for the Parameter Identification of an SDM,†Sustainability, vol. 15, no. 15, p. 11791, 2023, https://doi.org/10.3390/su151511791.
[46] A. A. Al-Shamma’a et al., “Parameter estimation of photovoltaic cell/modules using bonobo optimizer,†Energies, vol. 15, no. 1, p. 140, 2022, https://doi.org/10.3390/en15010140.
[47] M. Naeijian, A. Rahimnejad, S. M. Ebrahimi, N. Pourmousa, and S. A. Gadsden, “Parameter estimation of PV solar cells and modules using Whippy Harris Hawks Optimization Algorithm,†Energy Reports, vol. 7, pp. 4047-4063, 2021, https://doi.org/10.1016/j.egyr.2021.06.085.
[48] P. P. Biswas, P. N. Suganthan, G. Wu, and G. A. J. Amaratunga, “Parameter estimation of solar cells using datasheet information with the application of an adaptive differential evolution algorithm,†Renewable Energy, vol. 132, pp. 425-438, 2019, https://doi.org/10.1016/j.renene.2018.07.152.
[49] J. P. Ram, D. S. Pillai, N. Rajasekar, and V. K. Chinnaiyan, “Flower pollination based solar PV parameter extraction for double diode model,†Intelligent Computing Techniques for Smart Energy Systems, vol. 607, pp. 303-312, 2020, https://doi.org/10.1007/978-981-15-0214-9_34.
[50] M. Premkumar, P. Jangir, C. Ramakrishnan, G. Nalinipriya, H. H. Alhelou and B. S. Kumar, “Identification of Solar Photovoltaic Model Parameters Using an Improved Gradient-Based Optimization Algorithm With Chaotic Drifts,†IEEE Access, vol. 9, pp. 62347-62379, 2021, https://doi.org/10.1109/ACCESS.2021.3073821.
[51] B. Javidy, A. Hatamlou, and S. Mirjalili, “Ions motion algorithm for solving optimization problems,†Applied Soft Computing, vol. 32, pp. 72-79, 2015, https://doi.org/10.1016/j.asoc.2015.03.035.
[52] M. Awad, M. M. Mahmoud, Z. M. S. Elbarbary, L. Mohamed Ali, S. N. Fahmy, and A. I. Omar, “Design and analysis of photovoltaic/wind operations at MPPT for hydrogen production using a PEM electrolyzer: Towards innovations in green technology,†PLoS One, vol. 18, no. 7, p. e0287772, 2023, https://doi.org/10.1371/journal.pone.0287772.
[53] M. N. A. Hamid et al., “Adaptive Frequency Control of an Isolated Microgrids Implementing Different Recent Optimization Techniques,†International Journal of Robotics and Control Systems, vol. 4, no. 3, pp. 1000-1012, 2024, https://doi.org/10.31763/ijrcs.v4i3.1432.
[54] A. T. Hassan et al., “Adaptive Load Frequency Control in Microgrids Considering PV Sources and EVs Impacts: Applications of Hybrid Sine Cosine Optimizer and Balloon Effect Identifier Algorithms,†International Journal of Robotics and Control Systems, vol. 4, no. 2, pp. 941-957, 2024, https://doi.org/10.31763/ijrcs.v4i2.1448.
[55] A. A. Mas’ud et al., “A Quasi oppositional smell agent optimization and its levy flight variant: A PV/Wind/battery system optimization application,†Applied Soft Computing, vol. 147, p. 110813, 2023, https://doi.org/10.1016/j.asoc.2023.110813.
[56] S. R. K. Joga et al., “Applications of tunable-Q factor wavelet transform and AdaBoost classier for identification of high impedance faults: Towards the reliability of electrical distribution systems,†Energy Exploration & Exploitation, 2024, https://doi.org/10.1177/01445987241260949.
[57] A. A. Elfatah, F. A. Hashim, R. R. Mostafa, H. A. El-Sattar, and S. Kamel, “Energy management of hybrid PV/diesel/battery systems: A modified flow direction algorithm for optimal sizing design — A case study in Luxor, Egypt,†Renewable Energy, vol. 218, p. 119333, 2023, https://doi.org/10.1016/j.renene.2023.119333.
[58] Q. Niu, L. Zhang, and K. Li, “A biogeography-based optimization algorithm with mutation strategies for model parameter estimation of solar and fuel cells,†Energy Conversion and Management, vol. 86, pp. 1173-1185, 2014, https://doi.org/10.1016/j.enconman.2014.06.026.
[59] V. Lo Brano, A. Orioli, and G. Ciulla, “On the experimental validation of an improved five-parameter model for silicon photovoltaic modules,†Solar Energy Materials and Solar Cells, vol. 105, pp. 27-39, 2012, https://doi.org/10.1016/j.solmat.2012.05.028.
Refbacks
- There are currently no refbacks.
Copyright (c) 2024 Mohaned Elnaggar, Dina Mourad, Mahmoud M. Hussein, Noha Anwer
This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.
| About the Journal | Journal Policies | Author | Information |
International Journal of Robotics and Control Systems
e-ISSN: 2775-2658
Website: https://pubs2.ascee.org/index.php/IJRCS
Email: ijrcs@ascee.org
Organized by: Association for Scientific Computing Electronics and Engineering (ASCEE), Peneliti Teknologi Teknik Indonesia, Department of Electrical Engineering, Universitas Ahmad Dahlan and Kuliah Teknik Elektro
Published by: Association for Scientific Computing Electronics and Engineering (ASCEE)
Office: Jalan Janti, Karangjambe 130B, Banguntapan, Bantul, Daerah Istimewa Yogyakarta, Indonesia