Buck-boost Converter using GA-based MPPT for Solar Energy Optimization

Lailis Syafaah; Amrul Faruq; Basri Noor Cahyadi; Khusnul Hidayat; Novendra Setyawan; Merinda Lestandy; Zulfatman

doi:10.22219/kinetik.v8i3.1658

Issue

Vol. 8, No. 3, August 2023

Issue Published : Aug 17, 2023

This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.

Buck-boost Converter using GA-based MPPT for Solar Energy Optimization

https://doi.org/10.22219/kinetik.v8i3.1658

Lailis Syafaah

Universitas Muhammadiyah Malang

Amrul Faruq

Universitas Muhammadiyah Malang

Basri Noor Cahyadi

Universitas Muhammadiyah Malang

Khusnul Hidayat

Universitas Muhammadiyah Malang

Novendra Setyawan

Universitas Muhammadiyah Malang

Merinda Lestandy

Universitas Muhammadiyah Malang

Zulfatman

Universitas Muhammadiyah Malang

Corresponding Author(s) : Basri Noor Cahyadi

basrinoorc@umm.ac.id

Kinetik: Game Technology, Information System, Computer Network, Computing, Electronics, and Control, Vol. 8, No. 3, August 2023
Article Published : Aug 17, 2023

Abstract

Energy optimization in the Solar Power Plant system needs to have more attention. Indonesia is a tropical country that has two seasons, where the weather and cloud movements are frequently unpredictable, especially in the southern region of Java Island. To overcome this problem, an inverter equipped with maximum power point tracking (MPPT) was used. However, the current MPPT switching system was still not optimal with an efficiency of around 90%. In this study, the installation of MPPT was carried out in order to optimize the power in solar photovoltaic (PV) system due to the fluctuations of solar irradiation at PT. Jatinom Indah Agri, Blitar City. The maximum power generated by solar photovoltaic could be achieved by using the combination of DC - DC converter and artificial intelligence. In this study, the modeling of solar PV system was made using MATLAB software, where the design of the solar PV system consisted of a PV module with capacity 240W, DC to DC converter, battery and MPPT. Genetic Algorithm (GA)-based MPPT had been tested and compared to Particle Swarm Optimization (PSO)-based MPPT and conventional MPPT, where the GA-based MPPT worked well in finding the maximum power point in the solar photovoltaic system. It was found that GA-based MPPT produced a maximum power point close to PV power with an efficiency of 92%, while the effciciency of PSO-based MPPT and conventional MPPT were 85% and 79% respectively. In selecting the method for designing MPPT, a method with a wide range of sample data is required. This is due to the fluctuation of solar irradiance received by the solar PV.

Keywords

MPPT Buck boost converter Genetic Algorithm Photovoltaic Battery Poultry Farm

Syafaah, L., Faruq, A., Noor Cahyadi, B., Hidayat, K., Setyawan, N., Lestandy, M., & Zulfatman. (2023). Buck-boost Converter using GA-based MPPT for Solar Energy Optimization. Kinetik: Game Technology, Information System, Computer Network, Computing, Electronics, and Control, 8(3). https://doi.org/10.22219/kinetik.v8i3.1658

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References

M.R. Javed et al., “A comparative study of maximum power point tracking techniques for solar systems,” Proc. - 22nd Int. Multitopic Conf. INMIC 2019, Nov. 2019. https://doi.org/10.1109/INMIC48123.2019.9022762
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D.S. Yanaratri, L.P. SR, I. Ferdiansyah, and R.P. Eviningsih, “Desain dan Implementasi MPPT PSO pada Sistem Pembangkit Listrik Tenaga,” JTT (Jurnal Teknol. Terpadu), vol. 9, no. 1, pp. 34–43, Apr. 2021. https://doi.org/10.32487/jtt.v9i1.964
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R.G. Suryavanshiu, S.R. Suryavanshi, D. R. Joshi, and R. B. Magadum, “Maximum power point tracking of SPV at varying atmospheric condition using Genetic Algorithm,” Int. Conf. Energy Syst. Appl. ICESA 2015, pp. 415–419, Jul. 2016. https://doi.org/10.1109/ICESA.2015.7503382
I. Ferdiansyah, Sutedjo, O. A. Qudsi, and A. Noer Ramadhan, “Implementation of maximum power point tracking on solar panels using cuckoo search algorithm method,” Proc. ICAITI 2019 - 2nd Int. Conf. Appl. Inf. Technol. Innov. Explor. Futur. Technol. Appl. Inf. Technol. Innov., pp. 88–92, Sep. 2019. https://doi.org/10.1109/ICAITI48442.2019.8982163
H.A. Mohamed, H.A. Khattab, A. Mobarka, and G.A. Morsy, “Design, control and performance analysis of DC-DC boost converter for stand-alone PV system,” 2016 18th Int. Middle-East Power Syst. Conf. MEPCON 2016 - Proc., pp. 101–106, Jan. 2017. https://doi.org/10.1109/MEPCON.2016.7836878
“(13) (PDF) DC-DC boost converter design for solar electric system.” (accessed Dec. 28, 2022).
P. Sahu, D. Verma, and S. Nema, “Physical design and modelling of boost converter for maximum power point tracking in solar PV systems,” Int. Conf. Electr. Power Energy Syst. ICEPES 2016, pp. 10–15, May 2017. https://doi.org/10.1109/ICEPES.2016.7915898
M.A. Sahnoun, H.M.R. Ugalde, J.C. Carmona, and J. Gomand, “Maximum Power point Tracking Using P&O Control Optimized by a Neural Network Approach: A Good Compromise between Accuracy and Complexity,” Energy Procedia, vol. 42, pp. 650–659, Jan. 2013. https://doi.org/10.1016/j.egypro.2013.11.067
V. V. and V. S. R. R., “Microcontroller based bidirectional buck–boost converter for photo-voltaic power plant,” J. Electr. Syst. Inf. Technol., vol. 5, no. 3, pp. 745–758, Dec. 2018. https://doi.org/10.1016/j.jesit.2017.04.002
K.K. Pandey, M. Kumar, A. Kumari, and J. Kumar, “Bidirectional DC-DC Buck-Boost Converter for Battery Energy Storage System and PV Panel,” Smart Innov. Syst. Technol., vol. 206, pp. 681–693, 2021. http://dx.doi.org/10.1007/978-981-15-9829-6_54
D. Mohapatra, S. Padhee, and J. Jena, “Design of Solar Powered Battery Charger: An Experimental Verification,” 2018 IEEE Int. Students’ Conf. Electr. Electron. Comput. Sci. SCEECS 2018, Nov. 2018. https://doi.org/10.1109/SCEECS.2018.8546929
K.H. Chao and M.N. Rizal, “A Hybrid MPPT Controller Based on the Genetic Algorithm and Ant Colony Optimization for Photovoltaic Systems under Partially Shaded Conditions,” Energies 2021, Vol. 14, Page 2902, vol. 14, no. 10, p. 2902, May 2021. https://doi.org/10.3390/en14102902
M.S. Bouakkaz et al., “Global Maximum Power Point Tracking Using Genetic Algorithm Combined with PSO Tuned PID Controller,” Lect. Notes Networks Syst., vol. 211 LNNS, pp. 1171–1180, 2021. http://dx.doi.org/10.1007/978-3-030-73882-2_107
S. Hadji, J.P. Gaubert, and F. Krim, “Real-Time Genetic Algorithms-Based MPPT: Study and Comparison (Theoretical an Experimental) with Conventional Methods,” Energies 2018, Vol. 11, Page 459, vol. 11, no. 2, p. 459, Feb. 2018. https://doi.org/10.3390/en11020459
M. Lasheen, A K.A. Rahman, M. Abdel-Salam, and S. Ookawara, “Performance Enhancement of Constant Voltage Based MPPT for Photovoltaic Applications Using Genetic Algorithm,” Energy Procedia, vol. 100, pp. 217–222, Nov. 2016. https://doi.org/10.1016/j.egypro.2016.10.168

References

M.R. Javed et al., “A comparative study of maximum power point tracking techniques for solar systems,” Proc. - 22nd Int. Multitopic Conf. INMIC 2019, Nov. 2019. https://doi.org/10.1109/INMIC48123.2019.9022762

M. Ben Smida and A. Sakly, “Genetic based algorithm for maximum power point tracking (MPPT) for grid connected PV systems operating under partial shaded conditions,” Proc. 2015 7th Int. Conf. Model. Identif. Control. ICMIC 2015, Feb. 2016. https://doi.org/10.1109/ICMIC.2015.7409433

M. Nour Ali, “Improved Design of Artificial Neural Network for MPPT of Grid-Connected PV Systems,” 2018 20th Int. Middle East Power Syst. Conf. MEPCON 2018 - Proc., pp. 97–102, Feb. 2019. https://doi.org/10.1109/MEPCON.2018.8635202

N.M. Elbehairy, R.A. Swief, A.M. Abdin, and T. S. Abdelsalam, “Maximum Power Point Tracking for a Stand Alone PV System under Shading Conditions Using Flower Pollination Algorithm,” 2019 21st Int. Middle East Power Syst. Conf. MEPCON 2019 - Proc., pp. 840–845, Dec. 2019. https://doi.org/10.1109/MEPCON47431.2019.9008230

X. Meng, Y. An, H. Wang, Q. Yao, and C. Liang, “Tracking the Maximum Power Point of Photovoltaic Power Generation Based on Self-coding Neural Network,” Proc. 31st Chinese Control Decis. Conf. CCDC 2019, pp. 592–597, Jun. 2019. https://doi.org/10.1109/CCDC.2019.8832919

S. Hadji, F. Krim, and J.P. Gaubert, “Development of an algorithm of maximum power point tracking for photovoltaic systems using genetic algorithms,” 7th Int. Work. Syst. Signal Process. their Appl. WoSSPA 2011, pp. 43–46, 2011. https://doi.org/10.1109/WOSSPA.2011.5931408

S. Salman, X. Ai, and Z. Wu, “Design of a P-&-O algorithm based MPPT charge controller for a stand-alone 200W PV system,” Prot. Control Mod. Power Syst., vol. 3, no. 1, pp. 1–8, Dec. 2018. https://doi.org/10.1186/s41601-018-0099-8

S.K. Sahoo, M. Balamurugan, S. Anurag, R. Kumar, and V. Priya, “Maximum power point tracking for PV panels using ant colony optimization,” 2017 Innov. Power Adv. Comput. Technol. i-PACT 2017, vol. 2017-January, pp. 1–4, Jan. 2017. https://doi.org/10.1109/IPACT.2017.8245004

S.K. Saha and Jaipal, “Optimization technique based fuzzy logic controller for MPPT of solar PV system,” 2018 Int. Conf. Emerg. Trends Innov. Eng. Technol. Res. ICETIETR 2018, Nov. 2018. https://doi.org/10.1109/ICETIETR.2018.8529078

H. Salmi, A. Badri, and M. Zegrari, “Maximum Power Point Tracking (MPPT) Using Artificial Bee Colony Based Algorithm for Photovoltaic System,” http://www.sciencepublishinggroup.com, vol. 5, no. 1, p. 1, 2016. http://dx.doi.org/10.11648/j.ijiis.20160501.11

J. Khanam and S.Y. Foo, “Neural Networks Technique for Maximum Power Point Tracking of Photovoltaic Array,” Conf. Proc. - IEEE SOUTHEASTCON, vol. 2018-April, Oct. 2018. https://doi.org/10.1109/SECON.2018.8479054

N A. Windarko, A. Tjahjono, D.O. Anggriawan, and M. H. Purnomo, “Maximum power point tracking of photovoltaic system using adaptive modified firefly algorithm,” Proc. - 2015 Int. Electron. Symp. Emerg. Technol. Electron. Information, IES 2015, pp. 31–35, Jan. 2016. https://doi.org/10.1109/ELECSYM.2015.7380809

L. Nie, M. Mao, Y. Wan, L. Cui, L. Zhou, and Q. Zhang, “Maximum power point tracking control based on modified abc algorithm for shaded PV system,” 2019 AEIT Int. Conf. Electr. Electron. Technol. Automotive, AEIT Automot. 2019, Jul. 2019. https://doi.org/10.23919/EETA.2019.8804525

D.S. Yanaratri, L.P. SR, I. Ferdiansyah, and R.P. Eviningsih, “Desain dan Implementasi MPPT PSO pada Sistem Pembangkit Listrik Tenaga,” JTT (Jurnal Teknol. Terpadu), vol. 9, no. 1, pp. 34–43, Apr. 2021. https://doi.org/10.32487/jtt.v9i1.964

P. Megantoro, Y.D. Nugroho, F. Anggara, A. Pakha, and B.A. Pramudita, “The implementation of genetic algorithm to MPPT technique in a DC/DC buck converter under partial shading condition,” Proc. - 2018 3rd Int. Conf. Inf. Technol. Inf. Syst. Electr. Eng. ICITISEE 2018, pp. 308–312, Jul. 2018. https://doi.org/10.1109/ICITISEE.2018.8721005

M. Orellana, S. Petibon, B. Estibals, and C. Alonso, “Four Switch Buck-Boost converter for Photovoltaic DC-DC power applications,” IECON Proc. (Industrial Electron. Conf., pp. 469–474, 2010. https://doi.org/10.1109/IECON.2010.5674983

R.G. Suryavanshiu, S.R. Suryavanshi, D. R. Joshi, and R. B. Magadum, “Maximum power point tracking of SPV at varying atmospheric condition using Genetic Algorithm,” Int. Conf. Energy Syst. Appl. ICESA 2015, pp. 415–419, Jul. 2016. https://doi.org/10.1109/ICESA.2015.7503382

I. Ferdiansyah, Sutedjo, O. A. Qudsi, and A. Noer Ramadhan, “Implementation of maximum power point tracking on solar panels using cuckoo search algorithm method,” Proc. ICAITI 2019 - 2nd Int. Conf. Appl. Inf. Technol. Innov. Explor. Futur. Technol. Appl. Inf. Technol. Innov., pp. 88–92, Sep. 2019. https://doi.org/10.1109/ICAITI48442.2019.8982163

H.A. Mohamed, H.A. Khattab, A. Mobarka, and G.A. Morsy, “Design, control and performance analysis of DC-DC boost converter for stand-alone PV system,” 2016 18th Int. Middle-East Power Syst. Conf. MEPCON 2016 - Proc., pp. 101–106, Jan. 2017. https://doi.org/10.1109/MEPCON.2016.7836878

“(13) (PDF) DC-DC boost converter design for solar electric system.” (accessed Dec. 28, 2022).

P. Sahu, D. Verma, and S. Nema, “Physical design and modelling of boost converter for maximum power point tracking in solar PV systems,” Int. Conf. Electr. Power Energy Syst. ICEPES 2016, pp. 10–15, May 2017. https://doi.org/10.1109/ICEPES.2016.7915898

M.A. Sahnoun, H.M.R. Ugalde, J.C. Carmona, and J. Gomand, “Maximum Power point Tracking Using P&O Control Optimized by a Neural Network Approach: A Good Compromise between Accuracy and Complexity,” Energy Procedia, vol. 42, pp. 650–659, Jan. 2013. https://doi.org/10.1016/j.egypro.2013.11.067

V. V. and V. S. R. R., “Microcontroller based bidirectional buck–boost converter for photo-voltaic power plant,” J. Electr. Syst. Inf. Technol., vol. 5, no. 3, pp. 745–758, Dec. 2018. https://doi.org/10.1016/j.jesit.2017.04.002

K.K. Pandey, M. Kumar, A. Kumari, and J. Kumar, “Bidirectional DC-DC Buck-Boost Converter for Battery Energy Storage System and PV Panel,” Smart Innov. Syst. Technol., vol. 206, pp. 681–693, 2021. http://dx.doi.org/10.1007/978-981-15-9829-6_54

D. Mohapatra, S. Padhee, and J. Jena, “Design of Solar Powered Battery Charger: An Experimental Verification,” 2018 IEEE Int. Students’ Conf. Electr. Electron. Comput. Sci. SCEECS 2018, Nov. 2018. https://doi.org/10.1109/SCEECS.2018.8546929

K.H. Chao and M.N. Rizal, “A Hybrid MPPT Controller Based on the Genetic Algorithm and Ant Colony Optimization for Photovoltaic Systems under Partially Shaded Conditions,” Energies 2021, Vol. 14, Page 2902, vol. 14, no. 10, p. 2902, May 2021. https://doi.org/10.3390/en14102902

M.S. Bouakkaz et al., “Global Maximum Power Point Tracking Using Genetic Algorithm Combined with PSO Tuned PID Controller,” Lect. Notes Networks Syst., vol. 211 LNNS, pp. 1171–1180, 2021. http://dx.doi.org/10.1007/978-3-030-73882-2_107

S. Hadji, J.P. Gaubert, and F. Krim, “Real-Time Genetic Algorithms-Based MPPT: Study and Comparison (Theoretical an Experimental) with Conventional Methods,” Energies 2018, Vol. 11, Page 459, vol. 11, no. 2, p. 459, Feb. 2018. https://doi.org/10.3390/en11020459

M. Lasheen, A K.A. Rahman, M. Abdel-Salam, and S. Ookawara, “Performance Enhancement of Constant Voltage Based MPPT for Photovoltaic Applications Using Genetic Algorithm,” Energy Procedia, vol. 100, pp. 217–222, Nov. 2016. https://doi.org/10.1016/j.egypro.2016.10.168

Issue

Vol. 8, No. 3, August 2023

Buck-boost Converter using GA-based MPPT for Solar Energy Optimization

Corresponding Author(s) : Basri Noor Cahyadi

Abstract

Keywords

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References

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