Design of Maximum Power Point Tracking Photovoltaic System Based on Incremental Conductance Algorithm using Arduino Uno and Boost Converter
Article Sidebar
Main Article Content
Abstract
Fossil fuel reserves are limited while the growing demand for energy utilization. It leads to an acceleration of renewable energy use. One of the renewable energy resources is solar energy, called the photovoltaic system. This paper uses a photovoltaic solar system consisting of a solar panel module, DC-DC boost converter, voltage divider, ACS712 as a current sensor, Arduino Uno, and load resistor. Maximum Power Point Tracking (MPPT) controller is implemented to track the maximum power point of the solar panel system using a boost converter based on the Incremental Conductance algorithm embedded in Arduino UNO. The PV system with MPPT controller is designed with PV 20 W. The testing of the ACS712 current sensor and voltage sensor show error values of about 1.82% and 0.83%, respectively, which are acceptable limits. Besides, the DC-DC boost converter is also tested, and its performance shows an increase in the output voltage. The test result of the PV system with MPPT control based on the Incremental Conductance algorithm shows the average value of the PV power output with resistive load at 36 Ω is about 7.34 W, while the PV system without MPPT is about 6.07 W. Thus, the Photovoltaic system using MPPT controller based on the incremental conductance algorithm can control PV power output at the maximum power point.
Downloads
Article Details
Copyright (c) 2022 Efendi S Wirateruna, Mohammad Jasa Afroni; Fawaidul Badri
This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.
References
A. Shahsavari and M. Akbari, "Potential of solar energy in developing countries for reducing energy-related emissions," Renewable and Sustainable Energy Reviews, vol. 90, pp. 275-291, 2018.
V. S. Arutyunov and G. V. Lisichkin, "Energy resources of the 21st century: problems and forecasts. Can renewable energy sources replace fossil fuels," Russian Chemical Reviews, vol. 86, no. 8, pp. 777-804, 2017.
S. Bilgen, S. Keleş, İ. Sarıkaya and K. Kaygusuz, "Bilgen, S., Keleş, S., Sarıkaya, İ., & Kaygusuz, K. (2015). A perspective for potential and technology of bioenergy in Turkey: Present case and future view," Renewable and Sustainable Energy Reviews, vol. 48, pp. 228-239, 2015.
M. Tükenmez and E. Demireli, "Renewable energy policy in Turkey with the new legal," Renewable Energy, vol. 39, no. 1, pp. 1-9, 2012.
N. M. Xie, C. Yuan and Y. Yang, "Forecasting China's energy demand and self-sufficiency rate by grey forecasting model and Markov model," International Journal of Electrical Power & Energy Systems, vol. 66, pp. 1-8, 2015.
A. Sopinka, G. van Kooten and L. Wong, "Reconciling self-sufficiency and renewable energy targets in a hydro dominated system: the view from British Columbia," Energy Polic, vol. 61, pp. 223-229, 2013.
A. Kiraly, B. Pahor and Z. Kravanja, "Achieving energy self-sufficiency by integrating re-newables into companies' supply networks," Energy, vol. 55, p. 46–57, 2013.
M. Zhang, D. Zhou, P. Zhou and G. Liu, "Optimal feed-in tariff for solar photovoltaic power generation in China: a real options analysis," Energy Policy, vol. 97, p. 181–192, 2016.
M. A. G. De Brito, L. Galotto, L. P. Sampaio, G. d. A. e Melo and C. A. Canesin, "Evaluation of the Main MPPT Techniques for Photovoltaic Applications," IEEE Transactions on Industrial Electronics, pp. 1156-1167, 2013.
A. Chamim, R. Al Hasibi, Y. Jusman, A. Jamal, S. Aprilia and Jeckson, "Analysis of Potential Alternative Energy Sources for Electricity Conservation in Yogyakarta State Finance Building," Journal of Electrical Technology UMY (JET-UMY), vol. 3, no. 3, pp. 98-105, 2019.
Y. Chen, K. VanSant, Y. Khoo, Z. Wang, W. Luo, C. Deline, P. Hacke, J. Chai, L. Yin, Y. Wang, A. Aberle, Y. Yang, P. Altermatt, Z. Feng, S. Kurtz and P. Verlinden, "Investigation of Correlation between Field Performance and Indoor Acceleration Measurements of Potential Induced Degradation (PID) for c-Si PV Modules," in 33rd EU PVSEC, Amsterdam, Netherland, 2017.
S. Ganesh, J. Janani and G. B. Angel, "Maximum Power Point Tracker for PV Solar Panels Using SEPIC Converter," International Journal of Science and Research (IJSR), vol. 4, no. 5, pp. 356-361, 2014.
N. Moheimani and D. Parlevliet, "Sustainable solar energy conversion to chemical and electrical energy," Renewable and Sustainable Energy Reviews, vol. 27(C), pp. 494-504, 2013.
P. Bhatnagar and R. Nema, "Maximum power point tracking control techniques: State-of-the-art in photovoltaic applications," Renewable and Sustainable Energy Reviews, vol. 23, no. C, pp. 224-241, 2013.
M. Mao, L. Cui, Q. Zhang, K. Guo, L. Zhou and H. Huang, "Classification and Summarization of Solar Photovoltaic MPPT Techniques: A review based on traditional and intelligent control strategies," Energy Reports, vol. 6, pp. 1312-1327, 2020.
Y. Chaibi, M. Salhi, A. El-Jouni and A. Essadki, "A new method to extract the equivalent circuit parameters of a photovoltaic panel," Solar Energy, vol. 163, p. 376–386, 2018.
S. Motahhir, A. Chalh, A. Ghzizal, S. Sebti and A. Derouich, "Modeling of Photovoltaic Panel by using Proteus," Journal of Engineering Science and Technology Review, vol. 10, no. 2, pp. 8-13, 2017.
L. Amartee, "Voltage Sensor," 08 01 2021. [Online]. Available: https://www.emartee.com/product/42082/VoltageSensor.
Components101, "www.components101.com," [Online]. Available: https://components101.com/sensors/acs712-current-sensor-module. [Accessed 06 01 2021].
W. H. Daniel, Introduction to Power Electronics, Indiana: Printice-Hall International, 1997.
K. Ishaque and Z. Salam, "A review of maximum power point tracking techniques of PV system for uniform insolation and partial shading condition.," Renewable and Sustainable Energy Review, vol. 19, pp. 475-488, 2013.
P. Mohanty, G. Bhuvaneswari, R. Balasubramanian and N. Dhaliwal, "MATLAB based modeling to study the performance of different MPPT techniques used for solar PV system under various operating conditions," Renewable and Sustainable Energy Reviews, vol. 38, pp. 581-593, 2014.
A. Chalh, A. Hammoumi, S. Motahhir, A. Ghzizal, U. Subramaniam and A. Derouich, "Trusted Simulation Using Proteus Model for a PV System: Test Case of an Improved HC MPPT Algorithm," Energies, vol. 13, no. 8, p. 1943, 2020.
P. Sivakumar, A. Kader, Y. Kaliavaradhan and M. Arutchelvi, "Analysis and Enhancement of PV efficiency with Incremental Conductance MPPT Technique under non-linier Loading Conditions," Journal of Renewable Energy, vol. 81, pp. 543-550, 2015.
T. Kok Soon, S. Mekhilef and A. Safari, "Simple and low cost incremental conductance maximum power point tracking using," Jounal of Renewable and Sustainable Energy, vol. 5, no. 2, 2013.
S. Necaibia, M. S. Kelaiaia, H. Labar, A. Necaibia and E. D. Castronuovo, "Enhanced auto-scaling incremental conductance MPPT method, implemented on low-cost microcontroller and SEPIC converter," Solar Energy, vol. 180, p. 152–168, 2019.
S. Ma, M. Chen, J. Wu, W. Huo and L. Huang, "Augmented nonlinear controller for maximum power-point tracking with artificial neural network in grid-connected photovoltaic systems," Energies, vol. 9, no. 12, p. 1005, 2016.