Performance of MPSO-MPPT on PV-Based DC Microgrid in Partial Shading Conditions

Haneef Nouval Alannibras Humaidi(1*), Mokhammad Isnaeni Bambang Setyonegoro(2), Sarjiya Sarjiya(3)

(1) Universitas Gadjah Mada
(2) Universitas Gadjah Mada
(3) Universitas Gadjah Mada
(*) Corresponding Author


Microgrid is a controllable decentralized group of energy resources and loads with the ability to operate both in grid-connected or island modes. Photovoltaic (PV) is one of the sources that are commonly used in microgrid. PV has a good ability to convert solar irradiation into electrical energy, especially under ideal condition, namely uniform irradiation or non-shading condition. However, PV often has some problems when facing partial shading condition. In this condition, PV does not produce optimal power because it stucks at the local maximum power point (MPP), thus it unables to track the global MPP. For this reason, it is necessary to implement a smart maximum power point tracker (MPPT) that can solve this problem. Furthermore, MPPT will be implemented in pulse width modulation (PWM) to control the buck converter. This study is focused on designing a laboratory scaled microgrid system with PV sources and controlled by modified particle swarm optimization (MPSO)-based MPPT. The 360 Wp PV array used consisted of two strings of three series modules Solarex MSX-60. The performance of the proposed method was compared with perturb and observe (P&O)-based MPPT, which was the commonly used method on MPPT. Furthermore, it was found that P&O and MPSO performed relatively similar accuracy (with difference of 0.04%) in non-shading condition. However, in partial shading condition, MPSO could perform better by producing greater output power so that it delivers better accuracy (98.74% to 99.11%) compared to P&O (57.95% to 71.87%). However, MPSO required a slightly longer time to converge because it had more complicated method and more computational load.


DC Microgrid;MPPT;P&O;MPSO;Partial Shading

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N. Hatziargyiou, Ed., Microgrids: Architecture and Control. West Sussex, UK: Wiley-IEEE Press, 2014.

D. Yoesgiantoro, Kebijakan Energi Lingkungan, 1st ed., Jakarta, Indonesia: Pustaka LP3ES, 2017.

(2010) “Pemanfaatan Energi Surya di Indonesia,” [Online],, access date: May 16, 2019.

A. Reinders, H. Veldhuis, and A. Susandi, “Development of Grid-Connected PV Systems for Remote Electrification in Indonesia,” 2011 37th IEEE Photovoltaic Specialists Conference, 2011, pp. 002420–002425.

F.G. Nst and Syukriyadin, “Studi Pemodelan Integrasi Pembangkit Skala Mikro Terdistribusi pada Daerah Isolated di Aceh,” Seminar Nasional dan ExpoTeknik Elektro 2012, 2012, pp. 8–13.

I. Rahardjo and I. Fitriana, “Analisis Potensi Pembangkit Listrik Tenaga Surya di Indonesia,” in Strategi Penyediaan Listrik Nasional Dalam Rangka Mengantisipasi Pemanfaatan PLTU Batubara Skala Kecil, PLTN, dan Energi Terbarukan, P3TKKE, BPPT, I. Nurdyastuti and M.S. Boedoyo, Eds., Jakarta, Indonesia: Pusat Pengkajian dan Penerapan Teknologi Konversi dan Konservasi Energi, 2005, pp. 43–52.

M.G. Villalva, J.R. Gazoli, and E.R. Filho, “Modeling and Circuit-Based Simulation of Photovoltaic Arrays,” 2009 Brazilian Power Electronics Conference, 2009, pp. 1244–1254.

K. Ishaque, Z. Salam, M. Amjad, and S. Mekhilef, “An Improved Particle Swarm Optimization (PSO)-Based MPPT for PV with Reduced Steady-State Oscillation,” IEEE Transactions on Power Electronics, Vol. 27, No. 8, pp. 3627–3638, Aug. 2012.

B. Bendib, H. Belmili, and F. Krim, “A Survey of the Most Used MPPT Methods: Conventional and Advanced Algorithms Applied for Photovoltaic Systems,” Renewable and Sustainable Energy Reviews, Vol. 45, pp. 637–648, May 2015.

K. Ishaque, Z. Salam, M. Amjad, and S. Mekhilef, “An Improved Particle Swarm Optimization (PSO)-Based MPPT for PV with Reduced Steady-State Oscillation,” IEEE Transactions on Power Electronics, Vol. 27, No. 8, pp. 3627–3638, 2012.

W. Apriliyanto, F.D. Wijaya, and E. Firmansyah, “Performance of Microgrid with Photovoltaic, Synchronous Generator and Induction Generator Power Sources,” 2016 8th International Conference on Information Technology and Electrical Engineering (ICITEE), 2016, pp. 1–6,

N. Femia, G. Petrone, G. Spagnuolo, and M. Vitelli, “Optimizing Sampling Rate of P&O MPPT Technique,” 2004 IEEE 35th Annual Power Electronics Specialists Conference (IEEE Cat. No.04CH37551), 2004, pp. 1945–1949.

A.F. Sapprudin, “Modifikasi variabel Step Size Mppt P&O pada Sistem Turbin Angin Stand-Alone,” Master's thesis, Universitas Gadjah Mada, Indonesia, 2020.

Y.M. Kolewora, E. Firmansyah, and S. Suharyanto, “MPPT Berdasarkan Algoritma P&O dan IC pada Interleaved-Flyback 250W,” Telematika, Vol. 11, No. 1, pp. 18–36, Feb. 2018.

F.D. Murdianto, A.R. Nansur, A.S.L. Hermawan, E. Purwanto, A. Jaya, and M.M. Rifadil, “Modeling and Simulation of MPPT SEPIC - BUCK Converter Series Using Flower Pollination Algorithm (FPA) - PI Controller in DC Microgrid Isolated System,” 2018 International Electrical Engineering Congress (iEECON), 2018, pp. 1–4.

G.L.H. Priyanka and A.S.H. Babu, “PSO & GSA Algorithms for Global MPPT in Photo Voltaic System,” Internatinal Journal of Research in Computer and Communication Technology, Vol. 6, No. 5, pp. 167–175, May 2017.

P. Megantoro, F.D. Wijaya, and E. Firmansyah, “Analyze and Optimization of Genetic Algorithm Implemented on Maximum Power Point Tracking Technique for PV System,” 2017 International Seminar on Application for Technology of Information and Communication (iSemantic), 2017, pp. 79–84.

A. Kowalczyk, A. Wlodarczyk, and J. Tarnawski, “Microgrid Energy Management System,” 2016 21st International Conference on Methods and Models in Automation and Robotics (MMAR), 2016, pp. 157–162.

J. Hui, A. Bakhshai, and P.K. Jain, “A Hybrid Wind-Solar Energy System: A New Rectifier Stage Topology,” 2010 Twenty-Fifth Annual IEEE Applied Power Electronics Conference and Exposition (APEC), 2010, pp. 155–161.

N. Femia, G. Petrone, G. Spagnuolo, and M. Vitelli, “Optimization of Perturb and Observe Maximum Power Point Tracking Method,” IEEE Transactions on Power Electronics, Vol. 20, No. 4, pp. 963–973, Jul. 2005.

R. Eberhart and J. Kennedy, “A New Optimizer Using Particle Swarm Theory,” Proceedings of the Sixth International Symposium on Micro Machine and Human Science, 1995, pp. 39–43.


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