COMPARISON OF PARTICLE SWARM OPTIMIZATION (PSO) AND PERTURB AND OBSERVE (P&O) METHODS FOR MAXIMUM POWER POINT TRACKING IN PHOTOVOLTAIC SYSTEMS UNDER CHANGING CLIMATIC CONDITIONS WITH OPTIMAL PARAMETER SELECTION

Ömer Faruk Çiriş; Süleyman Adak; Hasan Cangi; Ramazan Taşaltin

COMPARISON OF PARTICLE SWARM OPTIMIZATION (PSO) AND PERTURB AND OBSERVE (P&O) METHODS FOR MAXIMUM POWER POINT TRACKING IN PHOTOVOLTAIC SYSTEMS UNDER CHANGING CLIMATIC CONDITIONS WITH OPTIMAL PARAMETER SELECTION

Abstract

: Photovoltaic (PV) systems have low efficiency in electricity generation. In PV systems, Maximum Power Point Tracking (MPPT) algorithms must track the MPPT efficiently. There are both conventional and meta-heuristic methods available to track the maximum power point(MPP) of a PV system. Under Partial Shading Conditions (PSC), local maximum power points (LMPP) and a global maximum power point (GMPP) can occur. The Particle Swarm Optimization (PSO) algorithm can easily and quickly track the global maximum point. Under partial shading condition, the Perturb and Observe (P&O) method tends to get stuck at local maximum power point while tracking maximum power point. As a result, the global maximum power point of the PV system cannot be detected using the perturb and observe algorithm. In this paper, a comparative analysis was performed based on simulation results obtained from Matlab/Simulink circuit models under PSC conditions. It was observed that when the parameters of the particle swarm optimization algorithm are appropriately chosen, the particle swarm optimization method outperforms the perturb and observation method in terms of efficiency in tracking the global maximum power point. According to the simulation results, no oscillations around the global maximum power point were observed with the particle swarm optimization method. Furthermore, in rapidly changing climatic conditions, the particle swarm optimization algorithm tracks the global maximum power point more efficiently, stably, and effectively compared to the perturb and observe algorithm.

Keywords

Supporting Institution

This article has not been financially or scientifically supported by any institute

Ethical Statement

In this study, there is no issue in terms of ethical guidelines. Therefore, there is no need to obtain an ethics certificate.

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Details

Primary Language

English

Subjects

Electrical Energy Generation (Incl. Renewables, Excl. Photovoltaics), Photovoltaic Power Systems

Journal Section

Research Article

Authors

Ömer Faruk Çiriş ^*
0009-0004-6236-9548
Türkiye

Süleyman Adak
0000-0002-9290-0684
Türkiye

Hasan Cangi
0000-0001-6954-7299
Türkiye

Ramazan Taşaltin
0000-0003-2026-2430
Türkiye

Publication Date

May 30, 2025

Submission Date

March 23, 2025

Acceptance Date

May 30, 2025

Published in Issue

Year 2025 Volume: 10 Number: 1

IZ

https://izlik.org/JA32MC58YH

Cite

RIS / Bibtex

APA

Çiriş, Ö. F., Adak, S., Cangi, H., & Taşaltin, R. (2025). COMPARISON OF PARTICLE SWARM OPTIMIZATION (PSO) AND PERTURB AND OBSERVE (P&O) METHODS FOR MAXIMUM POWER POINT TRACKING IN PHOTOVOLTAIC SYSTEMS UNDER CHANGING CLIMATIC CONDITIONS WITH OPTIMAL PARAMETER SELECTION. International Journal of Energy and Smart Grid, 10(1), 42-57. https://izlik.org/JA32MC58YH

AMA

1.Çiriş ÖF, Adak S, Cangi H, Taşaltin R. COMPARISON OF PARTICLE SWARM OPTIMIZATION (PSO) AND PERTURB AND OBSERVE (P&O) METHODS FOR MAXIMUM POWER POINT TRACKING IN PHOTOVOLTAIC SYSTEMS UNDER CHANGING CLIMATIC CONDITIONS WITH OPTIMAL PARAMETER SELECTION. IJESG. 2025;10(1):42-57. https://izlik.org/JA32MC58YH

Chicago

Çiriş, Ömer Faruk, Süleyman Adak, Hasan Cangi, and Ramazan Taşaltin. 2025. “COMPARISON OF PARTICLE SWARM OPTIMIZATION (PSO) AND PERTURB AND OBSERVE (P&O) METHODS FOR MAXIMUM POWER POINT TRACKING IN PHOTOVOLTAIC SYSTEMS UNDER CHANGING CLIMATIC CONDITIONS WITH OPTIMAL PARAMETER SELECTION”. International Journal of Energy and Smart Grid 10 (1): 42-57. https://izlik.org/JA32MC58YH.

EndNote

Çiriş ÖF, Adak S, Cangi H, Taşaltin R (May 1, 2025) COMPARISON OF PARTICLE SWARM OPTIMIZATION (PSO) AND PERTURB AND OBSERVE (P&O) METHODS FOR MAXIMUM POWER POINT TRACKING IN PHOTOVOLTAIC SYSTEMS UNDER CHANGING CLIMATIC CONDITIONS WITH OPTIMAL PARAMETER SELECTION. International Journal of Energy and Smart Grid 10 1 42–57.

IEEE

[1]Ö. F. Çiriş, S. Adak, H. Cangi, and R. Taşaltin, “COMPARISON OF PARTICLE SWARM OPTIMIZATION (PSO) AND PERTURB AND OBSERVE (P&O) METHODS FOR MAXIMUM POWER POINT TRACKING IN PHOTOVOLTAIC SYSTEMS UNDER CHANGING CLIMATIC CONDITIONS WITH OPTIMAL PARAMETER SELECTION”, IJESG, vol. 10, no. 1, pp. 42–57, May 2025, [Online]. Available: https://izlik.org/JA32MC58YH

ISNAD

Çiriş, Ömer Faruk - Adak, Süleyman - Cangi, Hasan - Taşaltin, Ramazan. “COMPARISON OF PARTICLE SWARM OPTIMIZATION (PSO) AND PERTURB AND OBSERVE (P&O) METHODS FOR MAXIMUM POWER POINT TRACKING IN PHOTOVOLTAIC SYSTEMS UNDER CHANGING CLIMATIC CONDITIONS WITH OPTIMAL PARAMETER SELECTION”. International Journal of Energy and Smart Grid 10/1 (May 1, 2025): 42-57. https://izlik.org/JA32MC58YH.

JAMA

1.Çiriş ÖF, Adak S, Cangi H, Taşaltin R. COMPARISON OF PARTICLE SWARM OPTIMIZATION (PSO) AND PERTURB AND OBSERVE (P&O) METHODS FOR MAXIMUM POWER POINT TRACKING IN PHOTOVOLTAIC SYSTEMS UNDER CHANGING CLIMATIC CONDITIONS WITH OPTIMAL PARAMETER SELECTION. IJESG. 2025;10:42–57.

MLA

Çiriş, Ömer Faruk, et al. “COMPARISON OF PARTICLE SWARM OPTIMIZATION (PSO) AND PERTURB AND OBSERVE (P&O) METHODS FOR MAXIMUM POWER POINT TRACKING IN PHOTOVOLTAIC SYSTEMS UNDER CHANGING CLIMATIC CONDITIONS WITH OPTIMAL PARAMETER SELECTION”. International Journal of Energy and Smart Grid, vol. 10, no. 1, May 2025, pp. 42-57, https://izlik.org/JA32MC58YH.

Vancouver

1.Ömer Faruk Çiriş, Süleyman Adak, Hasan Cangi, Ramazan Taşaltin. COMPARISON OF PARTICLE SWARM OPTIMIZATION (PSO) AND PERTURB AND OBSERVE (P&O) METHODS FOR MAXIMUM POWER POINT TRACKING IN PHOTOVOLTAIC SYSTEMS UNDER CHANGING CLIMATIC CONDITIONS WITH OPTIMAL PARAMETER SELECTION. IJESG [Internet]. 2025 May 1;10(1):42-57. Available from: https://izlik.org/JA32MC58YH