Evaluation of particle swarm optimization techniques applied to maximum power point tracking in photovoltaic systems

This paper presents an accelerated particle swarm optimization (PSO)-based maximum power point tracking (MPPT) algorithm to track global maximum power point (MPP) of photovoltaic (PV) generation under partial shading conditions. Conventional PSO-based MPPT algorithms have common weaknesses of a long convergence time to reach the global MPP and oscillations during the searching. The proposed algorithm includes a standard PSO and a perturb-and-observe algorithm as the accelerator. It has been experimentally tested and compared with conventional MPPT algorithms. Experimental results show that the proposed MPPT method is effective in terms of high reliability, fast dynamic response, and high accuracy in tracking the global MPP.

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Maximum Power Point Tracking Method Based on Modified Particle Swarm Optimization for Photovoltaic Systems

International Journal of Photoenergy ◽

10.1155/2013/583163 ◽

2013 ◽

Vol 2013 ◽

pp. 1-6 ◽

Cited By ~ 12

Author(s):

Kuei-Hsiang Chao ◽

Long-Yi Chang ◽

Hsueh-Chien Liu

Keyword(s):

Particle Swarm Optimization ◽

Maximum Power Point Tracking ◽

Particle Swarm ◽

Maximum Power ◽

Photovoltaic Module ◽

Maximum Power Point ◽

Swarm Optimization ◽

Point Tracking ◽

Power Point Tracking ◽

Power Point

This study investigated the output characteristics of photovoltaic module arrays with partial module shading. Accordingly, we presented a maximum power point tracking (MPPT) method that can effectively track the global optimum of multipeak curves. This method was based on particle swarm optimization (PSO). The concept of linear decreases in weighting was added to improve the tracking performance of the maximum power point tracker. Simulation results were used to verify that this method could successfully track maximum power points in the output characteristic curves of photovoltaic modules with multipeak values. The results also established that the performance of the modified PSO-based MPPT method was superior to that of conventional PSO methods.

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Efficiency Improvement of Photovolataic by Using Maximum Power Point Tracking Based on Particle Swarm Optimization Algorithm Under Normal and Partial Shading

JEEE-U (Journal of Electrical and Electronic Engineering-UMSIDA) ◽

10.21070/jeee-u.v2i2.1703 ◽

2018 ◽

Vol 2 (2) ◽

pp. 71

Author(s):

Machmud Effendy ◽

Khusnul Hidayat ◽

Wahyu Dianto Pramana

Keyword(s):

Particle Swarm Optimization ◽

Maximum Power Point Tracking ◽

Particle Swarm ◽

Maximum Power ◽

Maximum Power Point ◽

Partial Shading ◽

Swarm Optimization ◽

Point Tracking ◽

Power Point Tracking ◽

Power Point

Photovoltaic (PV) is a device which is capable to converts solar irradiance into Direct Current (DC) electricity energy. To increase the power result of PV, it needs a method to track the Maximum Power Point(MPP) which is usually called Maximum power Point Tracking(MPPT). So that, the power result increased with low cost. The purpose of this research is to conduct MPPT modeling by Particle Swarm Optimization (PSO). The proposed method is implemented in DC to DC converter. This research used SEPIC converter. The purpose of using SEPIC converter is in order the output of current and voltage have smallest ripple. The modelling system is conducted by using MATLAB 2016b software to find out performance of PSO and SEPIC converter. The evaluation of PSO and SEPIC converter performance has been done. The simulation result shows that the proposed system has been working very well. The PSO has good accurateness in tracking and capable to to track the power produced by PV with velocity around ±4,2 seconds when in conditions STC, ±9,2 seconds when in conditions partial shading, despite a fluctuating irradiance change. While in SEPIC converter is able to reach efficiency of ≥ 80%.

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