Application of particle swarm optimization for maximum power point tracking in PV system

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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Maximum Power Point Tracking of Partially Shaded Photovoltaic Arrays Using Particle Swarm Optimization

2014 4th International Conference on Artificial Intelligence with Applications in Engineering and Technology ◽

10.1109/icaiet.2014.48 ◽

2014 ◽

Cited By ~ 2

Author(s):

Kenneth Tze Kin Teo ◽

Pei Yi Lim ◽

Bih Lii Chua ◽

Hui Hwang Goh ◽

Min Keng Tan

Keyword(s):

Particle Swarm Optimization ◽

Maximum Power Point Tracking ◽

Particle Swarm ◽

Maximum Power ◽

Maximum Power Point ◽

Swarm Optimization ◽

Point Tracking ◽

Power Point Tracking ◽

Photovoltaic Arrays ◽

Power Point

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PARTICLE SWARM OPTIMIZATION WITH INDIVIDUALLY BIASED PARTICLES FOR RELIABLE AND ROBUST MAXIMUM POWER POINT TRACKING UNDER PARTIAL SHADING CONDITIONS

Eurasian Physical Technical Journal ◽

10.31489/2020no2/128-137 ◽

2020 ◽

Vol 17 (2) ◽

pp. 128-137

Author(s):

K. Baktybekov ◽

◽

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

Efficient power control techniques are an integral part of photovoltaic system design. One of the means of managing power delivery is regulating the duty cycle of the DC to DC converter by various algorithms to operate only at points where power is maximum power point. Search has to be done as fast as possible to minimize power loss, especially under dynamically changing irradiance. The challenge of the task is the nonlinear behavior of the PV system under partial shading conditions. Depending on the size and structure of the photovoltaic panels, PSC creates an immense amount of possible P-V curves with numerous local maximums - requiring an intelligent algorithm for determining the optimal operating point. Existing benchmark maximum power point tracking algorithms cannot handle multiple peaks, and in this paper, we offer an adaptation of particle swarm optimization for the specific task.

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