A direct control based maximum power point tracking method for photovoltaic system under partial shading conditions using particle swarm optimization algorithm

Ishaque, Kashif; Salam, Zainal; Shamsudin, Amir; Amjad, Muhammad

doi:10.1016/j.apenergy.2012.05.026

Cited by 203 publications

(81 citation statements)

References 37 publications

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“…(a) Table 6 gives the performance comparison in terms of the average tracking time and the average MPP for 40 iterations among the proposed I-TBLO, a typical TLBO, ACO [17] and PSO [21], both referred to in the Introduction section. This proposal is obviously found to outperform the counterparts in terms of dynamic tracking response and static performance for the five cases investigated in the present study underwent MPPT.…”

Section: Mppt Measurement Of Pv Module Arraysmentioning

confidence: 99%

“…As mentioned in [18], obtaining the statistical results of ABC and particle swarm optimization (PSO) algorithms requires 5-6 s, indicating that the tracking response speed can be improved. Moreover, scholars have proposed incorporating intelligent algorithms with conventional MPPT algorithms [19][20][21][22], such as incorporating PSO or genetic algorithms with P&O. Although the incorporated methods can successfully identify global optimal solutions, the dynamic response speed is too slow.…”

Section: Introductionmentioning

confidence: 99%

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Global Maximum Power Point Tracking (MPPT) of a Photovoltaic Module Array Constructed through Improved Teaching-Learning-Based Optimization

Chao

2016

Energies

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Abstract:The present study proposes a maximum power point tracking (MPPT) method in which improved teaching-learning-based optimization (I-TLBO) is applied to perform global MPPT of photovoltaic (PV) module arrays under dissimilar shading situations to ensure the maximum power output of the module arrays. The proposed I-TLBO enables the automatic adjustment of teaching factors according to the self-learning ability of students. Incorporating smart-tracking and self-study strategies can effectively improve the tracking response speed and steady-state tracking performance. To evaluate the feasibility of the proposed I-TLBO, a HIP-2717 PV module array from Sanyo Electric was employed to compose various arrays with different serial and parallel configurations. The arrays were operated under different shading conditions to test the MPPT with double, triple, or quadruple peaks of power-voltage characteristic curves. Boost converters were employed with TMS320F2808 digital signal processors to test the proposed MPPT method. Empirical results confirm that the proposed method exhibits more favorable dynamic and static-state response tracking performance compared with that of conventional TLBO.

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Section: Mppt Measurement Of Pv Module Arraysmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Global Maximum Power Point Tracking (MPPT) of a Photovoltaic Module Array Constructed through Improved Teaching-Learning-Based Optimization

Chao

2016

Energies

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“…This phenomenon is known as the hot spot problem, whereby the shaded PV cells are damaged without appropriate protection. For that, a bypass diode is typically connected in parallel and in opposite polarity to a group of PV cells to minimize the impact of shadow on PV module [42,43]. Ideally, one bypass diode per PV cell is the best solution but would definitely increase the PV cost.…”

Section: Pv Arrays Under Partial Shaded Conditionsmentioning

confidence: 99%

Photovoltaic Multiple Peaks Power Tracking Using Particle Swarm Optimization with Artificial Neural Network Algorithm

Ngan¹,

Tan

2016

Advances in Solar Photovoltaic Power Plants

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Photovoltaic (PV) array may receive different level of solar irradiance, such as partially shaded by clouds or nearby building. Multiple peak power points occur when PV module is under partially shaded conditions, which would significantly reduce the energy produced by PV without proper control. Therefore, a Maximum Power Point Tracking (MPPT) algorithm is used to extract maximum available PV power from the PV array. However, most of the conventional MPPT algorithms are incapable to detect global peak (GP) power point with the presence of several local peaks (LP). A hybrid Particle Swarm Optimization and Artificial Neural Network (PSO-ANN) algorithm is proposed in this article to detect the GP power. The PV system which consists of PV array, DC-DC boost converter, and a resistive load, were simulated using MATLAB/Simulink. The performance of the proposed algorithm is compared with that of the standard PSO algorithm. The proposed algorithm is tested and verified by hardware experiment. The simulation results and the experimental results are compared and discussed. It shows that the proposed algorithm performs well to detect the GP of the PV array under partial shaded conditions. In this work, the tracking efficiency of the proposed algorithm is in the range of 92.7-99.7 %.

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“…Several papers available in the literature try to define standardized procedures for assessing the MPPT efficiency of these algorithms [3][4][5], and many others propose optimized MPPT approaches, e.g. [6][7][8][9]. Unfortunately, most of these techniques have a limited field of practical applicability because they require high computational burden [6,7] and/or expensive hardware resources [8,9].…”

Section: Introductionmentioning

confidence: 98%

A two-steps algorithm improving the P&O steady state MPPT efficiency

2014

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A direct control based maximum power point tracking method for photovoltaic system under partial shading conditions using particle swarm optimization algorithm

Cited by 203 publications

References 37 publications

Global Maximum Power Point Tracking (MPPT) of a Photovoltaic Module Array Constructed through Improved Teaching-Learning-Based Optimization

Global Maximum Power Point Tracking (MPPT) of a Photovoltaic Module Array Constructed through Improved Teaching-Learning-Based Optimization

Photovoltaic Multiple Peaks Power Tracking Using Particle Swarm Optimization with Artificial Neural Network Algorithm

A two-steps algorithm improving the P&O steady state MPPT efficiency

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