A Particle Swarm Optimization-Based Maximum Power Point Tracking Algorithm for PV Systems Operating Under Partially Shaded Conditions

Liu, Yi-Hwa; Huang, Shyh-Ching; Huang, Jiao; Liang, Wen-Cheng

doi:10.1109/tec.2012.2219533

Cited by 478 publications

(222 citation statements)

References 36 publications

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“…The proposed EGWO algorithm is compared with conventional GWO MPPT algorithm (Satyajit et al 2016) and most implemented Particle Swarm Optimization MPPT algorithms (Liu et al 2012) under similar conditions. The parameters of three algorithms are mentioned in Appendix.…”

Section: Comparative Analysismentioning

confidence: 99%

“…Several authors proposed MPPT algorithms based on Particle Swarm Optimization -Liu et al 2012, Artificial Bee Colony (Sundareswaran et al 2015), Ant Colony Optimization (Jiang et al 2013), Cuckoo Search (Ahmed et al 2014), Firefly (Sundareswaran et al 2014), Grey Wolf Optimizer (Satyajit et al 2016) and Whale Optimization Algorithm (Santhan et al 2016). All these algorithms differ noticeably in terms of accuracy, efficiency, tracking time and complexity (Jordehi 2016).…”

Section: Introductionmentioning

confidence: 99%

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Enhanced Grey Wolf Optimizer Based MPPT Algorithm of PV System Under Partial Shaded Condition

Cherukuri

Rayapudi

2017

Int. J. Renew. Energy Dev.

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ABSTRACT:Partial shading condition is one of the adverse phenomena which effects the power output of photovoltaic (PV) systems due to inaccurate tracking of global maximum power point. Conventional Maximum Power Point Tracking (MPPT) techniques like Perturb and Observe, Incremental Conductance and Hill Climbing can track the maximum power point effectively under uniform shaded condition, but fails under partial shaded condition. An attractive solution under partial shaded condition is application of meta-heuristic algorithms to operate at global maximum power point. Hence in this paper, an Enhanced Grey Wolf Optimizer (EGWO) based maximum power point tracking algorithm is proposed to track the global maximum power point of PV system under partial shading condition. A Mathematical model of PV system is developed under partial shaded condition using single diode model and EGWO is applied to track global maximum power point. The proposed method was programmed in MATLAB environment and simulations are carried out on 4S and 2S2P PV configurations for dynamically changing shading patterns. The results of the proposed method were analyzed and compared with GWO and PSO algorithms. It was observed that proposed method is effective in tracking global maximum power point with more accuracy in less computation time compared to other methods.

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Section: Comparative Analysismentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Enhanced Grey Wolf Optimizer Based MPPT Algorithm of PV System Under Partial Shaded Condition

Cherukuri

Rayapudi

2017

Int. J. Renew. Energy Dev.

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“…It is depicted from this figure that, PV is working at MPP with tracking efficiency of 99.94%. The MPP tracking efficiency has been calculated by taking the ratio between averaged output power obtained under steady state and maximum available power of the PV array [11]. As the solar Array Simulator from Agilent Technologies (E4360A) has been used here, the maximum available power, P max is the maximum power point of the PV module.…”

Section: Experimental Validation Of Single Phase Semi-z-source Invertmentioning

confidence: 99%

“…In the past literature many techniques and algorithms for tracking the maximum power from the PV array have been discussed. These techniques include perturb and observe (P&O) [7], incremental conductance [8,9], particle swarm optimization [10,11], fuzzy control [12,13], neural network based schemes [14], etc. Perturb and observe and incremental conductance algorithms are the most used among these algorithms because of their suitability and simplicity to implement for any PV array as well as during implementation no information about the PV array is required.…”

Section: Introductionmentioning

confidence: 99%

A Single Phase Doubly Grounded Semi-Z-Source Inverter for Photovoltaic (PV) Systems with Maximum Power Point Tracking (MPPT)

2014

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Abstract:In this paper, a single phase doubly grounded semi-Z-source inverter with maximum power point tracking (MPPT) is proposed for photovoltaic (PV) systems. This proposed system utilizes a single-ended primary inductor (SEPIC) converter as DC-DC converter to implement the MPPT algorithm for tracking the maximum power from a PV array and a single phase semi-Z-source inverter for integrating the PV with AC power utilities. The MPPT controller utilizes a fast-converging algorithm to track the maximum power point (MPP) and the semi-Z-source inverter utilizes a nonlinear SPWM to produce sinusoidal voltage at the output. The proposed system is able to track the MPP of PV arrays and produce an AC voltage at its output by utilizing only three switches. Experimental results show that the fast-converging MPPT algorithm has fast tracking response with appreciable MPP efficiency. In addition, the inverter shows the minimization of common mode leakage current with its ground sharing feature and reduction of the total harmonic distortion (THD) as well as DC current components at the output during DC-AC conversion.

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“…It is possible for conventional algorithms to be trapped on a local maximum [9,10]. Many MPPT algorithms have been proposed for the PS condition [11][12][13][14][15], however they are complicated and/or require long tracking times.…”

Section: Introductionmentioning

confidence: 99%

Improvement of Shade Resilience in Photovoltaic Modules Using Buck Converters in a Smart Module Architecture

2018

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Partial shading has a nonlinear effect on the performance of photovoltaic (PV) modules. Different methods of optimizing energy harvesting under partial shading conditions have been suggested to mitigate this issue. In this paper, a smart PV module architecture is proposed for improvement of shade resilience in a PV module consisting of 60 silicon solar cells, which compensates the current drops caused by partial shading. The architecture consists of groups of series-connected solar cells in parallel to a DC-DC buck converter. The number of cell groups is optimized with respect to cell and converter specifications using a least-squares support vector machine method. A generic model is developed to simulate the behavior of the smart architecture under different shading patterns, using high time resolution irradiance data. In this research the shading patterns are a combination of random and pole shadows. To investigate the shade resilience, results for the smart architecture are compared with an ideal module, and also ordinary series and parallel connected architectures. Although the annual yield for the smart architecture is 79.5% of the yield of an ideal module, we show that the smart architecture outperforms a standard series connected module by 47%, and a parallel architecture by 13.4%.

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A Particle Swarm Optimization-Based Maximum Power Point Tracking Algorithm for PV Systems Operating Under Partially Shaded Conditions

Cited by 478 publications

References 36 publications

Enhanced Grey Wolf Optimizer Based MPPT Algorithm of PV System Under Partial Shaded Condition

Enhanced Grey Wolf Optimizer Based MPPT Algorithm of PV System Under Partial Shaded Condition

A Single Phase Doubly Grounded Semi-Z-Source Inverter for Photovoltaic (PV) Systems with Maximum Power Point Tracking (MPPT)

Improvement of Shade Resilience in Photovoltaic Modules Using Buck Converters in a Smart Module Architecture

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