Optimal reconfiguration of PV modules in an array without any constraint on structure by the use of genetic algorithm

Tazehkand, Mehdi Zarei; Fathi, S. H.; Eskandari, Aref; Milimonfared, Jafar

doi:10.1109/pedstc.2018.8343787

Cited by 6 publications

(2 citation statements)

References 12 publications

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“…A significant part of the research in this field has been investigating the effect of the used heuristic reconfiguration algorithm on system performance [2,7,[16][17][18][19][20][21][22][23][24][25][26][27][28][29].…”

Section: Literature Reviewmentioning

confidence: 99%

Automatic PV Array Reconfiguration under Partial Shading Conditions

Ikram Siddiq,

Fadhel,

Omar Anwar

2023

NTU-JRE

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Photovoltaic (PV) arrays have been recognized as one of the main clean renewable sources of electrical energy. In practice, PV arrays are subject to unavoidable non-uniform partial shading (PS) due to clouds, buildings, dust, etc. PS causes the hot spot problem, mismatch losses, and output power degradation. A widely used approach to mitigate the effect of PS is dynamic reconfiguration, where, the interconnection of PV panels is modified according to the shading condition to achieve maximum output. Dynamic reconfiguration techniques use sensors, a programmable controller, and a switch matrix for optimal operation. However, they have drawbacks such as system complexity and scalability issues. For instance, reducing the number of switches limits the flexibility of the reconfiguration algorithm. In this paper, an automatic dynamic reconfiguration scheme is proposed in which PV panel irradiation activity controls the interconnection of switches, without the need for a programmable controller. A modular building block is proposed from which easily scalable PV arrays can be constructed in a hierarchical manner. Experimental and analytic results have verified the effectiveness of the proposed reconfiguration scheme.

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Section: Literature Reviewmentioning

confidence: 99%

Automatic PV Array Reconfiguration under Partial Shading Conditions

Ikram Siddiq,

Fadhel,

Omar Anwar

2023

NTU-JRE

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“…In the work in Reference [35], an adaptive GA based reconfiguration technique is applied to a (4 × 4) SP PV array to maximize the output power of the PV array under the different pattern of partial shading conditions. In Reference [36], a GA based optimal reconfiguration technique is applied to a PV array to maximize the output power at partial shading condition. There are some other reconfiguration techniques are developed in References [25,37], to reduce MML due to partial shading.…”

Section: Introductionmentioning

confidence: 99%

Performance Comparison of Mismatch Power Loss Minimization Techniques in Series-Parallel PV Array Configurations

2019

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The mismatch in current-voltage (I-V) characteristics of photovoltaic (PV) modules causes significant power loss in a large PV array, which is known as mismatch power loss (MML). The PV array output power generation can be improved by minimizing MML using different techniques. This paper investigates the performance of different module arrangement techniques to minimize MML both for long series string (LSS) and long parallel branch (LPB) in series-parallel (SP) array configurations at uniform irradiance condition. To investigate the significance of MML LSS-SP configuration with dimensions: 1 × 40, 2 × 20, 4 × 10, 5 × 8 and LPB-SP configuration with dimensions: 40 × 1, 20 × 2, 10 × 4, 8 × 5 were used. A comparative analysis is made to find the effectiveness of MML reduction techniques on PV arrays with three different power ratings. Simulation results show that the PV modules arrangement obtained by the genetic algorithm (GA) and current based arrangement (Im) performed better than the arrangements obtained by all other techniques in terms of PV array output power and MML minimization. The performance of the proposed technique was analyzed for both LSS-SP and LPB-SP array configurations in 400 W, 3400 W, and 9880 W arrays. To substantiate the simulation results experiment was performed using a 400 W PV array in outdoor weather condition and obtained similar results. It was also observed that the percentage of recoverable energy (%RE) obtained by arranging the modules using the GA method was higher than Im based method for both LSS-SP and LPB-SP array configurations. A maximum %RE of 4.159 % was recorded for a 5 × 8 LSS-SP array configuration by applying the GA based MML reduction method.

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