Optimal reconfiguration of PV array based on digital image encryption algorithm: A comprehensive simulation and experimental investigation

2023

Energy Tech

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The photovoltaic array reconfiguration approach is the most promising solution to enhance the global maximum power (GMP) and improve the array characteristics by mitigating the variation between distinct rows, thereby reducing the computational burden on maximum power point tracking systems. However, the majority of the existing reconfiguration approaches inherently have many drawbacks such as scalability issues, poor shade dispersion, distorted array characteristics, numerous power peaks, augmented mismatch, etc. In order to address these issues, this article proposes a novel integer‐based Fibonacci transform technique using the idea of image encryption for reconfiguration. The proposed strategy is tested for both symmetric and asymmetric photovoltaic (PV) arrays under 19 shading cases. Further, its performance is compared with the 23 existing techniques. Besides, a nonparametric Wilcoxon signed‐rank sum test with a significant difference (p‐value) of 0.05 is used to perform a pairwise unbiased comparison of all the techniques. Due to the discriminate shade dispersion through intelligent reconfiguration, the proposed strategy delivers consistently superior performance yielding the respective GMP enhancement of 34.43%, 12.5%, 5.06%, and 37.39%, 22.94%, 16.5% for 9 × 9, and 4 × 8 PV arrays under distinct cases. The proposed algorithm is further validated using the Levenberg–Marquardt neural network‐based MPPT controller for a 7 kWp standalone PV system.

Section: Fibonacci Sequence and Its Transformmentioning

confidence: 99%

Solar Array Optimization Using Cryptographic Fibonacci Transformation for Global Power Enhancement and Ease of MPPT Controllers

2023

Energy Tech

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“…According to Kirchhoff's current law (KCL), the solar cell current is given as follows:

I_{italicPV_italiccell} goodbreak= I_{italicL_italiccell} goodbreak- I_{d} goodbreak- I_{sh}

where I pv_cell is the PV cell current, I L_cell denotes light‐produced current of PV cell, I d denotes the diode current, and I sh denotes shunt resistance current. By substituting I sh and I d in Equation (1), the cell current 37 can be computed as given

I_{italicPV_italiccell} goodbreak= I_{L_italiccell} goodbreak- I_{0} ([], \exp ((), q \frac{V_{cell} + I_{cell} R_{se}}{b normalσ T_{c}} goodbreak- 1)) goodbreak- \frac{V_{cell} + I_{cell} R_{se}}{R_{italicsh}}

where I o denotes diode saturation current, q denotes electron charge, V cell denotes PV cell voltage, σ denotes ideality factor, T c denotes operating temperature, b denotes Boltzmann's constant, R se denotes PV cell series resistance, R sh denotes shunt resistance. By considering a PV module comprising n s series‐connected cells, then the module current is given as

I_{m} goodbreak= I_{L} goodbreak- I_{0} ([], \exp ((), q \frac{V_{m} + I_{m} R_{s}}{n_{s} b normalσ T_{c}} goodbreak- 1)) goodbreak- \frac{V_{m} + I_{m} R_{SE}}{R_{italicSH}}

where I m denotes PV module current, q denotes electron charge, V m denotes PV module voltage, R SE denotes PV module series resistance, R SH denotes PV module shunt resistance, and I L denotes the light‐produced current of PV module, which is computed as given

I_{L} goodbreak= \frac{G}{{normalG}_{0}}

…”

Section: Modeling Of Solar Pv Arraymentioning

confidence: 99%

A novel scan pattern for reconfiguration of partially shaded photovoltaic arrays for maximum power extraction

2022

Circuit Theory & Apps

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Reconfiguration plays an indispensable role in augmenting the output of the photovoltaic (PV) array under partial shading conditions. Various reconfiguration schemes have been proposed in the literature to disperse the shade in partially shaded PV arrays. Nevertheless, most of these schemes can be employed only for less‐rated arrays, are not compatible with all array sizes, fails in effective shade dispersion over the entire array, and so forth. To overcome these shortcomings, a calligraphy‐based diagonal scan pattern is proposed to reconfigure the PV array to improve the row currents of the PV array thereby reducing the mismatch between them. The superiority of the proposed scheme is examined by comparing it with conventional Series‐Parallel, Total‐Cross‐Tied, and the existing image processing based‐Chaotic Baker Map, Odd‐Even, and Odd‐Even‐Prime configurations. Besides, the system is extensively studied for various symmetrical 9 × 9, 8 × 8, 4 × 4, and unsymmetrical 8 × 6 PV arrays under 34 distinct shading cases with various performance indices. An experimental laboratory prototype model of a 4 × 4 PV array reconfiguration system is developed and studied under distinct shading conditions. Subsequently, an inclusive economic analysis is also conducted, and it is noted that there is a notable enhancement in electricity units and revenue generation by executing the proposed reconfiguration scheme.

“…Hence, mitigating the LMPPs by equalizing the irradiation between the rows of the PV array through an efficient and intelligent reconfiguration process solves the problem to a maximum extent. 17 Reconfiguring the PV array not only mitigates the LMPPs but also enhances the GMP by a significant percentage due to the reduction in the mismatch. The recent developments and the existing research on various static and dynamic reconfiguration strategies have been reviewed in detail in Yang et al 18 The dynamic reconfiguration strategies encompass various optimization based, [19][20][21][22] electrical array reconfiguration (EAR) based, 23,24 artificial intelligence (AI) based, 25,26 adaptive array reconfiguration based, 27 and so forth.…”

Section: Introductionmentioning

confidence: 99%

“…Despite the recent advancements and vast investigations on improving the MPPT efficiency, tracking the GMP among the numerous power peaks remains challenging. Hence, mitigating the LMPPs by equalizing the irradiation between the rows of the PV array through an efficient and intelligent reconfiguration process solves the problem to a maximum extent 17 . Reconfiguring the PV array not only mitigates the LMPPs but also enhances the GMP by a significant percentage due to the reduction in the mismatch.…”

Section: Introductionmentioning

confidence: 99%

A novel hybrid image processing‐based reconfiguration with RBF neural network MPPT approach for improving global maximum power and effective tracking of PV system

Rao

2023

Circuit Theory & Apps

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SummaryThe solar photovoltaic (PV) array output is reduced significantly by the frequently occurring inevitable partial shading conditions. In consequence, the array exhibits multiple peaks in its characteristics that cause the conventional maximum power point tracking (MPPT) algorithms to get stuck at the local maximum. So, to track the global maximum power (GMP) among the multiple peaks, a novel radial basis function (RBF)‐based neural network approach has been proposed for predicting the optimal GMP. Additionally, a novel and intelligent encryption‐based ruler transform (RT) reconfiguration approach is proposed to disperse the shading effect enhancing the GMP and mitigating the multiple peaks. The effectiveness of the proposed RBF‐MPPT and novel RT‐reconfiguration strategies has been tested and analyzed for a 5 × 7 PV array under distinct dynamic, uniform, and nonuniform shading conditions. The results of the proposed RBF have been compared with the conventional incremental conductance (INC) algorithm before and after reconfiguration of the PV array. Further, the ease of GMP tracking by a simple conventional INC due to the reduction of peaks after the array reconfiguration under shading conditions has been demonstrated and discussed in detail. After reconfiguration, the GMP is enhanced by 37.35%, 31.41%, 30.86%, 21.46%, 13.69%, and 8.88%, using the proposed RBF for the considered five shading conditions. The steady‐state oscillations are also considerably mitigated by employing the proposed reconfiguration and RBF strategies.