Photovoltaic Array Reconfiguration Research Articles

PV Array Reconfiguration for Global Maximum Power Optimizing under Partial Shading Conditions based on PV Switched System

Background: Due to the partial shading effects on different photovoltaic (PV) modules in a PV array, PV module operating conditions are inconsistent, and PV array output power is significantly reduced. Although the maximum power point (MPP) of a non-uniform irradiance PV array can be observed through global maximum power point tracking (GMPPT), no evaluation of the array's energy potential has been done. Objective: One of the most effective solutions to overcome the negative effects of partial shading in PV systems is the PV array reconfiguration process. To optimize the electrical structure of the PV array as the PV modules are partially shaded in a non-uniform manner, this study proposes a promising technique for dynamic reconfiguring a PV array in order to improve the extracted maximum power from a PV array under partial shading conditions (PSC). Methods: PV modules are rearranged by iteratively sorting them to allow the PV array with nonuniform irradiance to produce as much power as possible. This is conducted by applying a switching matrix to implement a PV-switched system approach. The proposed system with different PV array dimensions (e.g., 3×4, 4×6, and 5×8) is assessed in order to validate the proposed algorithm. A MATLAB/Simulink PV array developed model is used to find the global maximum power point for the different PV array dimensions in both pre-reconfiguration and post-reconfiguration states. Results: A detailed numerical comparison of the extracted power from the proposed system has been provided. Conclusion: The results show that the proposed system has the potential to extract the exact global maximum power for a PV-switched system under PSC, irrespective of array dimensions, according to simulation results.

Backpropagation artificial neural network-based maximum power point tracking controller with image encryption inspired solar photovoltaic array reconfiguration

The enhancement of photovoltaic (PV) arrays through reconfiguration presents a promising avenue for increasing the global maximum power (GMP) and improving overall array performance. This enhancement is achieved by minimizing differences between rows, thereby reducing the computational load on Maximum Power Point Tracking (MPPT) systems. However, many existing reconfiguration methods face various challenges, including scalability issues, inadequate shading dispersion, distortion of array characteristics, emergence of multiple power peaks, increased mismatch, and more. In order to overcome these obstacles, this study presents a novel method for array reconfiguration that is modelled after the widely used Kolakoski Sequence Transform in picture encryption. The suggested approach is assessed in eight different scenarios with 9 × 9 and 5 × 5 PV arrays shaded differently. Its performance is compared against seven established techniques. Due to its intelligent reconfiguration aimed at minimizing shade dispersion, the suggested approach consistently outperforms alternative methods. It results in substantial improvements in GMP, enhancing it by 32.79%, 14.98%, 10.15%, and 4.13% for 9 × 9 arrays, and 37.10%, 14.36%, and 9.88% for 5 × 5 arrays across diverse conditions. Furthermore, this study comprehensively investigates three separate Artificial Neural Network algorithms, specifically the Levenberg-Marquardt (LMB), Scaled Conjugate Gradient, and Bayesian Regularization algorithms for MPPT. A Levenberg-Marquardt Backpropagation-based MPPT controller for a 250Wp standalone PV system is used to validate the effectiveness of the recommended configuration. This integrated approach, which combines reconfiguration and LMB-based MPPT utilizes only two sensors regardless of array size. It achieves accelerated convergence tracking within a short 0.13 s, displaying minimal steady-state oscillations.

Dynamic reconfiguration of photovoltaic arrays for laser wireless power transmission via Deep neural networks

Dynamic reconfiguration of photovoltaic arrays for laser wireless power transmission via Deep neural networks

A Scalable Hierarchical Dynamic PV Array Reconfiguration under Partial Shading

Photovoltaic (PV) arrays are often affected by partial shading (PS), which can significantly reduce their power output. Dynamic reconfiguration is a promising technique for mitigating the negative effects of PS by adjusting the electrical connections of the PV modules in real-time. This paper introduces a hierarchical-based switching block scheme for the dynamic reconfiguration of PV arrays under PS conditions. With the aim of mitigating the negative impact of PS on PV arrays, the proposed system employs a low complexity and easily scalable architecture, making it well-suited for practical applications. Comparative assessments against conventional configurations such as bridge-linked (BL), total-cross-tied (TCT), and series–parallel (SP) reveal superior energy harvesting efficiency for the proposed system under various shading conditions. The hierarchical switching block architecture, featuring multiple levels of switching blocks, enables efficient and flexible reconfiguration of the PV array, even in the presence of complex shading patterns. Through extensive simulations, the system consistently outperforms conventional configurations by adapting effectively to changing shading patterns and optimizing the PV array’s output. The proposed switching block (SB) reconfiguration technique significantly outperforms existing methods like TCT, Sudoku, dynamic proposals, and Magic Square in terms of both power generation (up to 42.52% increase) and efficiency (up to 42.13% improvement) under diverse partial shading conditions. The proposed hierarchical-based switching block scheme thus presents a promising solution for enhancing the dynamic reconfiguration of PV arrays under PS conditions, offering a balance between low complexity, scalability, and superior energy harvesting efficiency for practical applications in the realm of solar energy.

A novel shadow dispersion approach for solar PV modules in array using chess board game methodology: An experimental study

In the global scenario, photovoltaic (PV) systems contribute much power compared to other renewable energy (RE) sources due to their benefits, e.g., environmental friendliness, low maintenance, and the small investment required for efficient energy harvest. However, it experiences performance limitations due to adverse climatic conditions, i.e., temperature and sun irradiance variations. Partial shadowing circumstances (PSCs) have a negative effect on PV modules, leading to a shift in irradiance and diminished PV performance in terms of power loss (PL), performance ratio (PR), and reduced fill factor (FF). In this paper, the modification of PV module interconnections in an array system shows the power loss reduction under PSCs. The chess board game theory (CBGT) based PV array reconfiguration technique shows efficient results in terms of shade dispersion on the entire PV array to diminish the shading effect. Novel CBGT configuration (9 × 9 size) shows minimum PL and higher global maximum power point (GMPP) compared to existing series–parallel (SP), total-cross-tied (TCT), and puzzle-based Su-Do-Ku (SDK) and puzzle game theory (PGT) PV configurations. The CBGT configuration achieves higher performance in power GMPP (315.8 W, 273.6 W, 232.8 W, and 262.1 W) under four shading instances experimentally.

Optimal PV array configurations for partial shading conditions

Increasing the effectiveness of photovoltaic (PV) power generation systems is a major barrier to their widespread use. Partial shading conditions (PSCs), which are caused by nearby objects like trees, buildings, and clouds, reduce the energy produced by PV systems and may be mitigated by the reconfiguration of PV arrays. A novel approach dubbed a modified series-parallel (MSP) setup, was suggested in this paper and compares its performance to four PV configuration strategies: series-parallel (SP), total-cross-tied (TCT), bridge-linked (BL), and honey-comb (HC). A 3×3 solar array is used in five partial shading arrangements. MATLAB/Simulink simulates all shading conditions. This study indicated that MSP delivers high performance and is superior to all other configurations in terms of maximum power in even and uneven row-shaded cases. in the case of an even column shaded, the performance of (SP, BL, HC, and TCT) was equal in terms of the maximum power obtained, while MSP was the least in comparison. the performance of the TCT configuration was the best compared to the other configuration when shading the PV system vertically unevenly. Finally, for diagonal shading, TCT and MSP configurations work best. Shading loss, mismatch loss and fill factor (FF) results were also compared.

Modeling and performance analysis of novel quad‐tied PV array configuration under partial shading conditions

AbstractA photovoltaic (PV) cell is the smallest unit in an array that exhibits nonlinear characteristic curves. To gather the maximum amount of energy from a PV array under partial shading conditions (PSCs), it is necessary to follow the largest peak in the power–voltage (P–V) curve. PV cells are partially or totally shaded due to atmospheric conditions, which show multiple peaks in the PV curve. To overcome the losses occurring due to PSCs, PV array reconfiguration action is advisable. The authors of this work proposed a novel quad‐tied PV array configuration and compared its performance to that of other current configurations such as series‐parallel, total‐cross tied, and others in terms of global maximum power point tracking, mismatch loss, fill factor, and efficiency. The MATLAB/Simulink 2020a platform was used to generate PV array curves under various shading conditions.

Photovoltaic Array Dynamic Reconfiguration Based on an Improved Pelican Optimization Algorithm

After prolonged operation, external objects may obstruct the photovoltaic (PV) array, resulting in prolonged partial shading. The dynamic reconfiguration of PV arrays uses a switch matrix to change the electrical positions of the PV cells in the array, and it is an effective method to solve the problem of partial shading. Most of the current dynamic reconfigurations only consider the optimization of power output. Neglecting the switch actions will increase the number of switch matrix actions, making the switch control more complex and reducing the lifespan of devices. To address power optimization and switch action optimization simultaneously during dynamic reconfiguration, this paper introduces a novel objective function. This function combines power optimization and switch action optimization in a weighted manner. Based on the novel function, the algorithm prioritizes optimizing the electrical positions of PV cells with larger shading values. This ensures that the PV array can improve its output while significantly reducing the number of switch actions. The Pelican Optimization Algorithm (POA) is improved and employed to optimize the proposed objective function. In terms of the output power optimization, the effectiveness of the novel objective function with the improved POA is validated by comparing and analyzing the reconfiguration results with the conventional objective functions under four shading scenarios. The results demonstrate that the novel objective function with the improved POA increases the output power by 30% in short and wide shadow and achieves the highest power output. Moreover, the tests conducted on dynamic reconfiguration results with different weights validate the effectiveness of the novel objective function in minimizing switching actions while improving power output.

Innovative Methodologies for Higher Global MPP of Photovoltaic Arrays under PSCs: Experimental Validation

Partial shading conditions (PSCs) are responsible for the root causes of photovoltaic (PV) system performance deprivation such as hotspots (damaged PV cells), mismatch power losses and multiple power maxima. Recently, PV array reconfiguration strategies have proven to be beneficial in improving PV system performance and achieving improved shade dispersion properties. This research analyzes the improved Su-Do-Ku (I-SDK) PV array configuration in order to counteract the shading effect. This approach implements a 6 × 6 size PV array configuration and performance evaluation under different realistic shading scenarios. The performance of the I-SDK configuration is assessed and compared to that of the total-cross-tied (TCT) and Su-Do-Ku (SDK) arrangements. The performance indices such as power loss (PL), power at global maximum power point (GMPP), fill-factor (FF), performance ratio (PR), power enhancement (PE) and execution ratio (ER) are analyzed to show comprehensive comparison. An experimental analysis confirms the MATLAB/Simulink findings, demonstrating that the I-SDK configuration outperforms both the TCT and SDK array setups. The GMPP values of 143.5 W, 141.7 W, 138.1 W and 129.3 W also show the superiority of I-SDK during four shading instances compared to conventional SP, TCT, SDK and SM arrangements. Moreover, under similar PSCs, higher %FF (74.61%, 76.10%, 77.1%, 75.92%) and lower PL (36.7 W, 38.5 W, 42.1 W, 50.9 W) support the adoptability of I-SDK for experimental validation/commercial viability.

A novel PV array reconfiguration technique based on circular array data structure

Partial shading condition (PSC) poses a significant challenge to solar power generation as it has a severe impact on the performance of photovoltaic (PV) systems, leading to a decrease in energy yield and reliability. Reconfiguration of PV arrays is a potential technique to deal with this challenge, however, reconfiguration techniques proposed in the past are restricted in their suitability for practical implementations in real-world installations as they are only optimal for specific shading patterns. To overcome this limitation, the article introduces a novel reconfiguration approach inspired by the circular array data structure, a commonly utilized tool in the realm of computer science. The proposed circular array transformation (CAT) technique shows great potential in mitigating the impact of partial shading (PS) and maximizing the overall power generation across a wider range of PSCs. The effectiveness of the proposed technique is validated through simulations and experimental studies conducted on a 5 × 5 PV array. Furthermore, the scalability of the proposed reconfiguration technique is verified through extensive simulations on a 9 × 9 PV array. Comparative analysis reveals that the proposed CAT rearrangement approach exhibits clear dominance and outperforms existing and recently published state-of-the-art reconfiguration methods.

Augmenting Power Efficiency by Virtue of a Novel Physical Reconfiguration of Solar Photovoltaic Array in Tandem with Experimental Validation

The growing interest in solar energy has led to large photovoltaic (PV) energy parks in today's world. Though the commonly used total‐cross‐tied (TCT) interconnection scheme reduces mismatch losses (MLs), the occurrence of partial shading on massive PV arrays (PVAs) reduces the output power. It invokes numerous local maximum power points (LMPPs) on the power–voltage (P–V) profiles. To counteract the undesired LMPPs, reconfiguration of PVAs is done either through electrical or physical reconfiguration methods. In this respect, physical relocation scheme is more economical for better distribution of partial shade. A novel greater‐than‐SuDoKu (GTS) topology is presented in this paper for achieving physical rearrangement of PV modules amalgamated with TCT interconnection scheme. For analysis, five shading cases are considered and obtained results are compared with conventional TCT and 10 newly established methods. In general, the proposed GTS strategy has shown its eminence in receiving a smoother P–V characteristic, enhanced efficiency, better fill factor, and reduced MLs, which ranges up to 1343 W. Moving forward, herein, the efficacy of the proposed reconfiguration scheme is validated, under the influence of partial shading conditions, through an experimental lab prototype for a 3 × 3 PVA.

Disperse Partial Shading Effect of Photovoltaic Array by Means of the Modified Complementary SuDoKu Puzzle Topology

This paper presents a novel modified Complementary SuDoKu puzzle (MC-SDKP) topology for the static reconfiguration of photovoltaic (PV) arrays. It was developed with the aim of enhancing the power output of a PV array which is exposed to partially shaded conditions (PSCs). To disperse patterns of both center shading and corner shading, the MC-SDKP technique modified and combined the Optimal SDKP and the Complementary SDKP (C-SDKP) topologies. An 8 × 8 PV array configured with the MC-SDKP topology was exposed to nine different shading patterns, and its performance was compared with that of the other four topologies. The results of the performance evaluation confirmed that, when configured according to the MC-SDKP, the PV array produced the highest average power output among all five topologies, with a 15.07% higher output on average than the total-cross tied. The PV array with the MC-SDKP topology also exhibited the lowest average power loss (1.34%). This study clearly established the effectiveness of the MC-SDKP topology at mitigating the effects of both center and corner shading. The advantages of the MC-SDKP reconfiguration technique are: an increase in extracted power, a reduction in current mismatch losses, an improvement in shade dispersion under conditions of center shading, and good scalability.

Dynamic Reconfiguration Method of Photovoltaic Array Based on Improved HPSO Combined with Coefficient of Variation

In order to address the issue of power loss resulting from partial shadow and enhance the efficiency of photovoltaic power generation, the photovoltaic array reconfiguration technology is being increasingly utilized in photovoltaic power generation systems. This paper proposes a reconfiguration method based on improved hybrid particle swarm optimization (HPSO) for the photovoltaic array of TCT (total-cross-tied) structure. The motivation behind this method is to get the best reconfiguration scheme in a simple and efficient manner. The ultimate goal is to enhance the output power of the array, save energy, and improve its overall efficiency. The improved HPSO introduces the concept of hybridization in genetic algorithms and adopts a nonlinear decreasing weight method to balance the local search and global search ability of the algorithm and prevent it from falling into the local optimal solution. The objective function used is the variation coefficient of the row current without the weight factor. This approach saves time and balances the row current of the array by altering the electrical connection of the component. In the 4 × 3 array, the improved HPSO is compared with the Zig-Zag method. In the 9 × 9 array, the improved HPSO is compared with the CS (competence square) method and the improved SuDoKu method. The simulation results show that the power enhancement percentage of the improved HPSO is between 6.39% and 28.26%, and the power curve tends to single peak characteristics. The improved HPSO has a smaller mismatch loss and a higher fill factor in the five shadow modes, which can effectively improve the output power, and it is convenient to track the maximum power point later.

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

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.

A Novel Row Index Mathematical Procedure for the Mitigation of PV Output Power Losses during Partial Shading Conditions

Energy demand forecasted for the next several years has been bench marked due to the massive need for electrical energy. Solar power plants have earned a great marketplace position in recent years, but also face challenges in terms of power dissipation due to the frequent occurrence of shade. As a result, the per unit solar electricity price increases drastically. There is an immense need to ensure the maximum dependable power conversion efficiency of Photovoltaic (PV) systems by mitigating power output losses during partial shading conditions. The reconfiguration of PV arrays is a useful, effective, and promising approach in this context. Though several reconfiguration techniques have been developed in recent years, their applicability to real-time power plants is debatable due to the requirement of many physical relocations, long interconnecting ties, and complexity. This research work proposes a novel row index mathematical procedure followed by a technique in which the reconfiguration matrix indexes are filled with a unique number so that no row number repeats in the same row and column. Additionally, the proposed approach uses small number of switches that reduce the cost as well as the computational complexity. To strengthen the analysis, very recent techniques such as Sudoku, Total Cross Tied (TCT), Chess-Knight, and Particle Swarm Optimization (PSO) based reconfiguration are compared against five different shading patterns. It has been observed that approximately 68% power loss is mitigated in TCT configuration. It is worth noting that it results in higher PV output power than the existing latest reconfiguration techniques such as PSO, Chess-Knight, Sudoku, and others.

Photovoltaics literature survey (No. 181)

Photovoltaics literature survey (No. 181)

A review of PV array reconfiguration techniques for maximum power extraction under partial shading conditions

Partial shading is a significant obstacle to the effective use of photovoltaic (PV) systems because it reduces output power significantly. The output power reduction is not proportional to the shaded area but rather depends on the PV array configuration/reconfiguration and shadowing pattern. PV array reconfiguration is one of the most effective solutions for overcoming the adverse effects of partial shading in PV systems. The main objective of PV array reconfiguration strategies is to disperse shades consistently over the entire area of the PV array to reduce the adverse impact of partial shading situations. This paper provides an in-depth examination of the significant existing PV array reconfiguration methods used to address the problem of partial shading. The various methods are evaluated and compared based on their techniques, benefits, and drawbacks. This work is an interesting reference for researchers in the field and a simple guide for beginners on PV array reconfiguration.

An innovative competence square technique for PV array reconfiguration under partial shading conditions

ABSTRACT The power generated by the photovoltaic (PV) array reduces drastically due to irregular solar irradiation. Shading pattern, shaded area, and array configuration are the main causes of reduction in power generation. The electrical characteristics of the modules in the array possess several peaks due to the fact that they produce distinct row currents and have various peaks in their electrical characteristics. Therefore, an appropriate technique is needed to minimize the row current difference that leads to maximum power generation at a higher level. This can be achieved by array reconfiguration; therefore, an Innovative Competence Square technique is proposed in this paper. The proposed technique disperses the shade effectively over the entire array by displacing the modules. The MATLAB simulation was run under three distinct shading conditions to validate the proposed technique’s performance, and it has been compared to the Competence Square technique and TCT interconnection. The technique’s benefits can be seen in terms of increased power generation, FF, and reduced mismatch losses.

Performance of PV array configurations under dynamic partial shadings

The partial shading effect (PSE) is responsible for most power losses in a photovoltaic (PV) system. By modifying the interconnections between PV modules, called PV array reconfiguration, it is possible to improve the power output under partial shading conditions (PSCs). Compared to research on static PSCs, the impact of dynamic PSCs on PV arrays is rarely mentioned, although it deserves to be studied. This paper studies the dynamic PSE on four traditional PV configurations and two reconfiguration techniques based on a 5 × 5 PV array. The four traditional PV configurations are Series-Parallel (SP), Bridge-Link, Honey-Comb, and Total-Cross-Tied (TCT). The two reconfiguration techniques are SuDoKu (SDK) representing Physical Array Reconfiguration (PAR) and Electrical Array Reconfiguration (EAR). The dynamic PSCs are simplified to three types based on the varying orientation: horizontal, vertical, and diagonal. Simulations are carried out with Matlab & Simulink. The performance comparison for the four traditional PV array and two reconfiguration techniques is based on daily energy losses. The results show that four traditional PV configurations techniques, in all PSCs' scenarios, EAR has the most stable performance and the lowest energy losses. The energy losses of SP connection are the largest in all PSCs cases. Although their performance varies depending on the partial shading case, Total-Cross-Tied and SudoDKu lead to the lowest energy losses.

A hybrid approach to modelling and analyzing reconfiguration of photovoltaic arrays under partial shading conditions

A hybrid approach to modelling and analyzing reconfiguration of photovoltaic arrays under partial shading conditions