Commercial Photovoltaic Research Articles

Performance Investigation of Tempered Glass-Based Monocrystalline and Polycrystalline Solar Photovoltaic Panels

Solar photovoltaic (PV) converts sunlight into electricity and is an appropriate alternative to overcome the depletion of conventional fuels and global warming issues. The performance of a PV panel may vary with respect to PV cell technology, fabrication methods, and operating conditions. This research aims at performing an experimental study to investigate the electrical performance of novel tempered glass-based PV panels using two different types of solar cells: monocrystalline and polycrystalline. Tempered glass-based panels are modified forms of commercial PV panels, in which ethylene-vinyl acetate (EVA) and Tedlar are not utilized. This new fabrication method was carried out in this research. Real-time data recordings regarding the PV electrical characteristics ( I - V curve) and solar irradiance were conducted under Malaysian weather conditions on clear sunny days. Results indicated that, at solar irradiance of 900 W/m2, the outputs from the fabricated polycrystalline and monocrystalline PV panels were 67.4 W and 75.67 W, respectively. However, at the highest average solar irradiance (634.61 W/m2), which was obtained at 12:30 PM, the outputs from both panels were 47.87 W and 54.89 W. An I - V curve was obtained for the real-time weather. The electrical efficiencies of the two PV panels were analyzed to be 10.54% and 12.23%.

Implementation of adjustable variable step based backstepping control for the PV power plant

The most recent research challenge in sustainable photovoltaic (PV) energy is to maintain a high efficiency of PV arrays. Our contribution in this issue is reducing the power loss caused by environmental condition change and parametric variations. A non linear recursive Backstepping maximum power point tracking (MPPT) controller based on an adjusted variable step Perturb and Observe (P&O) algorithm (VS-Backstepping) is proposed to gather the maximum power with fast converge time from the PV system. The trade off between the high accuracy and the fast tracking speed cannot be realized through single MPPT techniques. Thus this work combines two individual MPPT controllers. However, the accuracy for finding the maximum power is highly related to the part of MPP tracking control using the Backstepping approach as well as the rapidity to reach the MPP is managed with the adjusted variable step P&O algorithm. To further evaluate the effectiveness of the proposed method (VS-Backstepping), simulation and experimental results on a commercial PV panel are presented and compared to an individual fixed step P&O algorithm and a variable step P&O (VS-P&O) controller.

Reliability-based trade-off analysis of reactive power capability in PV inverters under different sizing ratio

Due to the intermittent characteristic of solar irradiance, photovoltaic (PV) inverters usually operate below rated power conditions. In this scenario, commercial PV inverters can be used to provide ancillary services, such as reactive power compensation. On the other hand, over-sizing PV inverters by increasing the number of installed PV panels can increase the generated energy during low irradiance conditions. Despite the advantages, both approaches can increase the PV inverter wear-out, leading to early failures. The trade-off between reactive power compensation and lifetime consumption under different inverter sizing ratios (ISR) was not previously addressed in the literature. Hence, this paper proposes to evaluate the system-level reliability of a single-phase two-stage PV inverter performing reactive power compensation. The analysis is carried out from three different mission profiles (Aalborg, Goiânia, and Izaña). The thermal loading on the inverter components is translated to lifetime prediction. The results from Goiânia show that the PV inverter lifetime is reduced from 22.6 to 6.2 years when compensating reactive power. In addition, this reduction is observed in all three regions, going from 40.8 to 12.4 years and 10 to 4.4 years, for Aalborg and Izaña, respectively. To improve the lifetime, a reactive power capability factor QR is applied to the maximum reactive power condition. The unreliability map is presented as a tool to match the inverter sizing ratio with reactive power capability in agreement with lifetime requirements. An economic analysis based on Levelized Cost of Electricity (LCOE) showed that the reactive power compensation increases the costs of the system installed in Goiânia with ISR = 100 % by 46.6 % in comparison with the conventional operation. These additional costs can be reduced if the reactive power is partially compensated.

Impact of Potential‐Induced Degradation on Different Architecture‐Based Perovskite Solar Cells

Organic–inorganic perovskites photovoltaic materials are considered as one of the promising candidates for the emerging photovoltaic (PV) sector. It has drawn tremendous attention from fundamental research and PV industries, due to its high efficiency, chemical properties, and low fabrication cost. But, its lifetime under real field operation is always the major obstacle toward commercialization. Potential‐induced degradation (PID) is known as the common reliable threat in the established commercial PV technologies which lead to catastrophic failure within a short time. Thus, it is essential to enable reliability assessment of PID on the precommercial development stage of perovskite photovoltaics to further enrich the confidence by identifying, eliminating, and developing an understanding of the possible degradation mechanism in the field condition. In this article, different architecture‐based perovskite solar cells are studied to reveal the degradation mechanism under PID for the first time. The results show that PSCs of n–i–p with a phenyl C61 butyric acid methyl ester (PCBM) layer have good stability under PID compared with other treated structures with only 4% degradation after 18 h.

Parameter estimation of triple diode photovoltaic model using an artificial ecosystem‐based optimizer

This manuscript proposes a modern optimization framework for parameter extraction of a triple-diode model of the unknown solar cell and Photovoltaic (PV) module parameters. The suggested optimization framework is based on applying a new metaheuristic optimization algorithm called Artificial Ecosystem-based Optimizer (AEO) to determine the nine unknown parameters of the triple-diode model of PV equivalent circuit model. Fitting the experimental data is the main objective of the extracted unknown parameters to develop a generic PV model. In this context, the root means squared error (RMSE) between the measured and estimated data is considered as the primary objective function. This objective function achieves the closeness degree between the estimated and experimental data. On the way to accomplish this study, the proposed AEO is carried out on three different commercial PV cells/modules. To assess the proposed algorithm, a comprehensive comparison study is used compared with several well-matured optimization algorithms reported in the literature. The attained numerical results prove the high precision and fast response of the proposed AEO algorithm for identifying multiple PV models.

Buck-based DMPPT emulator: a helpful experimental demonstration unit

<span lang="EN-GB">Distributed control strategyrepresents the most promising solution to enhance the lackluster energetic performance of mismatched PhotoVoltaic (PV) systems. Moreover, many factors that contribute to such poor performance are still to be explored. To fully understand the advantages offered by the Distributed Maximum Power Point Tracking (DMPPT) approach, the implementation of a DMPPT emulator is necessary. Based on the above needs, this paper describes the realization and use of a Buck based DMPPT emulator and shows its high flexibility and potential. The realized device is capable to emulate the output current vs. voltage (I-V) characteristics of many commercial PV modules with a dedicated Buck DC/DC converter not only in controlled atmospheric conditions but also with different currents rating of the switching devices. The system implementation is based on a commercial power supply controlled by a low-cost Arduino board. Data acquisition is performed through a low-cost current and voltage sensor by using a multichannel board by National Instruments. Experimental results confirm the validity and potential of the proposed DMPPT emulator.</span>

Fuzzy Logic Approach for Maximum Power Point Tracking Implemented in a Real Time Photovoltaic System

Photovoltaic (PV) panels are devices capable of converting solar energy to electrical without emissions generation, and can last for several years as there are no moving parts involved. The best performance can be achieved through maximum power point tracking (MPPT), which is challenging because it requires a sophisticated design, since the solar energy fluctuates throughout the day. The PV used in this research provided a low output voltage and, therefore, a boost-converter with a non-linear control law was implemented to reach a suitable end-used voltage. The main contribution of this research is a novel MPPT method based on a voltage reference estimator (VRE) combined with a fuzzy logic controller (FLC) in order to obtain the maximum power from the PV panel. This structure was implemented in a dSpace 1104 board for a commercial PV panel, PEIMAR SG340P. The scheme was compared with a conventional perturbation and observation (P&O) and with a sliding mode controller (SMC), where the outcomes demonstrated the superiority of the proposed advanced method.

MODELS, DETECTION METHODS, AND CHALLENGES IN DC ARC FAULT: A REVIEW

The power generation of solar photovoltaic (PV) technology is being implemented in every nation worldwide due to its environmentally clean characteristics. Therefore, PV technology is significantly growing in the present applications and usage of PV power systems. Despite the strength of the PV arrays in power systems, the arrays remain susceptible to certain faults. An effective supply requires economic returns, the security of the equipment and humans, precise fault identification, diagnosis, and interruption tools. Meanwhile, the faults in unidentified arc lead to serious fire hazards to commercial, residential, and utility-scale PV systems. To ensure secure and dependable distribution of electricity, the detection of such hazards is crucial in the early phases of the distribution. In this paper, a detailed review of modern approaches for the identification of DC arc faults in PV is presented. In addition, a thorough comparison is performed between various DC arc-fault models, characteristics, and approaches used for the identification of the faults.

A novel equivalent circuit-based model for photovoltaic sources

This paper presents a novel circuit-based model of photovoltaic (PV) source (cell, module or array) that can be easily integrated into any circuit-oriented simulators such as PSpice, PSCAD/EMTDC, PSIM, PowerSys of MATLAB/Simulink, etc. This proposed model is able to simulate accurately any commercial PV module behavior either exposed to uniform or non-uniform irradiance distributions. Moreover, it can also simulate perfectly PV arrays behavior in large scale PV systems. It is mainly derived from the conventional one-diode equivalent circuit model, which consists of a current source, a diode and two resistors. By modifying the linear part of this latter and including implicitly the effect of weather parameters (irradiance and cell temperature) on the circuit elements, our proposed model will encompass two types of dependent sources (voltage and current sources) and two resistances.To validate the truthfulness of the proposed novel model, comparisons between simulated and outdoor measured I-V characteristics on commercial PV module are done. Preliminary results have shown promising outputs and accuracy of this model.

Parameters Identification of PV Triple-Diode Model Using Improved Generalized Normal Distribution Algorithm

To simulate the behaviors of photovoltaic (PV) systems properly, the best values of the uncertain parameters of the PV models must be identified. Therefore, this paper proposes a novel optimization framework for estimating the parameters of the triple-diode model (TDM) of PV units with different technologies. The proposed methodology is based on the generalized normal distribution optimization (GNDO) with two novel strategies: (i) a premature convergence method (PCM), and (ii) a ranking-based updating method (RUM) to accelerate the convergence by utilizing each individual in the population as much as possible. This improved version of GNDO is called ranking-based generalized normal distribution optimization (RGNDO). RGNDO is experimentally investigated on three commercial PV modules (Kyocera KC200GT, Ultra 85-P and STP 6-120/36) and a solar unit (RTC Si solar cell France), and its extracted parameters are validated based on the measured dataset points extracted at generalized operating conditions. It can be reported here that the best scores of the objective function are equal to 0.750839 mA, 28.212810 mA, 2.417084 mA, and 13.798273 mA for RTC cell, KC200GT, Ultra 85-P, and STP 6-120/36; respectively. Additionally, the principal performance of this methodology is evaluated under various statistical tests and for convergence speed, and is compared with a number of the well-known recent state-of-the-art algorithms. RGNDO is shown to outperform the other algorithms in terms of all the statistical metrics as well as convergence speed. Finally, the performance of the RGNDO is validated in various operating conditions under varied temperatures and sun irradiance levels.

Characterization of Soiling Bands on the Bottom Edges of PV Modules

Soiling of photovoltaic (PV) modules, especially non-uniform soiling, can lead to PV power loss. For example, soiling bands at the bottom edge of framed modules are caused by the accumulation of water and dirt at a lower tilt angle. However, few studies have investigated this issue. In this study, industrial and commercial metal rooftop PV power stations in central and eastern China were investigated, with a focus in Xi’an and Kaifeng cities. The results show that (1) soiling bands were widespread, even in Guangzhou city, where annual rainfall is approximately 1,800 mm; (2) soiling bands were found during every month in Xi’an city, even from July to September when heavy rainfall occurs frequently; (3) three types of soiling bands were observed on modules (rectangular, transverse trapezoidal, and triangular), with double triangular, arch, and shallow U-shape types also being observed in landscape-oriented modules; (4) the mean relative difference of the maximum direct current due to soiling bands between one maximum power point tracking system and its control from June 19 to October 2, 2019 in Kaifeng city was approximately 4.7%.

Nondestructive silicon wafer recovery by a novel method of solvothermal swelling coupled with thermal decomposition

• 86.11% of Si-wafers in commercial PV module can be reclaimed without damage. • The formation of gas release channels contributes to the nondestructive recovery. • PV backsheet removal avoids the fluorine-containing gas emission. • Solvothermal swelling strategy provides significant time and organic solvent savings. • The reclaimed silicon wafer meets the requirements of new PV module fabrication. End-of-life (EoL) photovoltaic (PV) waste is becoming a severe environmental issue worldwide. Developing technologies to reclaim nondestructive and reusable silicon wafers (Si-wafers) is the most appealing way to solve this problem, saving ~40% on PV module production costs, but it remains a great challenge. Herein, we develop a novel method of coupling solvothermal swelling with thermal decomposition (SSTD) for structure-intact Si-wafers recovery. Laboratory-scale studies reveal that undamaged Si-wafers can be easily obtained by conducting a solvothermal swelling process in advance to build channels for the quick, horizontal release of ethylene-vinyl acetate (EVA) thermal decomposition gas. Using scaling-up equipment, 86.11% of Si-wafers in commercial PV module are reclaimed without any damage, nearly 10-fold higher than that of thermal decomposition alone (9.26%). Moreover, PV backsheet can be depolymerized with specially designed solvents (toluene-ethanol), greatly facilitating swelling by exposing EVA directly to toluene vapor and reducing the emission of fluorine-containing gas pollutants. The reclaimed Si-wafers are comparable to the originals, with the following properties: interstitial oxygen, <6 × 10 17 atoms·cm −3 ; substitutional carbon, <5 × 10 17 atoms·cm −3 ; resistivity, 1.84 Ω·cm; and minority carrier lifetime, 3.92 μs.

Comparison of Perovskite Solar Cells with other Photovoltaics Technologies from the Point of View of Life Cycle Assessment

A review of the life cycle sustainability of perovskite solar cells (PSCs) is presented, distinguishing results between simulated laboratory‐based and simulated industrial‐based PSCs, comparing this technology with the commercial photovoltaic (PV) technologies. Laboratory‐based perovskites are seriously affected by the unrealistic energy consumption of the deposition routes. Moreover, other hot spots such as lead and solvent toxicity are much less relevant. A cluster analysis of single‐junction PSCs allows us to differentiate two clusters, in one of them, the most numerous, environmental impacts are in a similar range to other thin film PVs. Despite more progress at the industrial scale being needed, the current studies point out the promising results in terms of energy payback time and the environmental impacts at the industrial‐scale, that are the lowest compared with commercial PVs, if 1 kWp is used as the functional unit. In addition, PSCs present less supply risk than other photovoltaic technologies. Only cesium, which is dispensable, can present a specific risk. Current production costs could be reduced if barrier foils and transparent conductive oxide coated plastics can be found. However, this cost could be competitive selling into niche markets. In addition, their lightness, flexibility and ease of integration give them very advantageous qualities for social acceptance.

Performance analyses of various commercial photovoltaic modules based on local spectral irradiances in Malaysia using genetic algorithm

A novel comprehensive methodology integrated with genetic algorithm (GA) has been formulated by accounting for local spectral irradiance and the specifications of commercial photovoltaic (PV) module. Despite having the same solar irradiance, variation in power conversion efficiency (PCE) of PV module can be significant in different site locations by referencing to that of standard AM1.5 spectrum. We have carried out a case study using GA for a combination of three site locations in Peninsular Malaysia and twelve types of commercial PV modules. Type-9 PV module operating in Bangi has recorded the lowest gain with 0.1%, while type-10 PV module operating in Bandar Sungai Long has shown the best gain of up to 27%. For solving multi-objective problems, MmGA and NSGAII have been applied to optimize three objectives concurrently including PCE, PV weight and PV panel area. From the simulation, type-1, type-6, and type-12 PV modules show the best in at least two objectives for the categories of m-Si, p-Si, and thin film, respectively.

Design of a Portable Photovoltaic I–V Curve Tracer Based on the DC–DC Converter Method

The I–V curve tracer is an instrument that captures the current–voltage characteristics of photovoltaic (PV) generators under real operating conditions. Such device can be used to evaluate their performance and identify faults or aging effects, but its high costs have prevented it from being widely used in the industry. This article thus proposes the design of a low-cost, portable I–V curve tracer based on the classic dc–dc Cuk converter for PV modules of up to 300 W. In order to obtain a compact device, some design techniques are proposed, including circuit reduction, high switching frequency operation, specification of the optimum load resistor power rating, and improved measurement distribution because of a nonlinear duty cycle variation. Experimental curves were compared with those acquired from commercial PV tracers to demonstrate its accuracy. In addition, the physical parameters of the well-known single-diode model have been extracted and compared with data provided by manufacturers to identify aging effects and module performance.

Maximum power estimation through injection dependent electroluminescence imaging

AbstractThe mathematical models applied to photovoltaic (PV) modules are typically oversimplified. In general, the models applied to individual PV cells are modified to obtain the “cell” voltage by dividing the module voltage by number of cells in the module. Due to the complexity of the current–voltage (IV) relation and the presence of bypass diodes in commercial PV modules this approach is inappropriate and can lead to incorrect conclusions about the electrical response of a module. This paper provides a method of determining each cell's electrical response using a combination of the Dark IV response of the entire module and injection dependent electroluminescence (EL) imaging. This combination of characterization techniques makes use of equipment that is readily available in commercial facilities as well as regular PV characterization laboratories. This method can be used as an alternative to lock‐in thermography (LIT) based methods, as the equipment required is not always present in standard PV characterization laboratories. In this study, Evolutionary Algorithms are used to optimize the individual cells' electrical parameters. This advanced characterization method can be utilized in commercial facilities, to investigate atypical module electrical response and in research laboratories to investigate the degradation in individual cells within a module.

Electrical Parameters Identification of Three-Diode Photovoltaic Model Based on Equilibrium Optimizer Algorithm

Tremendous penetration of photovoltaic (PV) systems into the electric grids develops many challenges in the modern power systems. In the simulation analyses of PV systems, accurate modelling of PV modules plays a crucial role in enhancing the characteristics of such systems. Modelling of such PVs is represented by a non-linear I - V behavior, involving various unknown parameters because of the inadequate data offered in the datasheet of PV cells. This paper proposes a novel implementation of the equilibrium optimizer algorithm (EOA) to identify the nine-parameters of a three-diode (TD) model of a PV module. Soundness of the EOA-TD model is extensively confirmed by the simulation results that are carried out in different environmental conditions. The optimal parameters obtained using the proposed approach are compared with those realized using other optimization techniques-based TD models. To achieve a practical study, the simulation and experimental outcomes are checked for various commercial PV panels and the error among these results records a value less than 0.5%. Moreover, the optimal parameters attained using the EOA are competitive and very close to that realized using other approaches, where the offered EOA has exhibited a minimum fitness value of 1.14e-14 and 7.154 e-13 for Kyocera and Solarex marketable PV cells, respectively. The effectiveness of the proposed TD PV model is adequately assessed by evaluating its absolute current error (ACE) with the ACE in different PV models. The EOA technology is considered to be an accurate means of achieving the proper modelling of any commercial PV module.

АНАЛИЗ И МОДЕЛИРОВАНИЕ АВТОНОМНОЙ ФОТОЭЛЕКТРИЧЕСКОЙ СИСТЕМЫ С ИСПОЛЬЗОВАНИЕМ СРЕДЫ MATLAB/SIMULINK

The use of renewable energy sources and in particular solar energy has received considerable attention in recent decades. Photovoltaic (PV) energy projects are being implemented in very large numbers in many countries. Many research projects are carried out to analyze and verify the performance of PV modules. Implementing a pilot plant for a photovoltaic power system with a DC / DC converter to test system performance is not always possible due to practical limitations. The software simulation model helps to analyze the performance of PV modules, and more useful would be a general circuit model that can be used to test any commercial PV module. This paper presents a simulation of a mathematical model of a photovoltaic module that boosts a DC / AC converter and also simulates the operating modes of a solar generating system at various load characteristics. The model presented in this article can be used as a generalized PV module to analyze the performance of any commercially available PV module. In the presented work, the parameters that affect the performance of the generating system were investigated. The results were obtained for the operation of DC/AC photoelectric converters. The presented characteristics strongly depend on such parameters as solar insolation, the temperature of the working surface of the photovoltaic module, the charge-discharge time of storage batteries, etc. When one of the values ​​of these parameters changes, the operating modes of the solar power generating battery change. Changing the operating modes can lead to malfunctions of the entire operation of the system, therefore, it is necessary to control all the energy characteristics of the installation. The actions proposed in this work aimed at studying the operation of the photovoltaic system and the energy storage system, as well as the use of the necessary auxiliary devices for monitoring and controlling the parameters of the installation, are capable of achieving an increase in the efficiency of the generation of the system. The studies carried out in the course of the presented work make it possible to increase the level of knowledge on the control and management of the parameters of photovoltaic generating plants and expand the possibilities of their uninterrupted operation and increase energy production.

Optimized Global Maximum Power Point Tracking of Photovoltaic Systems Based on Rectangular Power Comparison

Global maximum power point tracking (GMPPT) refers to the extraction of the maximum power from photovoltaic (PV) modules in real time under changing ambient conditions. Due to the installation of PV systems in densely built-up areas, partial shading scenarios are commonplace. Commercially established GMPPTs suffer from low tracking speeds and inefficiency. A novel GMPPT algorithm is proposed here based on the rectangular power comparison (RPC), which exploits the fundamental relationship between the shading factor, the bypass diode voltage and the global maximum power point. The entire theoretical formulation of RPC is presented systematically for the first time. This method boasts of increased conversion speeds owing to the precomputation of the module voltage versus the shading factor correlations using the regression of diode model from the experimentally obtained bypass diode characteristics. The proposed method is simple to implement with the computational complexity of order $n$ , which represents the number of uniquely shaded PV modules in a series string. The proposed approach addresses the much-needed intersection problem between the distributed and centralized PV systems and therefore targets PV strings which are most common in residential and small to medium scale commercial PV installations world over. The proposed approach is validated with the in-house developed prototype hardware set-up and software control implementation giving a 99% tracking efficiency with a recorded tracking time of 10 ms. The experimental results show 50 times improvement in speed and 95% increase in power gain as compared to the other popular existing methods namely scanning based GMPPT and local MPPT methods respectively, with negligible computational burden and less than 0.5% added cost to the conventional PV energy conversion system.

Simple PV Modeling Under Variable Operating Conditions

Photovoltaic (PV) panels are increasingly used to convert sunlight into electricity, as a source of sustainable energy. It can be used in a wide variety of applications ranging from the well-known power generation to the emerging energy harvesting in Internet of Things (IoT). Hence, an accurate model is required to evaluate and predict the performance of the PV panel. However, the non-linear characteristics of PV panels make the modeling of their electrical response a challenging task. In the literature, most of the previous PV models have been developed for large wattage PVs under high irradiance, or for small wattage PVs under lower irradiance. Those that can model both usually require more information, including the I-V curves data at different irradiances, which is not always provided by the manufacturers. Therefore, this paper presents a simple PV modeling that can be applied for different wattage panels at different operating levels of irradiance, using only the commonly provided datasheet values at standard test condition (STC). The model uses the characteristic points translation technique to translate the short circuit current, open circuit voltage and maximum power voltage points, at STC to other operating conditions. These translated values are then used by the parameter extraction technique to extract the model's parameters. The proposed model's techniques can model the losses across the resistors at low irradiance, which reduces the error. The accuracy of the proposed model is validated using two representative commercial PV panels. Results are generated for the proposed model and other comparative works. The results show that the proposed model can improve the accuracy over the other compared works, with a consistent percentage difference of below 5% across all levels of irradiances for both panels.