Search

• The pilot plant of salt farm parallel solar power plant is verified for a year. • The system showed 93.4 % power generation compared to land installed PV system. • The main power loss of the system is 9.8 % by installation angle, 1.6 % and 4 % power loss by light loss. • A parallel salt farm system that can achieve the land equivalent ratio 2.13. In this research, we proposed a new concept for a solar system on a salt farm, where electricity and salt are produced simultaneously. In order to verify the concept, we installed a pilot system and demonstrated it for one year. We installed different types of PV modules for the system and tested the electrical properties, durability, and waterproofing of the modules. The electricity generation of the salt farm photovoltaic system is compared to land installed photovoltaic system for its feasibility. Also, computer simulation analyzed the installation angle, light loss, and cooling effect due to salt water and loss due to foreign substances. We found that the power generation by the year of the salt farm photovoltaic system is 9 percent less than that of a photovoltaic system installed on land. we also propose several methods in order to improve electricity generation by the salt farm photovoltaic system. [ABSTRACT FROM AUTHOR]

• The main limitation of CPV systems is related to the use of heavy solar trackers. • Integrating tracking within the CPV system is one of the possible solutions. • This work studies two concentrations, determining their impact on the performance. • Optical simulations and indoor measurements of the two systems are carried out. • Results show an optical efficiency above 80% and 70% for each concentration at ± 50°. Tracking-integrated Concentrator Photovoltaics (CPV) represents an alternative to conventional CPV. The elimination of expensive and heavy solar trackers contributes to reduce the cost of conventional CPV, and open new market segments. This technology, still under development, needs further investigation. In this work, two tracking-integrated focusing systems with two different concentration levels, consisting of a fixed bi-convex aspheric lens and a movable triple-junction solar cell, are analysed. Initially, by means of detailed optical modelling, the concentrator elements are optimized. After that, they are experimentally investigated at Concentration Standard Test Conditions (CSTC) by varying the angle of incidence ± 50°. The results show an optical efficiency > 80% and > 60% for a geometric concentration of 10.0x and 82.5x, respectively, within the whole angular range. These systems could contribute to novel CPV applications such as agrivoltaics or building integrated. [ABSTRACT FROM AUTHOR]

The performance of a photovoltaic power system is heavily influenced by mismatches, for example, partial shading effects. In literature, it lacks of a scrupulous study on intelligent control designs whose transient responses and steady state responses are not directly given when achieving the goal of global maximum power point tracking (GMPPT). A novel and systematic control design approach is proposed mathematically to derive explicit discrete controllers for the overall GMPPT performance. Specifically, the new algorithms of nonlinear function (NF) based particle swarm optimization (PSO) and ordered excitation (OE) are incorporated into the extreme seeking controller for the enhancement of both transient and steady state responses when fulfilling the extreme seeking task. The explicit control functions are easy to implement in the applications. Both the simulation based analysis and experimental study are carried out in a statistical manner in order to evaluate the proposed controller through a number of control performance indicators. A comparison analysis of the statistical data reveals that both simulation and experimental results agree with the theory where both algorithms of NF-PSO and OE play a role to improve transient responses and steady state responses for the global extreme seeking. Meanwhile, the proposed intelligent controller outperforms the classical benchmark in tracking the GMPP. The insightful and instructive control design tool is promising in both academia and engineering. • An explicit ESC of OE-NF-PSO is proposed. • The algorithm of OE is introduced to reduce the oscillations. • The algorithm of NF-PSO helps improve the global extreme seeking ability. • New control norms are defined for a comprehensive analysis. • The analysis of both numerical and experimental results is carried out. [ABSTRACT FROM AUTHOR]

• An efficient optimization technique, dubbed the Chimp Optimization Algorithm (ChOA), for estimating the model parameters of solar networks. • The proposed ChOA outperforms state-of-the-art algorithms in terms of convergence rate, global search capacity, and durability. • To demonstrate the algorithm's efficiency, ChOA is used to determine the parameters of several photovoltaic modules and solar cells. • The performance of the algorithm has been evaluated in a practical application for parameter evaluation of three widely-utilized commercial modules. • The results confirm the proposed algorithm's robustness and high performance. The global shift toward solar energy has resulted in the advancement of research into the manufacture of high-performance solar cells. It is critical to accurately model and identify the parameters of solar cells. Numerous models of solar cells have been presented thus far, including the single-diode, the double-diode, and the three-diode models. Every model contains a number of unidentified parameters, and numerous approaches for determining their optimal values have been published in the literature. The purpose of this article is to propose an efficient optimization technique, dubbed the Chimp Optimization Algorithm (ChOA), for estimating the model parameters of solar networks. The proposed ChOA outperforms state-of-the-art algorithms in terms of convergence rate, global search capacity, and durability. To demonstrate the proposed ChOA algorithm's efficiency, it is used to determine the parameters of several photovoltaic modules and solar cells. The result of ChOA is evaluated and compared with ten well-known optimization algorithms in the literature. Additionally, the performance of the ChOA algorithm has been evaluated in a practical application for parameter evaluation of three widely-utilized commercial modules, i.e., multi-crystalline (KC200GT), polycrystalline (SW255), and monocrystalline (SM55), under a variety of temperature and irradiance circumstances that result in alterations in the photovoltaic model's parameters. The results confirm the proposed algorithm's robustness and high performance. [ABSTRACT FROM AUTHOR]

• Reviews the looming global problem of PV waste generation in near future. • Identifies issues in the PV modules which contribute to early failure. • Two configurations are experimentally compared in light of PV reliability. • Proposes ways to mitigate high-volume of PV waste due to early failures. • The inclusion of bypass circuit verification test is recommended in IEC 61215. The global installed capacity of photovoltaic (PV) plants is increasing exponentially since the beginning of the 21st century. And as the early installations have started nearing their end-of-life, presently, PV waste management has started raising concerns amongst environmental researchers. The cumulative PV waste generation is estimated to reach 8 million tonnes by 2030, however, interestingly, this humungous volume may be reduced by 79% if early failures could be averted. And one of the major contributors to the early failure of the PV modules is the hotspot generation under partial shading and other mismatch conditions. Various innovative array configurations have been proposed in the past to minimize power loss under partial shading conditions, however, the performance of those from the perspective of hotspot formation and PV reliability is neglected. In the present work, the efficacy of the hotspot prevention mechanism is investigated, both in an experimental setup and in real installations. The results revealed that the extant mechanism is ineffective in preventing the occurrence of hotspots in total cross-tied (TCT) array configuration, which is hailed as the best performing one in the literature, when studied from the perspective of mismatch power loss only. [ABSTRACT FROM AUTHOR]

• A simple method for Performance Loss Ratio estimation is applied step by step to PERC bifacial photovoltaic modules. • The results of the applied method are compared with the solar simulator lab test. • The PLR has been estimated by the "5-STEP method" using classical PR, temperature corrected PR and bifacial PR as metric, calculated within a narrow Irradiance range filter. The need to replace fossil energy sources with renewable energy sources to combat global warming has prompted the growth and development of various technologies, including photovoltaics. At the same time the PV technology is evolving to enhance efficiency and durability of PV modules. Bifacial PV modules is gaining larger share of market due to the higher energy and power density at almost the same price of conventional PV modules. In recent years, as PV systems have been operating for a long time, understanding the aging phenomenon of PV modules has become increasingly important. Various types of defects are known that occur during the life of the modules, however, understanding the trend of degradation through a simple quantification of the decrease in performance over time can be a useful tool. The Performance Loss Ratio can give indications about the state of health of the system and can be used for a rough comparison on the performance reduction guaranteed by the module manufacturer and check if the warranty terms are actually respected. In the present study a simple method is used to evaluate Performance Loss Ratio (PLR) on a real PV plant equipped with bifacial PERC modules. Criticalities were highlighted within each phase of the application of the method. The numerical results of the PLR estimate of the photovoltaic modules of the system are reported, calculated on a two-year dataset starting from the date of installation. Finally, the PLR values, that have been estimated using three different metrics and linear fitting, have been compared with the measured average Power decay values associated exclusively with PV modules. The simplicity of the method allows it to be replicated to other case studies. [ABSTRACT FROM AUTHOR]

• Distribution feature among the different status of PV arrays is revealed. • New indicators are introduced to comprehensive evaluation operating status of PV arrays. • Reference status array is selected based on the improved objective weight TOPSIS method. • The proposed method can effectively identify the operation status of PV arrays. In the context of rapid development of photovoltaic (PV) power generation, as an aspect of the key equipment that undertakes the photoelectric conversion in PV power plants, the operation status of PV arrays directly affects the power generation efficiency and economic benefits of PV power plants. An accurate evaluation of the PV array operation status can quickly locate operational weak points and provide the benchmark array for fault diagnosis, which has important engineering application value. So, a new method for selecting the operating reference status of PV arrays is proposed in the paper. First, the array Performance Ratio (PR) probability distribution model was established using the non-parametric estimation method, and the comprehensive evaluation indicators of the PV array were determined using the model characteristic indices and output power of the PV array. The technique for order preference by similarity to ideal solution (TOPSIS) method was improved, the reference PV array was selected, and a graded evaluation of the operation status of the PV arrays was designed. This study provides a novel method to evaluate the operation status of PV arrays from the perspectives of power deviation and stability. The effectiveness of the proposed method was verified through empirical analysis. [ABSTRACT FROM AUTHOR]

Photovoltaic (PV) systems have become an integral and widespread part of renewable energy generation. In combination with energy storage, they offer a variety of advantages such as increased self-sufficiency or improved grid stability. However, geographic location, subsidies, energy tariffs, size of PV panels and battery, and other factors significantly influence the overall performance and profitability of the system. Solving this complex task of system design and component dimensioning is not easy. The diversity and multitude of parameters therefore usually requires the help of, more or less complex, computer simulations. This led and still leads to a high publication activity on techno-economic and other optimizations for such systems. However, the operating strategies and component models are often oversimplified, leading to results with significant errors. The goal of this paper is to provide in-depth insight into component modeling and parametrization for PV module, battery energy storage, and inverter, as well as giving suggestions on appropriate control strategies. The focus lies on the description of suitable simple-but-accurate models and their parametrization. In order to avoid the effort of having to conduct measurements for component characterization, an approach relying on values presented in product data sheets is considered. Furthermore, the effects of model simplifications, as they are found in many publications, are shown. Finally, the importance of an uncertainty analysis for the entire simulation is discussed in order to gain insight into the accuracy of the calculated simulation results and their dependency on model- and input-parameters. • Photovoltaic system modeling/simulation. • Component modeling for PV module, battery energy storage and inverter. • Suitable simple-but-accurate models and their parametrization • Characterization relying on product data sheets with minimal informations. [ABSTRACT FROM AUTHOR]

• Only all-sky images areused to estimate solar irradiance. • All-sky imagesare analyzed to obtain cloud features on a regional and global scale. • The estimation of solar energy is based on an all-sky image. The ramp event of solar irradiance is prone to occur due to atmospheric conditions, and makes it difficult to integrate solar power into regional power grid. The atmospheric aerosol, cloud occlusion, temperature and weather conditions especially influence the daily solar irradiance, and cause the uncertain of the solar power which would leads to the regional grid overloaded or lower-loaded. To integrate the solar power into the regional grid reliably, the estimation of solar irradiance and solar power output plays an important role. In the study, a system is proposed to perform accurate solar irradiance and solar power estimation. Through the all-sky image feature extractions, the regional and global weights are obtained. The long short-term memory (LSTM) is used as the training model with the weights as inputs to estimate the solar irradiance. The power curve is made by using the estimated solar irradiance and the solar power output to estimate the solar power. Several performance indices are used to evaluate the proposed method, including mean absolute error (MAE), root mean square error (RMSE) and coefficient of determination (R2). The experimental results show that the performance of the solar irradiance estimation of the proposed method is remarkable with the lower MAE and RMSE and the higher R2. Furthermore, the performance of the solar power estimation using the proposed method is very close to the actual estimation performance. [ABSTRACT FROM AUTHOR]

• A co-simulation approach for estimating snow losses is implemented. • The sliding coefficient is modified to simulate icephobic nanomaterials. • Highest snow losses are observed in Oslo, up to 32.75 kWh/m2. • Best monthly performance of icephobic coatings is in Trondheim, during March. Solar energy's penetration at high latitudes has been boosted during recent years, but snow deposits during the winter still limit its exploitation. Therefore, various solutions for snow removal, such as icephobic coatings, increasing panels' tilt angle, and using wind flows, are being attempted to reduce snow and ice accumulation. The novelty of this study is that it presents insights into the snow-related issues of photovoltaic plants in Norway and proposes a preliminary approach to modelling these issues' influences at high latitudes using a co-simulation approach. The workflow is based on a combination of PVsyst and Marion's algorithm, and moves from the assessment of snow deposits on photovoltaic panels and the consequent reduction of plane of array (POA) irradiance (snow losses) to evaluating the influence of icephobic nanomaterials on snow losses. Solar analyses are performed on a photovoltaic plant located in Trondheim, Norway, and then reiterated considering the climate of the Norwegian cities of Bergen and Oslo. The snow losses between November and April, when the snow depth is greater than zero, are 32.75 kWh/m2 in Oslo, 25.05 kWh/m2 in Trondheim, and 5.85 kWh/m2 in Bergen. The application of icephobic coatings currently available on the market will reduce such snow losses to 12.05 kWh/m2 (65% efficiency) in Oslo, 10.00 kWh/m2 (60% efficiency) in Trondheim, and 3.35 kWh/m2 (45% efficiency) in Bergen. In conclusion, the application of icephobic coatings should be more greatly boosted in a continental climate (Oslo and Trondheim) than in an oceanic climate (Bergen) to maximize photovoltaic power output. [ABSTRACT FROM AUTHOR]

• A novel MPPT controller based on yellow saddle goatfishes algorithm (YSGA) for energy optimization of PV systems. • Qualitative and quantitative comparison of YSGA with BAT,GWO,SOA,PSO, and P&O under partial shading condition. • Statistical analysis based on: the average best so far (AB), the median best so far (MB), and standard deviation (SD). • Wilcoxon test with 5% significance level based on the median value is applied to verify the superiority of the algorithm. This paper proposes a novel maximum power point tracking (MPPT) technique based on a new optimization algorithm called yellow saddle goatfish algorithm (YSGA). The photovoltaic system loses a significant amount of power under partial shading conditions (PSC). Because of the presence of bypass diodes, several maximums appear in the Power-Voltage characteristic, making tracking the global maximum power point (GMPP) extremely difficult. A yellow saddle goatfish-based MPPT algorithm is proposed and implemented to address this issue and improve the efficiency of the PV system. This algorithm employs a subgroup research methodology and a very interesting strategy of particle collaboration during GMPP tracking, providing a balance between the exploration and exploitation phases of the research process. To investigate its performance, tests were conducted using six different partial shading patterns and a fast irradiance variation. The simulation was carried out in MATLAB/Simulink using a series of MSX60 solar panels. The results were compared to well-known and efficient algorithms such as the Grey wolf optimization algorithm (GWO), the Bat algorithm (BAT), particle swarm optimization (PSO), the Seagull optimization algorithm (SOA), and the Perturb and observe (P&O) algorithm. The findings demonstrate the proposed method's high robustness, as well as its high dynamic and accuracy in tracking the GMPP. Furthermore, a quantitative and statistical analysis of 100 tests revealed that it outperformed the other algorithms in terms of efficiency, success rate, convergence time, and solution dispersion. [ABSTRACT FROM AUTHOR]

This paper deals with a new design of a photovoltaic-thermal (PVT) collector which incorporates a storage tank at the back of the thermal module to store heat as well as an electrical resistance to increase thermal production when necessary. This work investigates modeling and CFD study with the aim to provide a dynamic model which reflects a realistic behavior of the system. Simulations are performed to validate the model and to highlight the usefulness of the proposed design. Moreover, the modeling proves to be useful in analyzing the influence of internal geometrical parameters, such as thickness of insulation and absorber, type of fluid and also of materials used for absorber and serpentine tube. • A new design of a PVT collector which incorporates a tank and electrical resistance. • Influence of internal geometrical parameters, such as thickness, fluid and materials. • Consistency has been validated by comparison to a CFD simulation. [ABSTRACT FROM AUTHOR]

• Rapid growth in solar system utilization in buildings require long-term experimentation. • Challenges in integrating solar systems in hot climate and densely populated urban areas. • Cooling energy monitoring conducted for two identical portable cabins in Kuwait. • Evaluation of off-grid solar PV system on energy savings of the portable cabins. • The average energy savings of 24.1 % and CO 2 reduction of 129.4 kg in 9 months. The rapid growth of energy consumption in densely populated urban areas with limited land space, especially in hot climates, poses significant challenges. The Australian University of Kuwait conducted a study using two portable cabins to explore energy-saving techniques. One cabin integrated an off-grid solar photovoltaic (PV) system to evaluate its impact on grid electricity demands for an airconditioning (AC) cooling system over 9 months, compared to the second cabin without a PV system. The PV system utilized rooftop space with four Monofacial Go Green 350 W/24 V solar panels, an off-grid maximum power point tracker (MPPT) inverter charger 3.5kVA/100A/24 V, and two Gel deep cycle batteries 12 V/200Ah. The PV panels were oriented south at a 30-degree latitude angle, providing power through the MPPT to a 1.5-ton AC split unit for cooling. Findings showed that the cabin with solar PV panels achieved a 24.1 % energy saving and a total CO 2 reduction of 129.4 kg, consuming 1,743 kWh over 237 days, compared to 2,296 kWh for the cabin without the PV system. The novelty of this study lies in the integration of off-grid solar PV systems with existing cooling technologies to evaluate potential energy savings and environmental benefits for comprehensive utilization and addressing urban and climate challenges. Enhancements can include flexible room temperature control using advanced systems, optimizing the PV system settings with more efficient AC systems, and connecting the PV system to additional loads like heating/cooling and lighting. These improvements would ensure the comprehensive utilization of captured solar energy in Kuwait and countries with similar climatic conditions throughout the year. Advancements in solar PV panel efficiency and high-intensity flexible PV panels offer opportunities for maximizing solar energy capture in dense residential buildings. [ABSTRACT FROM AUTHOR]

The fast growth of solar photovoltaic (PV) power generation raises the concern of grid stability due to intermittency. The traditional solution based on the broad installation of energy storage systems (ESS) is considered to be costly. Hence, the latest research focuses on the active power ramp rate control (PRRC) that decouples the heavy reliance on ESS. While power-forecasting-based PRRC can be a promising solution, the relevant research is still limited and does not cover the prediction error's negative effect on the power ramp rate control. With the above, this paper investigates the over-regulation issue that is induced by inaccurate prediction and can lead to power losses. More importantly, this paper proposes a novel PRRC scheme incorporating a Gaussian confidence estimator and best-performed deep neural networks (DNN) predictor to implement more accurate control actions while overcoming the over-regulation problem. The experimental tests show that the proposed scheme can simultaneously achieve a more promising PRRC performance and relatively higher energy harvest efficiency compared to the prior arts. • A novel predictive PRRC scheme based on big meteorological data is proposed. • The proposed approach eliminates the reliance on ESS while simultaneously achieving promising PRRC performance and high energy harvest efficiency. • The PRRC's overregulation problem that can bring additional power losses is firstly investigated in this study. • A novel prediction confidence estimator based on Gaussian process is proposed to address the overregulation issue by monitoring the prediction's reliability. • A comprehensive study on the popular DNN-based solar forecasting models is implemented to select the best-performed predictor suitable for sequential meteorological data and the power system's PRRC task. [ABSTRACT FROM AUTHOR]

• Diagnostic procedure for the evaluation of module misalignments on a CPV array characterization based on images. • Implementation and demonstration of the method with a dron equipped with an imaging camera. • Determination and correction of error sources associated to dron-to-array positioning. • Example case: full characterization of a tracker composed by 48 modules, determination of uncertainties. This paper deals with the characterization of misalignments between CPV modules installed on tracker structures, for which a misalignment measurement method (suitable for inspecting CPV plants) is proposed. The method consists of acquiring images of the photovoltaic solar cells magnified through the optics with a visual camera mounted on a drone. The relative position between modules is proportional to the observed spatial misplacement between the magnified cells and equivalent to an angular misalignment of the pointing vector of the modules with respect to the ideal optical axis. The method, that had already been demonstrated at module level in laboratory conditions, has been adapted to account for the errors associated to the camera position during the drone flight sequence. An experimental validation of the method is carried out by characterizing the misalignments between 48 CPV modules in a tracker, with an uncertainty lower than ±0.09 degrees for measured misalignments of up to 0.95 degrees. [ABSTRACT FROM AUTHOR]

• Sizing of components affects the performance of the MPPT buck converter. • Inductance is needed to maintain CCM operation while operating close to DCM. • Correct capacitance size manages the voltage ripple. • Proposed derivation allows optimum sizing for resistive and battery load. A photovoltaic (PV) maximum power point tracking (MPPT) converter consists of MPPT algorithm and converter. Although there has been a lot of improvement for MPPT algorithm, there is still much to improve for the converter. This paper proposed optimum sizing for the ideal PV MPPT buck converter with resistive and battery loads. The optimum sizing ensures the MPPT converter operates in the continuous current mode (CCM) operation and within the defined output voltage ripple for the specified range of irradiance. These conditions are achieved by deriving the equations of the inductances and capacitances required for the MPPT buck converter. The CCM operation is designed to be closed to the DCM to ensure a small inductance value. The specified output voltage ripple ensures the quality of the output of the MPPT buck converter. The verification of the derivation is done using MATLAB/Simulink circuit simulation. The conventional single diode PV model and perturb and observe (PnO) MPPT is used in the system. The result shows that the range of output resistance is highly affecting the duty cycle range, which leads to MPPT failure if the output resistance is not calculated properly. The converters for both resistive and battery loads can operate in the CCM and close to the DCM operation based on the proposed design. These converters also maintain output voltage ripple factor at 1% or lower, which the proposed derivation follows the specification. In conclusion, the proposed derivation of the MPPT buck converter is accurate. [ABSTRACT FROM AUTHOR]

• Conversion time and failure rate are crucial factors for online optimization problems. • Control parameters of the swarm optimization techniques influence the performance of optimization. • The novel musical chairs algorithm (MCA) descriptions. • The simulation of the MCA compared to nine optimization algorithms. • Single-diode and double-diode models of the PV solar cells. • Parameters estimation for different operating conditions. Solar photovoltaic (PV) energy systems are representing the most attractive source of energy, especially with the continuous reduction of manufacturing costs. The new systems' sizing and cost estimation depend mainly on the accurate modeling of the PV cells. The modeling of the PV cells is based on one-diode modeling with five unknown parameters or the more accurate modeling based on two-diode modeling that have seven unknown parameters, or with a higher number of shunt diodes modeling with a higher number of unknown parameters. An accurate and fast estimation of the PV cell parameters will help designers to build their decision based on accurate results, where any small variation of these parameters can spoil the results obtained from the modeling and can produce an unwise decision. A high number of studies are introduced in the literature to estimate these parameters. These studies are different in the accuracy of results and the time consumed to get these results. Some of these studies used metaheuristic algorithms which are characterized by slow convergence and may cause inaccurate results. For this reason, a recent optimization algorithm called the musical chairs algorithm (MCA) is introduced in this paper to estimate these parameters faster and more accurately than many metaheuristic algorithms. The idea behind the use of MCA is to have a high number of search agents in the beginning to enhance the exploration and continuously reduce this number to enhance exploitation at the end of optimization and reduce the convergence time. The results obtained from using 10 optimization algorithms showed that the error associated with MCA is 20% of the average error of the other optimization algorithms. Moreover, the MCA never misses the global minimum of error which was not the case in other optimization algorithms. The MCA obtained these results in 40% of the time consumed by other optimization algorithms. These results of the MCA showed its superiority compared to other optimization algorithms. [ABSTRACT FROM AUTHOR]

• Amount of power processing determines the efficiency in power converter. • There are two types power processing techniques: full power and differential power. • Control requirement and complexity can be negligible in full power processing. • Differential power processing is low rated and cost. • Photovoltaic power optimizers on the market usually support module-based MPPT. Maximum power point tracking (MPPT) procedure in photovoltaic (PV) systems can be realized with many different methods. Especially in arrays consisting of PV modules (PVMs) connected in series; the maximum power point (MPP) may change due to partial shading conditions (PSC), aging, degradation, fabrication production differences etc. In addition, even in small power systems containing a single PVM, the difference in shading and irradiation between submodules affects the maximum power potential of the PVM. In this study, power electronics-based power processing methods in distributed MPPT (DMPPT) systems are emphasized. Power electronics-based hardware MPPT solutions are examined in two groups as full power processing (FPP) and differential power processing (DPP). In addition, commercially available power optimizers have been examined under many criteria. The literature on the subject has been analyzed in a broad perspective, and it has been comprehensively evaluated according to criteria such as power processing level, converter configuration, MPPT algorithm, MPPT application level and control approaches. This study is an important guide for scientists and hardware engineers doing academic studies on the subject. This study, which examines the topologies and control approaches used in application-oriented studies, has the feature of triggering future studies. The features that commercial power optimizers should have and the examination of the products in the market within the framework of some criteria is one of the original aspects of the study. It is expected that this study will contribute to the PV industry in building applied and building integrated studies, where extreme shading scenario occurs. [ABSTRACT FROM AUTHOR]

• A GEP-based MPPT technique for fast-changing atmospheric conditions is proposed. • The transient response and steady-state stability of the system are increased. • The convergence speed and tracking accuracy are remarkably improved. • The number of oscillations and rate of overshoots are substantially reduced. • The complexity level is significantly reduced by the model equation. The erratic behavior of the atmospheric conditions adversely affects efficient energy harvesting and the stable operation of photovoltaic systems. It is therefore critical to draw maximum power from photovoltaic modules regardless of atmospheric conditions. The maximum power point tracking techniques have crucial impacts on both efficient and stable operation of photovoltaic systems as being the controller part of the power converters. In this paper, a novel gene expression programming-based maximum power point tracking technique is proposed for micro-inverter applications under fast-changing atmospheric conditions. In this context, the main objective of this study is to improve the significant performance indices of maximum power point tracking technique including convergence speed during transients, tracking accuracy, steady-state oscillations, and rate of overshoots for ensuring the stable and efficient operation of the photovoltaic micro-inverter system. The proposed maximum power point tracking technique is integrated to a two-stage grid-connected micro-inverter system and tested in terms of the aforementioned performance parameters. The performance analyses of the developed technique are performed under various scenarios by utilizing the PSCAD/EMTDC platform. The obtained results reveal that the rate of overshoots is decreased by 0.6 A while the convergence speed is accelerated by 1.4 s. In comparison with traditional MPPT techniques, tracking accuracy, steady-state stability, and robustness of the whole system are remarkably improved along with increasing overall system efficiency by 4%. It is also worth pointing out that the complexity level of the control technique is significantly reduced by the equation obtained through the symbolic regression analysis. [ABSTRACT FROM AUTHOR]

The extraction of PV cell and module parameters is vital for the accurate simulation of PV systems. PV cell exhibits non-linear nature of I – V and P – V curves. Hence, parameters estimated at the optimum value of the current error criterion, such as root mean square error (RMSE) of current, may not give accurate power estimation at maximum power point (MPP). In this work, the shortcomings of the single objective optimization (SOO) approach based parameter estimation methods are assessed using two different problem formulations: compound objective function and weighted sum. The results from the SOO approach indicate that weightage assigned to objectives such as RMSE and the percentage relative power Error at MPP (% RPE) has impacted the accuracy of parameter estimation. The selection of weightage for each objective is indeed a difficult choice to make. Moreover, the obtained cumulative value of RMSE and % RPE is high. In order to overcome these shortcomings of the SOO approach, a multi-objective optimization (MOO) approach based parameter estimation is formulated. Then formulated MOO problem is solved by using the proposed nondominated sorting cuckoo search optimization (NSCSO). Combining nondominated sorting, a crowded comparison technique, and Lévy flight characteristics, the NSCSO algorithm is proposed, which is inspired by both the NSGA-II and NSCS algorithms. Results indicate that the proposed parameter estimation method based on the MOO approach using NSCSO has given the optimum value for cumulative RMSE and % RPE in comparison with the SOO approach using the CSO algorithm. The proposed method is also validated on various PV models: PVM 752 (GaAs thin film) cell, STM6-40 (monocrystalline), and STP6-120/36 (polycrystalline) silicon modules. • The multi objective optimization approach based parameter estimation of PV cell and module is proposed. • A new NSCSO algorithm is proposed. • Weighted Sum method is applied to formulated objective functions for parameter estimation of PV cell and module. • The deficiency of single objective optimization based parameter estimation of PV cell is established. • The performance of the NSCSO algorithm is compared with NSCS and NSGA-II algorithms. [ABSTRACT FROM AUTHOR]

The partial shading phenomenon in some modules of the PV arrays limits the total current of the series modules and reduces the total output power. In this paper, a power electronic compensator with a multi-winding transformer is presented to recover the undelivered energy of the shaded modules. The proposed configuration compensates reduced currents due to the partial shading on the series modules by injecting the required currents into parallel circuits of the shaded modules. The unshaded modules provide the compensatory currents by creating a common flux into the core of the multi-winding transformer. The average current and the output power of the PV array are considerably improved under partial shading conditions. The proposed configuration has a very simple and sensorless control structure, and its power electronic elements are less than other improving configurations. The simulation and experimental results confirm the presented analytical relations and desirable performance of the proposed configuration to recover the undelivered energy of the PV array under the partial shading conditions. • The proposed configuration recovers the undelivered energies of the shaded modules. • The presented compensator has a very simple and sensorless control structure. • The method can enhance the PV output power under all shading patterns. • Energy recovery is considerable than the fixed and dynamic reconfiguration methods. [ABSTRACT FROM AUTHOR]

Detecting the maximum power point in the photovoltaic (PV) system under normal and shaded weather conditions with high accuracy is vital to save the harvested power. Providing a robust model that emulates the physical behavior of a combination of particular solar modules is the core of designing a reliable PV system. As the PV models' parameters are not provided in the manufacturing datasheets, there is a persistent need to introduce an efficient and competent tool that provides the optimal parameters of the PV models. Therefore, this paper presents a novel strategy depending on a novel fractional calculus-based optimization technique to detect the optimal parameters of the PV models. The identified parameters globally fulfilled all tested shading conditions of different types and configurations of PV modules, strings, and arrays to verify the optimizer reliability and efficiency. A novel optimization algorithm called an Adaptive Fractional-order Archimedes Optimization Algorithm (A-FAOA) is proposed to identify the single and double diode model parameters for several PV solar cells/modules under various environmental conditions. The proposed algorithm uses a fractional-calculus memory perspective to enhance the exploration stage of the basic Archimedes Optimization Algorithm. In addition, the two-dimensional-Henon map is adopted in the algorithm to tune its parameters adaptively in an attempt to achieve a smooth transition between the exploration and exploitation phases. The developed technique is tested on several experimental datasets for several PV cells/modules under diverse environmental conditions. The proposed algorithm is compared with the recent literature based on statistical analysis and non-parametric tests. Moreover, the fitting curves and the values of error at the maximum power points are provided to demonstrate the superiority of the proposed method. For further evaluation of the reliability of the identified parameters, several PV systems based on the studied modules are implemented under uniform and partial shading conditions to affirm the accuracy of the identified parameters in representing a complete connected system under several environmental phenomena. The considered PV systems include three different strings (3x1, 6x1, 9x1) and three different arrays (3 × 2, 6 × 3, 9 × 9). High accuracy, robust performance, and minor deviation between the experimental and estimated curves are evident in the results. • Proposing an optimal modeling of a large integrated PV array system. • Proposing a novel strategy to detect the optimal parameters of the photovoltaic models. • Proposing a new Adaptive Fractional-order Archimedes Optimization Algorithm (A-FAOA). • Optimizing single and double diode model parameters for several photovoltaic solar cells/modules. • Considering different partial shading condition in this large system. [ABSTRACT FROM AUTHOR]

• The current efficiency maps of different spectral are obtained uniformly. • Both spatial and spectral dimensional correlation are explored simultaneously. • Defects under different spectra can be more finely distinguished. • The inspection speed of compressive sensing based LBIC has been further accelerated by additional dimensions. The Compressive Light-Beam-Induced Current (CLBIC) method has garnered considerable attention as an emerging fast Light-Beam-Induced Current (LBIC) technique. The detection speed can be enhanced by a factor of 10 through coded undersampling measurements, in comparison to the standard LBIC method. However, the CLBIC method's detection speed is still constrained by the sampling rate (number of sampling times), given that the reconstruction time is negligible for high-performance processors. This limitation poses a significant challenge in the context of multi-spectral assessment of photovoltaic cells, as the prolonged measurement time is required to repeat CLBIC measurements across various spectral bands. This paper introduces a Multispectral Compressive Light-Beam-Induced Current (MCLBIC) method for the multi-spectral assessment of photovoltaic cells to expedite the measurement time. This method can reconstruct the current map of the photovoltaic cell at a lower sampling rate through joint coding of the multi-spectral matrix and solving a multi-objective convex optimization problem. The feasibility of the proposed method and its detection performance are evaluated using a typical three-spectrum MCLBIC measurement model. Simulation and experimental results demonstrate that the MCLBIC method reduces the number of required sampling times for measurement by 40% compared to the CLBIC method, while maintaining reasonable accuracy. This suggests that the MCLBIC method can further accelerate the detection speed by 40%, based on the CLBIC method. This advantage implies significant potential for enhancing the detection speed in the large-scale multi-spectral evaluation of solar cells. In summary, the proposed method holds promise for improving the efficiency and speed of the detailed evaluation of photovoltaic module characteristics. [ABSTRACT FROM AUTHOR]

• Integration of phase change materials in tensile membrane structures. • Solar radiation and ambient temperature greatly affect the thermal performance. • Low thermal conductivity of this novel integration can cause overheating issues. • Control strategies to counter the overheating issue were implied. The performance of photovoltaic (PV) systems is known to degrade with temperature increase. To mitigate this issue, Phase Change Materials (PCMs) are utilized to regulate the temperature of PV modules. Many researchers have addressed the utilization of PCMs for thermal regulation of building integrated PVs (BIPV-PCM systems). Potential of integrating PV-PCM systems into membrane structures is relatively unexplored, it represents the novelty of this study. This paper explores the potential advantages and challenges of the thermal performance of OPV-ETFE foils with and without PCM integration under varying conditions. A detailed parametric analysis has been carried out to assess the impacts of ambient conditions and PCM properties under standard testing conditions. The results of this investigation offer critical insights into the thermal dynamics of OPV-PCM-ETFE modules and their application in building environments. A range of PCMs is analyzed and notably, Rubitherm-28 outperformed them, offering a 20-minute delay in temperature rise, showcasing its efficacy in thermal regulation for the OPV-PCM-ETFE module. Additionally, results indicate that an increase of 100 W/m2 in solar radiation or 5 °C in ambient temperature consequently raised the OPV surface temperature by 5 °C. PCM thickness emerged as a critical factor for this integration. Each millimeter of PCM thickness adds approximately a 2-minute delay to the melt duration but owing to the low thermal conductivity property of both ETFE and PCMs, larger thickness can cause overheating issue. Therefore, it is recommended to use PCMs with higher latent heat capacity and melting points at least 10 °C above ambient temperature. The multi-parametric analysis further validated the flexibility of this approach across various conditions. An adaptive control strategy, informed by these findings, demonstrated potential for enhancing thermal management in OPV-PCM-ETFE modules using different control criteria. The adaptive control strategies help to optimize the thermal performance of the system and mitigate any potential overheating issues. [ABSTRACT FROM AUTHOR]

In DC microgrid, photovoltaic systems (PVSs) typically operate in the maximum power point tracking (MPPT) mode, while the DC bus voltage is maintained only by the energy storage system (ESS). Therefore, to guarantee the bus voltage stability of DC microgrids, large-scale ESSs are generally required, that increases the investments and maintenance costs. This paper presents an adaptive power point tracking (APPT) control method to make the PVS operate in the grid-supporting mode and provide active voltage regulation for DC microgrid, which can reduce the requirement of ESS. A virtual inertia control method is also proposed to make the ESS operate in the grid-forming mode and simulate the dynamic characteristics of the synchronous machine. Moreover, adaptive non-singular terminal sliding mode control (ANTSMC) loops are proposed for the voltage and current control loops of the Buck-boost converters, which can effectively improve the voltage regulation performance. Detailed results of real-time simulation based on StarSim Hardware-in-the-loop (HIL) platform demonstrate the superior performance of the proposed novel control strategy. • Cascaded voltage and current control methods based on adaptive non-singular terminal sliding mode control (ANTSMC) are proposed for the Buck-boost converters, which interfaces the photovoltaic system and energy storage system into the DC microgrid. It offers faster response and robustness than PI and NTSMC control algorithms. • An adaptive power point tracking control algorithm is proposed for the photovoltaic system, that can adaptively adjust the output power according to the fluctuation of the DC bus voltage, and then can make the photovoltaic system participate in the voltage regulation. • A voltage recovery control strategy based on VIC is designed for ESS with sufficient inertial response capability to better play the role of grid-forming. [ABSTRACT FROM AUTHOR]

• This paper integrates bifacial photovoltaics as sunshades into buildings. • The impact of installation and building factors on power generation is studied. • The impact of installation factors of bPV on the energy savings is studied. • The south orientation, small tilt angle and wide bPV are recommended to install. • The buildings with high wall reflectivity and low WWR achieve more energy savings. Solar photovoltaic (PV) shading systems are of great significance for achieving low-carbon buildings. Bifacial photovoltaics (bPV) is a promising technology that can generate electricity from both the front and rear sides of bPV modules. By integrating bPV shading systems into buildings, more power generation and less building energy consumption can be achieved compared to traditional shading systems. This study aims to integrate and optimize bPV shading systems into the building vertical façades in hot and humid regions, considering varying installation and building parameters. The evaluations of electricity generation and energy saving were conducted based on a typical three-story office building in Hong Kong. The evaluation of electricity generation reveals that the optimal installation condition for bPV sunshades in Hong Kong is south orientation with a tilt angle of 35°. Regarding the width of bPV sunshades, as the width increases, the annual electricity generation per unit area (AEGPA) decreases, but the total annual electricity generation (TAEG) increases. Besides, the bifacial gain of optimized bPV sunshades increases from 3.3% to 6.1% as the wall reflectivity increases from 0.15 to 0.7, while being insensitive to window reflectivity. Similarly, when the window-to-wall ratio (WWR) increases, the bifacial gain decreases. Furthermore, the energy-saving evaluation indicates that the south orientation with small tilt angles and wide sunshades tends to achieve much more energy savings benefits. The findings of this study provide practical guidance for maximizing the power generation and optimizing the design of building-integrated bPV sunshades to achieve maximum energy savings. [ABSTRACT FROM AUTHOR]

• Novel Grecian Reconfiguration (NGR) is proposed and experimentally validated. • Proposed NGR is tested under 8 realistic shadings with 6 performance indices. • Proposed NGR reduces shading loss up to 37.04% to 91.91% over other models. • Experimentally, NGR boosts global power by 5.95% to 30.36% over other models. • Proposed NGR can be implemented on any solar array dimension. Partial shading conditions (PSC) degrade the maximum power production from the solar arrays. It generates shading losses which is dependent on the quantity of shade spread out on the solar array. This research proposes a novel Grecian square reconfiguration (NGR) for a 4 × 4 solar array to prevent shading issues. This novel technique is extensively compared with other benchmark solar models like total-cross-tied (TCT), kendoku (KDT), odd–even (OER), and skyscraper reconfigurations (SSR). The effectiveness of the proposed NGR is validated under four complex shadings. A thorough comparison of the proposed NGR is made based on several performance parameters like global power (GP), shading loss (SL), fill factor (FF), efficiency (Ƞ), power gain (PG), and execution ratio (ER). The experimental outcome validates the MATLAB/Simulink results, denoting the excellent performance of the proposed NGR over the existing TCT, KDT, OER, and SSR respectively. The proposed NGR magnifies the global power by 30.36%, 9.53%, 5.95%, and 21.38% under corner shading against TCT, KDT, OER, and SSR schemes. Also, under oblique shading, the shading loss is reduced by 72.04%, 91.91%, 37.04%, and 44.68% by the proposed NGR against TCT, KDT, OER, and SSR schemes. The outstanding performance of the proposed NGR against the TCT, KDT, OER, and SSR schemes under the considered shadings depicts its supremacy in handling shading issues effectively. [ABSTRACT FROM AUTHOR]

• An enhanced political optimizer (QNMPO) is proposed to realize the extraction of photovoltaic models parameters. • The performance of the proposed QNMPO algorithm is compared with some well-known competing algorithms. • The stability performance of QNMPO was tested on three commercial PV models at different temperature levels and irradiation levels. • QNMPO exhibits better convergence speed and accuracy. Evaluating the PV system parameters is crucial for the more efficient utilization of sustainable solar energy. Due to PV systems' nonlinear and multimodal nature, efficient evaluation of PV system parameters is still a very challenging task. This paper proposes an improved political optimization algorithm, namely the QNMPO algorithm, which combines quantum rotation gate and Nelder-Mead simplex (NMs). It can be used to evaluate unknown parameters of PV systems and solar cells efficiently. In QNMPO, the quantum rotation gate method can rotate the population of agents to a more favorable position for finding the optimal solution, making the individuals in the middle of the population communicate more frequently and enhancing the population's diversity. In addition, the NMs method can improve the solution quality by better searching the neighborhoods near the optimal solution and then strengthen the advantage of local development of the algorithm so that it can converge to the global optimal solution faster. The developed QNMPO algorithm extracts the unknown parameters for single diode, double diode, triple diode and photovoltaic modules in this study. It is compared with some other representative algorithms. The experimental results show that QNMPO outperforms similar algorithms in convergence speed, solution accuracy, and better solution performance. QNMPO was then used to successfully extract the best parameter values for three real PV models (three commercial PV models (thin-film ST40, monocrystalline SM55, and multi crystalline KC200GT)) at different temperatures and different irradiance levels. The results also show that QNMPO performs consistently and accurately enough under varying temperatures and irradiation. Therefore, the QNMPO algorithm proposed in this paper can be a promising parameter extraction method for solar PV systems with good performance. [ABSTRACT FROM AUTHOR]

Funnel type solar cookers are simple and effective. Most of them rely on a multifaceted reflector to concentrate solar radiation on a cooking pot that is placed inside a transparent enclosure to create a greenhouse effect. The analysis of the resulting optical system is a complex task, as multiple reflections occur. The overall performance of funnel solar cookers is strongly affected by their optical efficiency. There is a lack of information in academic literature about this important research topic. This work aims to fill this gap presenting an optical performance analysis of a funnel solar cooker with only azimuthal sun tracking. Open-source numerical ray-tracing software Soltrace is used to investigate relevant characteristics such as the intercept factor, optical efficiency, dependency on incidence angle, performance of each reflecting surface and irradiation density flux distribution on different surfaces of the cooking pot. Some important results for beam radiation at normal incidence are the intercept factor, determined to be 0.664, and the optical efficiency with realistic optical properties, that turned out to be 0.370. When the incidence of solar beam radiation is not normal, optical efficiency remains above 90% of its normal incidence value, if the alignment errors are less than 10°. • Numerical ray tracing is used to perform optical characterization of a funnel solar cooker. • The optical efficiency with perfect optical properties at normal incidence is 0.664. • The optical efficiency with realistic optical properties at normal incidence is 0.370. • The dependence of optical efficiency on the angle of incidence angle is investigated. • Irradiation density flux maps on cooking pot surfaces are presented. [ABSTRACT FROM AUTHOR]

Upscaling techniques are applied to estimate the total power feed-in by PV systems in control areas by grid operators. In order to improve the real-time upscaling of PV power production in the control area of the German transmission system operator TransnetBW we set up a network of 40 solar irradiance measurement stations in southern Germany. The measurement stations consist of a pyranometer, measuring global horizontal irradiance, and three silicon cells oriented east, south, and west with tilt angles of 25°, measuring global tilted irradiance. Irradiance values in minute resolution are transferred in near real-time. In order to ensure a good quality of our data we have developed a new quality control scheme exploiting the sensors with different orientations. Starting with data from September 2020, we will make the quality controlled minute-resolution measurements publicly available on a monthly basis. • Horizontal and tilted global irradiance measurements for 40 sites. • Publication of data set in minute resolution with monthly updates. • New quality control scheme for tilted irradiance. • Machine learning for detection of shading and orientation. [ABSTRACT FROM AUTHOR]

• Characterization of PV string performance by temperature-correcting the V mp and I mp. • Temperature correction formulas of V mp and I mp of PV strings under MPPT were verified. • Partial shading and activation of bypass diodes etc. can be sensitively detected. • Applicable to most kinds of crystalline silicon PV strings without modification. Improvement of the quantitative performance characterization of photovoltaic (PV) strings was investigated, based on their monitoring data during maximum power point tracking (MPPT) operation. The maximum power voltage V mp and current I mp of the PV strings under MPPT were continuously monitored, and corrected to standard temperature of 25 °C by using the temperature correction formulas, which were recently developed for PV modules. The irradiance G was measured by using a PV module irradiance sensor. It was verified that the formulas are applicable to PV strings, enabling reproducible temperature correction of V mp and I mp with relative standard deviation (σ) of about 0.4–0.9% under various weather conditions. Comparison of the outdoor results with indoor current–voltage curve measurements of the constituent modules in the strings showed that the maximum output power P max under the standard test conditions STC, i.e. 25 °C and 1 kWm−2, estimated from the temperature-corrected V mp and I mp , agreed with the indoor result typically within ±1.5%. The experimental results also showed that other information of the string such as partial shading and activation of bypass diodes can be also sensitively detected by analyzing the temperature-corrected V mp and I mp. The outdoor measurements and data analysis of this study can be carried out without stopping the MPPT operation of the string. The analysis is performed by using the real-time data. The present method is expected to be applicable to most kinds of crystalline silicon PV strings without modification. [ABSTRACT FROM AUTHOR]

[Display omitted] • Translation equations introduce bias in the power and device parameters of a module. • Device parameters transform algebraically with irradiance and temperature. • Module degradation assessment, based on translated I-V curves, is not advisable. Photovoltaic modules are rated at standard test conditions, STC, but in real life operation they are exposed to very different conditions. The power of a module and its device parameters are obtained from the current-voltage characteristic (I-V curve) of the module but the curve varies with irradiance and temperature conditions. The I-V curve is transformed from real operational conditions to STC and vice versa with translation equations. In this paper we investigate the fundamental nature of the translation equations and show that they introduce consistent bias in the power and device parameters, obtained from the translated I-V curves. We show that the nature of the translation equations forces the device parameters to transform from one to another set of irradiance and temperature conditions by algebraic transformations, which are derived in this paper. Validation of our findings is given for the series resistance. Our findings have significant implications for the assessment of module degradation. [ABSTRACT FROM AUTHOR]

[Display omitted] • Partial shading is detected on-time without disconnection of load from PV array. • Short circuit current measurement is not required in the proposed technique. • Sensor requirement is less than the conventional technique hence cheaper. • Quick detection of partial shading leads to more energy extraction. • Mismatch loss is greatly reduced in the proposed technique. Mismatch losses due to partial shading condition (PSC) is not permitted to extract maximum power from the solar PV array. Numerous techniques were proposed to reduce the partial shading effect. But the major problem is in finding out the occurrence and its distribution of the partial shading in the solar PV array. Conventional methods disconnect the load temporally from the PV array and measure the short circuit current (I sc ) and use the information to detect the partial shading. Frequent disconnection of the solar PV array from the load makes the conventional method unpractical in a large solar power plant and even a stand-alone PV system. A novel on-time partial detection technique is proposed in this paper and useing difference in row voltage (V d) instead of the short circuit current (I sc ) to estimate the partial shading. Greater the V d infers the severity of occurrence of the partial shading in the solar PV array. By using a static reconfiguration and then a modified couple matching (MCM) technique the voltage difference (V d) gets reduced. This will ensure the mitigation of the PSC. As in this proposed technique, the load never be disconnected from the solar PV array, to detect the partial shading, it can be used practically even for a stand-alone PV system. Eight extensive partial shading patterns are simulated using MATLAB Simulink to validate the proposed work and the size of 3 × 4 120 W polycrystalline PV panel array is used for the experimental validation. [ABSTRACT FROM AUTHOR]

• The study focuses on examining different PCMs to be used in PVT systems. • Hybrid PCMs were produced from mixing Vaseline and paraffin. • Vaseline mixes with paraffin and reduces its melting point. • Lower melting point of the PCM corresponds to an increase in the heat flow rate. • Best cooling results were obtained when using the hybrid PCM. The use of phase change materials (PCMs) in photovoltaic-thermal systems (PVT) is essential for developing PV systems and raising their productivity. PCM is distinguished by its many variations and properties, the most important of which is the melting point. In this study, the driven question and focus was on investigating which is better for use in a PVT, PCM systems with a high or low melting point? Two types of PCM were used in the study: paraffin wax (melting point 45 °C), Vaseline -petroleum jelly (melting point of 25 °C), and hybrid PCM (mixtures of the two PCMs in proportions of 25%, 50% and 75%). The study was conducted indoors by simulating the harshest condition in Iraq's weather in summer. The results showed that the wax and the Vaseline mixed entirely with an apparent decrease in the product's melting point. In contrast, the rest of the thermophysical properties of the product were relatively affected. The use of paraffin, petroleum jelly and 50% paraffin + 50% Vaseline in the PVT system caused a decrease in the surface temperatures of the photovoltaic cell, which resulted in a more significant improvement in the performance of the system. The maximum electrical efficiency reached was 13.7%, while the maximum thermal efficiency was 39.0%. Reducing paraffin melting point leads to better performance of PVT systems, as the hybrid paraffin (50% wax + 50% Vaseline) have better productivity than pure paraffin wax due to its lower melting point. [ABSTRACT FROM AUTHOR]

• Renewable tensegrity structures are viable for lightweight, low-cost PV racking. • A novel algorithm integrates tensegrity into standard PV system design workflow. • Locally sourced timbers, such as bamboo, can be used as tensegrity members. • Tensegrity support structures can reduce solar PV racking costs by as much as 77%. • Enables versatile applications of PV, such as agrivoltaics and water canal covering. Rapid decline in the cost of solar photovoltaic (PV) modules and associated electronics has elevated the significance of structural balance of systems (BOS) in the system cost composition. In this study tensegrity, a bio-inspired structure made of bars as compression members and strings as tensile members, is evaluated as an economical racking solution for solar photovoltaic arrays. For the first time, the electrical aspects of solar photovoltaic system design have been unified with the structural aspects of tensegrity through a novel algorithm. The end-to-end system design framework is validated through modelling of a practical system with System Advisor Model (SAM), a standard design tool by National Renewable Energy Lab (NREL), in congruence with the minimal mass planar bridge tensegrity model implemented in MATLAB. This algorithmic demonstration establishes tensegrity as a technically viable system design approach and assesses the significant reduction in racking material weight leading to maximum cost savings up to 77%. The technical compatibility, ease of installation, logistic efficiency and economic benefits of tensegrity-enabled racking would accelerate wide-scale adoption of solar energy across the world. It is also conducive to high-impact applications of solar energy such as water canal covering and shaded agriculture. Additionally, tensegrity configuration provisions the use of locally grown timbers like bamboo as the compression member which benefits developing regions through local sourcing, fast installation, carbon capture and farming incentive. Tensegrity also unlocks the research avenue for adding modularity and portability to solar PV systems leveraging its controllable dynamic properties. [ABSTRACT FROM AUTHOR]

[Display omitted] • Further improvements to an empirical model for photovoltaic performance is proposed. • Attenuation of the incoming light due to reflections on the module surfaces plays a key role. • Data recorded in a plant connected to the Cuban Electric System support the calculations. • A severe cost depletion of PV system by a factor two is also forecast in the next twenty years. Photovoltaic power generation capacity is increasing tremendously as a result of strong renewable energy policies and environmental concerns. In particular, the use of solar modules to generate electricity has grown significantly in Cuba recently. Based on the statistics published by the European Commission, the installed capacity of the photovoltaic modules increased from 15 to 100 MW in the timeframe of 2015–2019. In this context, efficiency is one of the most critical figures of merit of a photovoltaic module. It describes the ratio of the produced electrical power to the received solar irradiance. In this work, a widely-used model of efficiency is considered, and the incorporation of the pre-module losses due to light reflections is our original contribution. Experimental data recorded during eight months in a plant connected to the Cuban National Electric System are employed to examined and check the proposed approach. Our findings provide a key achievement in the estimation of the module efficiency within a system. In addition, based on the previous results, we perform a rough evaluation of the prevision of the photovoltaic system energy production using levelized cost of energy within the framework of the discounting method, showing a drastic drop by a factor two in the coming two decades. [ABSTRACT FROM AUTHOR]

• The effect of dust accumulation on the performance of three solar tracking PV modules is investigated. • The modified angular losses coefficient (α r) is calculated at different tilt angles and a dust deposition density. • The α r coefficient is used by a computational method to predict the power generation of solar tracking modules. • The proper performance of the α r coefficient is examined using the results of previous experimental studies. • The reduction in electricity generation and temperature distribution of the modules are calculated. Providing a suitable method for predicting the effect of particle aggregation on photovoltaic (PV) performance can be one of the best ways to make better use of solar energy. In this study, a mathematical method was used and modified to provide a better prediction of angular losses coefficient (α r). The modified coefficient as well as a computational method were used to find the performance of dusty modules equipped with one-axis (East-West (EW), North-South (NS)), and dual-axis (DAT) solar tracking systems. The modified α r , which here is called the degree of surface dirtiness, can be used to estimate the area covered by particles per cm 2 , i.e. A ∗ C (θ). A better prediction of α r causes a better prediction of power loss due to dust settlement. Results showed that A ∗ C (θ) is the factor that shows the role of incidence angle in visualizing the type of dust cover, while α r shows the effect of slope angle on dust deposition density. Furthermore, combination of α r with the computational model revealed that the dirty DAT module has the least daily power loss which is 9% of the clean counterpart power. The power losses for the NS and EW dusty modules are 13% and 20.5% lower than the clean counterparts, respectively. It should be noted that the obtained results in this study are in a good compromise with the experimental and computational data available in the literature. [ABSTRACT FROM AUTHOR]

• A homogeniser inspired by the crustacean's eye using for the CPV system. • Such homogeniser can evolve a uniform version of light distribution. • The best structure displays a uniformity ~85% and an optical efficiency ~90%. • Toward relaxing a secondary mirror in the existing CPV system using a parabolic mirror. We devise an implicitly new design for boosting the light uniformity in the concentrated photovoltaics (CPV) system, whereby addressing the overheating issue of the PV cell and enhancing the electrical cell efficiency. Rather than using a well-known system of the Cassegrain concentrator design, consisting of double mirrors + a homogeniser, in this study, we mimic a structure of crustacean's eyes for a design of homogeniser, consisting of an array of a mirror channel. Such proposed design allows making use of only a primary parabolic mirror + a homogeniser to concentrate and redistribute the sunlight, representing a large departure from virtually all of the previous studies. Specifically, such homogeniser can furcate the light beam into the small channels/trenches, redirect the light ray at the reflective plate and probably mix them to evolve a uniform version of light distribution. In general, the homogeniser can affect the uniformity and optical efficiency, which are good probes to assess the light performance, in a number of ways. We found that light performance depends sizably on the structural parameters such as the size and the number of channels of the homogeniser. The best structure displays a calculated uniformity of ~85% of the flux distribution on solar cell and a calculated optical efficiency of ~90% of the entire CPV system. We also assess the light performance against some scenarios of error in installation and operation processes such as tolerance and misalignment and compare well with the current design. The compelling of this proposed design is highly efficient light performance, compactness and inexpensive, which likely address virtually existing bottlenecks in the CPV system. [ABSTRACT FROM AUTHOR]

• Sky-Cloud Segmentation under low illumination. • Solar Irradiance Forecasting Correlation with Cloud Fraction. • Pre-emptive method to manage solar variability. This paper presents a novel approach to calculate cloud cover under any illumination conditions for short-term irradiance forecasting. A sky-imaging system, in parallel with an irradiance measurement, is set up to collect a database of sky images and irradiance readings. The colour space operations and various image segmentation methods are investigated to improve the visual contrast of the cloud component. Experimental results shows the effectiveness of applying the Normalized Blue-to-Red Ratio (NBRR) colour operation for high-illumination condition and the Red/Green channel for the low-illumination condition. The pre-processed sky images are then fed into Minimum Cross Entropy (MCE) adaptive thresholding segmentation, which effectively differentiates the sky and cloud components for all-sky images. The cloud fraction calculation is employed for the segmented images as an indication of cloud coverage. The proposed method demonstrates a positive linear correlation between cloud fraction and real-time irradiance data. [ABSTRACT FROM AUTHOR]

• A more consistent method to assess the performance of PV pumping systems. • Investigation of the effect of motor efficiency on PV pumping systems performance. • Detailed performance evaluation of PV pump systems based on the characteristics of a conventional centrifugal pump as well as local climatic information. Every centrifugal pump has an optimum efficiency duty point, known as Best Efficient Point (BEP), which is usually specified by the manufacturer. In conventional pumping systems, the centrifugal pump must operate at the rated speed and as close as possible to the BEP for optimal performance. This design approach, based on the BEP concept, is suitable only when the centrifugal pump is supplied by sources that can maintain the pump's operation at the rated frequency (50 Hz or 60 Hz) and voltage (220 V or 380 V). In photovoltaic pumping systems, the conventional centrifugal pump works at different speeds according to the availability of solar irradiance. Therefore, the BEP concept does not offer the best performance in terms of efficiency. This paper presents a method to determine the operating point that provides maximum efficiency for a given photovoltaic pumping system composed of a conventional centrifugal pump driven by a power control system. This point, referred to as Solar Best Efficiency Point (SBEP), is calculated considering the entire operating range of the pump for a given irradiance and photovoltaic cell temperature profile. According to the results, the SBEP operation, compared to the BEP operation, can increase the daily efficiency of the photovoltaic pumping system by up to 6.7%, depending on the centrifugal pump used. Furthermore, the theoretical approach developed in this paper shows that the selection of the motor-pump set cannot be based solely on the pump's characteristics, as the motor quality significantly influences system performance. [ABSTRACT FROM AUTHOR]

• M3S allows the monitoring of the I-V curve without disconnecting the PV module. • PV modules transient response from a fast characterization system is analyzed. • The entire measurements are performed in 5 ms. • A methodology is proposed to correct the hysteresis effect on dynamic I-V curves. • Static I-V characteristic is estimated around MPP with an error below 0.8%. Failures of single photovoltaic (PV) modules lead to significant power losses in large PV systems. Individual and periodic monitoring of each PV module is a powerful way to detect these losses. Recently, a novel monitoring method, named Module to Module Monitoring System (M3S), has been proposed. This monitoring method, without disconnecting the PV module from the rest of the system, is able to produce and measure small variations around the operating point of the PV module. The entire measurement is performed in less than 5 ms, using only low-power components. For current high-efficiency PV modules, these short measurement times generate a hysteresis effect in the current–voltage (I-V) curve during the transient-state, which makes it difficult to directly estimate the static I-V characteristics of the PV module. In this work, the transient response of the PV module is analyzed and a methodology to correct the hysteresis effect and estimate the I-V characteristics is implemented. From the obtained dynamic measurements, the proposed methodology is able to estimate the I-V characteristics of the PV module around the operating point with a mean squared error below 0.8%. [ABSTRACT FROM AUTHOR]

• An improved control strategy for charging solar batteries is proposed. • Design of a digital anti-windup control strategy for PI compensators. • A three-stage battery charging current regulation method is introduced. In off-grid photovoltaic (PV) systems, a battery charge controller is required for energy storage. However, due to unstable weather conditions as well as the frequent variations in load demand, the PV power flow delivered to the load could be fluctuated while the battery charging efficiency will be reduced. To overcome these issues, this paper presents an improved power balance control strategy based on two proportional and integral (PI) compensators only, which can adequately balance the PV power flow delivered to the DC load and the battery, so that the PV power is effectively utilized and the battery is properly charged. First, a modeling of the entire system based on the linear PV array model is performed to simplify the design of the PI compensators. In addition, four operating modes are adapted to deal with the aforementioned issues regarding any variation in weather conditions and load demand. Namely, Maximum Power Point Tracking (MPPT)-mode, Non-MPPT mode, Night-mode, and Off-mode. Afterwards, a digital anti-windup control strategy associated with PI compensators is also developed to ensure a smooth switching from an operating mode to another. Moreover, an improved Incremental Conductance IC-MPPT algorithm is adopted to extract the maximum power from the PV array. Finally, MATLAB/SIMULINK simulations are carried out and the results obtained demonstrate the good performance of the proposed control strategy under different atmospheric conditions, both in power balance control and MPPT control, notably in terms of efficiency (99.79%), steady-state power oscillations (0.03 W), and convergence time (0.03 s). [ABSTRACT FROM AUTHOR]

• This research paper deals with design and development of PV emulator for testing of MPPT algorithm and Battery Charger controller using GA optimized PI controlled DC-DC Buck converter. • Genetic Algorithm has been used to optimize the parameter of the PI controller to emulate the exact behavior of the reference PV model. • The proposed GA optimized PI controlled DC-DC Buck converter based PV emulator provides the successful operation in three region i.e., constant voltage region, variable voltage and current region and constant current region. • The proposed PV emulator has been tested with perturb and observe maximum power point tracking algorithm and constant voltage battery charging control. • The PV emulator was also tested with MPPT algorithm and solar MPPT battery charging control algorithm and it has maximum power point extraction ratio of 97.45% and charging efficiency of 93.9%. • The proposed PV emulator has been successfully realized in real time with low cost microcontroller i.e., control logic for the PV emulator was implemented using Arduino ATmega board. • The developed model was tested and IV and PV characteristics are compared with PV reference model and observed that PV emulator has an emulation efficiency of 98.2%. In this paper, PV emulator is developed using double loop PI controlled DC-DC buck converter. Ambient environmental conditions such as irradiance, temperature and wind speed are considered for creating PV reference model in the PV emulator. The simulation model of the proposed PV emulator is created and tested using MATLAB Simulink package. To validate the effectiveness of the proposed PV emulator, it is tested with different operating conditions such as varying irradiance, temperature and wind speed. The current–voltage and power-voltage characteristic of the PV emulator is compared with PV reference model. The suitability of the PV emulator is tested with MPPT algorithm and battery charging controller in addition to number of objectives. Real time testing of the proposed PV emulator is done experimentally and also corresponding results are discussed. The proposed Solar PV emulator has the following properties: (1) higher bandwidth DC-DC buck converter, (2) extremely reliable performance with lower response time, and (3) lower output voltage and current ripple. [ABSTRACT FROM AUTHOR]

[Display omitted] • A novel cell-level anomaly segmentation pipeline for solar panels is proposed. • Several cutting-edge deep learning techniques are used to achieve robust performance. • Electroluminescence images reveal the most slight and subtle anomalies. • Multiple data sources are combined and augmented to create a diverse dataset. • Weakly supervised model is used to infer high-level information from low-level knowledge. In the operation & maintenance (O&M) of photovoltaic (PV) plants, the early identification of failures has become crucial to maintain productivity and prolong components' life. Of all defects, cell-level anomalies can lead to serious failures and may affect surrounding PV modules in the long run. These fine defects are usually captured with high spatial resolution electroluminescence (EL) imaging. The difficulty of acquiring such images has limited the availability of data. For this work, multiple data resources and augmentation techniques have been used to surpass this limitation. Current state-of-the-art detection methods extract barely low-level information from individual PV cell images, and their performance is conditioned by the available training data. In this article, we propose an end-to-end deep learning pipeline that detects, locates and segments cell-level anomalies from entire photovoltaic modules via EL images. The proposed modular pipeline combines three deep learning techniques: 1. object detection (modified Faster-RNN), 2. image classification (EfficientNet) and 3. weakly supervised segmentation (autoencoder). The modular nature of the pipeline allows to upgrade the deep learning models to the further improvements in the state-of-the-art and also extend the pipeline towards new functionalities. [ABSTRACT FROM AUTHOR]

• The algorithm obtains a spatially DNI estimation with a multi-robot sensor network. • The algorithm approaches both the generation of tasks and the estimation of DNI. • The clouds and exploring unknown areas are needed to generate new tasks. • The framework is modular and additional information sources can be considered. An algorithm for mapping Direct Normal Irradiance (DNI) in thermosolar power plants using a Mobile Robotic Sensor Network (RSN) is presented. The algorithm selects measurement spots and allocates the RSN accordingly to carry out the dynamic estimation of DNI. A generic thermosolar power plant with a fleet of vehicles is used as a simulated case study to assess the performance of the algorithm. The results show that the proposed method allows us to obtain a spatial estimation of the DNI that could improve the performance of the plant, and that outperforms estimations based on a single pyrheliometer. [ABSTRACT FROM AUTHOR]

• A novel probability algorithm based on fuzzy information diffusion is proposed to track the global maximum power point. • This method is a probabilistic algorithm based on interval estimation. • Without the random searching process, this method can track the maximum power point quickly. Under stochastic partial shading conditions, the photovoltaic power system often produces a non-convex characteristic curve. It makes the maximum power point tracking a difficult task. In this paper, based on fuzzy information diffusion, a novel probability algorithm is proposed to track the global maximum power point (GMPP) under partial shading conditions. By uniform incomplete sampling and information diffusion, the proposed method can avoid the random searching process of intelligence algorithms, which will effectively improve the tracking speed and global search capability. From the perspective of probability estimation, the information diffusion function is used to fill the information gap caused by incomplete sampling data, thus transforming the discrete sampling points of PV system into a continuous distribution function. According to the fuzzy probability, one or more discrete intervals are selected to estimate the real value of GMPP. At last, the variable step-size P&O method is adopted to get a more accurate result in these selected intervals. In fact, the information diffusion is a global fuzzy probability estimation algorithm. It has a good global search characteristic. The comprehensive simulations and experiments have fully demonstrated the efficacy and applicability of the proposed method in this paper. [ABSTRACT FROM AUTHOR]

This paper deals with photovoltaic-thermal (PV/T) collectors that combine photovoltaic (PV) module and solar thermal (ST) modules to provide heat and electricity simultaneously. The use of a PV/T system not only enhances PV efficiency but also allows to use solar thermal energy for various heating applications. The performance evaluation of the PV/T collectors had been investigated both theoretically and experimentally for the past few years. In this work, we consider a new water-based PV/T configuration by incorporating a tedlar layer and parallel tubes and further investigate its modeling. The aim is to develop a non-linear dynamic model which gives a realistic and reasonable performance of the system. The fundamental equations are determined for the thermal part using a bond graph approach which is a generic and general tool to represent thermal transfers. Simulations are given to highlight the usefulness of the proposed design and its modeling, considering the influence of some external factors (e.g. wind action) and internal geometrical parameters (e.g. insulator thickness). The results indicate that the rise in wind speed can reduce thermal efficiency from 70% to approximately 40%. The results also show that with an increase in insulator thickness, there is a sudden change in outlet temperature but thicknesses of more than 0.14 m is not required as the energy losses become constant. The assessment of the electrical and thermal performance of a PV/T collector is taken into consideration for a sample weather condition of southern France. Further, our results are compared to existing experimental and numerical ones from the literature on alternative PV/Ts design to validate and demonstrate the viability and consistency of our model. [ABSTRACT FROM AUTHOR]

[Display omitted] • A new 'winged' solar concentrator was developed to enable biomass conversion at 150 °C. • An evacuated solar tube was placed at the focal line to serve as a biomass reactor. • The wings boosted the thermal efficiency of the design from ~18% to ~25% at 150 °C. • The 'on-sun' 5-HMF yield was ~21 mol % from a sucrose source in the biomass reactor. • A CFD model was developed to investigate the thermochemical behaviours of the reaction. Biomass-derived alcohols such as 5-Hydroxymethylfurfural represent a promising intermediary energy and species carriers for hydrogen and value‐added chemical production. Solar-driven reforming of biomass to 5-HMF at the desired reaction condition (e.g., at ~150 °C and ~5 bars) offers a sustainable route, but the lack of a rooftop-based solar biomass reactor represents a substantial impediment. In this work, a unique, low-profile "winged" solar concentrator with an evacuated tube reactor was designed for the renewable production of 5-HMF. The viability of this design was examined in detail, using sucrose as the feedstock for 5-HMF production in the presence of sulfuric acid. The optical study indicated that the winged structure significantly increased the effective concentration ratio (by ~42%) and that the design has a broader acceptance angle (from 60° to 90°) compared to CPC alone. During outdoor experiments, the wings boosted the thermal efficiency from 18% to ~25% when operating at 150 °C, and achieved a maximum 5-HMF yield of ~21 mol % (under a solar irradiance of ~800 W/m2). In parallel, a transient computational fluid dynamics model was developed to further elucidate the heat and mass transfer phenomena inside the reactor and to investigate a broader range of operating conditions and reactor design parameters. The numerical and experimental results were in agreement that a specific energy consumption for 5-HMF production of ~23 kWh/kg was achievable and that a full-scale system (~3 L reactor volume, 2.1 m2 gross area) can produce ~0.45 kg of 5-HMF per day, with an average daily solar input of 5 kWh/m2. [ABSTRACT FROM AUTHOR]

• Analysis of the new standard EN ISO 52010-1:2017. • Proposal for a calculation procedure alternative to EN ISO 52010-1:2017. • Comparative analysis among four different calculation methods on five European cities. • Discrepance between EN ISO 52010-1:2017 and the other considered procedures. A proper evaluation of the building energy consumption implies an accurate assessment of the solar gains and consequently an exact estimation of the direct and diffuse solar radiation on tilted and oriented surfaces. The new standard EN ISO 52016-1: 2017 introduces a new hourly methodology for the calculation of energy performance of buildings and is complemented by EN ISO 52010-1:2017, which specifies the procedure for the conversion of climate data for energy calculations. These standards represent a good compromise between the old EN ISO 13790:2008 and Trnsys, since they allow for a more accurate evaluation of energy consumption than the former, while being less onerous than the latter. In the present work, EN ISO 52010-1:2017 is analysed for the first time and an alternative calculation procedure is proposed. These two algorithms are then compared with two other irradiance splitting methods implemented in Meteonorm and Trnsys code. In order to test performance and limits of the different calculation algorithms, we make a comparison among such methods on five European cities characterized by different climatic characteristics. Results show that the model implemented in EN ISO 52010-1:2017 overestimates the diffuse solar irradiance on horizontal plane for all the considered locations, while the proposed procedure and those implemented in the Trnsys and Meteonorm softwares show similar results. Using Trnsys algorithm as a baseline, the proposed calculation algorithm gives the best approximation among the considered models for what concerns the direct, diffuse and global irradiance on vertical surfaces exposed to south, east and west. [ABSTRACT FROM AUTHOR]

• The electrical efficiency of the CPV/TSD system varies between 10.82% and 11.32%. • Drying rate was calculated to be 0.436 g matter/g dry matter.min for this system. • Overall thermal and exergy efficiency were found to be 20% and 8%, respectively. • Prediction results of ANN and SVM algorithms were compared with four metrics. • It is noticed that ANN and SVM have the ability to successfully predict the drying parameters. In this paper, a concentrated photovoltaic-thermal solar dryer (CPV/TSD) using nano-enhanced PCM (Al 2 O 3 -Paraffin wax) is experimentally studied. A comprehensive thermodynamic analysis of the system according to the first and second laws is discussed. Besides, the drying parameters (moisture content and moisture ratio) are predicted using the two machine learning algorithms (ANN and SVM) and compared the prediction success with four evaluation metrics (R2, rRMSE, MBE, and rMAE). The overall thermal energy efficiency and exergy efficiency of the CPV/TSD system are found to be 20% and 8%, respectively. Although solar radiation to the environment has decreased a lot, it has been found that the thermal energy transferred to the nano-enhanced PCM prevents the decrease in greenhouse temperature for the first 100 min. In the system, mushrooms are dried from the initial moisture content of 17.45 g water/g dry matter to the final moisture content of 0.0515 g water/g dry matter. Then the drying rate value for CPV/TSD system is calculated to be 0.436 g matter/g dry matter.min. On the other hand, even if both ANN and SVM algorithms have exhibited very satisfying results, ANN is coming to the fore in the prediction of the drying parameters considering all evaluation metrics together. [ABSTRACT FROM AUTHOR]